Características del total de pacientes
- Situación al ingreso
- Variables relacionadas con el trauma
- Variables relacionadas con el fallo orgánico
- Variables relacionadas con los procedimientos
- Variables relacionadas con la complicaciones
- Variables relacionadas con la analítica
- Variables relacionadas con la estancia/pronóstico
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Data summary
| Name |
tce2 |
| Number of rows |
125 |
| Number of columns |
109 |
| _______________________ |
|
| Column type frequency: |
|
| numeric |
102 |
| POSIXct |
7 |
| ________________________ |
|
| Group variables |
None |
Variable type: numeric
| num_caso |
0 |
1.00 |
63.00 |
36.23 |
1.00 |
32.00 |
63.00 |
94.00 |
125.00 |
▇▇▇▇▇ |
| nhc |
0 |
1.00 |
678627.97 |
199185.63 |
218611.00 |
509494.00 |
795529.00 |
843002.00 |
861472.00 |
▂▂▁▂▇ |
| edad |
0 |
1.00 |
54.94 |
21.21 |
15.00 |
38.00 |
60.00 |
73.00 |
91.00 |
▅▃▅▇▆ |
| sexo |
0 |
1.00 |
0.24 |
0.43 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▂ |
| procedencia |
0 |
1.00 |
1.40 |
0.80 |
1.00 |
1.00 |
1.00 |
1.00 |
3.00 |
▇▁▁▁▂ |
| antitromboticos |
0 |
1.00 |
0.39 |
0.91 |
0.00 |
0.00 |
0.00 |
0.00 |
5.00 |
▇▁▁▁▁ |
| mecanismo |
0 |
1.00 |
5.85 |
4.28 |
1.00 |
1.00 |
4.00 |
8.00 |
15.00 |
▇▆▇▂▂ |
| tipo_trauma |
0 |
1.00 |
0.05 |
0.21 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| at_prehosp |
0 |
1.00 |
2.87 |
0.68 |
0.00 |
3.00 |
3.00 |
3.00 |
4.00 |
▁▁▁▇▁ |
| iot_pre |
0 |
1.00 |
0.26 |
0.44 |
0.00 |
0.00 |
0.00 |
1.00 |
1.00 |
▇▁▁▁▃ |
| psicot |
0 |
1.00 |
0.29 |
0.62 |
0.00 |
0.00 |
0.00 |
0.00 |
2.00 |
▇▁▁▁▁ |
| drogas |
0 |
1.00 |
0.07 |
0.26 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| alcohol |
0 |
1.00 |
0.08 |
0.27 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| pupila_ing |
0 |
1.00 |
0.26 |
0.61 |
0.00 |
0.00 |
0.00 |
0.00 |
2.00 |
▇▁▁▁▁ |
| atx |
0 |
1.00 |
0.06 |
0.25 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| calcio |
0 |
1.00 |
0.03 |
0.18 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| pcr_extrahosp_24h |
123 |
0.02 |
1.00 |
0.00 |
1.00 |
1.00 |
1.00 |
1.00 |
1.00 |
▁▁▇▁▁ |
| fc |
9 |
0.93 |
84.81 |
23.26 |
0.00 |
72.50 |
85.00 |
95.50 |
187.00 |
▁▃▇▁▁ |
| fr |
32 |
0.74 |
17.88 |
5.83 |
0.00 |
15.00 |
16.00 |
20.00 |
50.00 |
▁▇▂▁▁ |
| tas |
7 |
0.94 |
134.67 |
34.93 |
0.00 |
116.00 |
130.00 |
149.00 |
251.00 |
▁▁▇▂▁ |
| gcs_ing |
0 |
1.00 |
11.19 |
4.44 |
3.00 |
7.00 |
14.00 |
15.00 |
15.00 |
▂▂▁▁▇ |
| rts |
32 |
0.74 |
6.83 |
1.51 |
0.00 |
5.96 |
7.84 |
7.84 |
7.84 |
▁▁▁▂▇ |
| t_rts |
76 |
0.39 |
10.88 |
2.10 |
0.00 |
10.00 |
12.00 |
12.00 |
12.00 |
▁▁▁▁▇ |
| supervivencia |
32 |
0.74 |
87.88 |
19.58 |
2.70 |
80.70 |
98.80 |
98.80 |
99.41 |
▁▁▁▁▇ |
| retrascore |
0 |
1.00 |
5.62 |
4.53 |
0.00 |
2.00 |
5.00 |
8.00 |
21.00 |
▇▅▃▁▁ |
| tce_unico |
0 |
1.00 |
0.30 |
0.46 |
0.00 |
0.00 |
0.00 |
1.00 |
1.00 |
▇▁▁▁▃ |
| gravedad |
0 |
1.00 |
1.79 |
0.90 |
1.00 |
1.00 |
1.00 |
3.00 |
3.00 |
▇▁▂▁▅ |
| marshall |
0 |
1.00 |
2.44 |
1.58 |
0.00 |
1.00 |
2.00 |
2.00 |
6.00 |
▅▇▁▁▃ |
| mais_cyc |
0 |
1.00 |
3.14 |
1.65 |
0.00 |
2.00 |
3.00 |
5.00 |
5.00 |
▅▅▆▆▇ |
| mais_torax |
22 |
0.82 |
1.96 |
1.46 |
0.00 |
0.00 |
3.00 |
3.00 |
5.00 |
▆▃▇▁▁ |
| mais_abdomen |
40 |
0.68 |
0.88 |
1.30 |
0.00 |
0.00 |
0.00 |
2.00 |
5.00 |
▇▂▁▁▁ |
| mais_extrem |
38 |
0.70 |
0.92 |
1.18 |
0.00 |
0.00 |
0.00 |
2.00 |
4.00 |
▇▁▃▂▁ |
| mais_cv |
115 |
0.08 |
2.90 |
0.99 |
2.00 |
2.00 |
3.00 |
3.00 |
5.00 |
▇▇▁▂▂ |
| iss |
0 |
1.00 |
21.07 |
11.36 |
0.00 |
13.00 |
22.00 |
25.00 |
59.00 |
▅▇▇▁▁ |
| apache_ii |
3 |
0.98 |
16.40 |
8.30 |
2.00 |
10.00 |
14.50 |
21.00 |
41.00 |
▅▇▅▂▁ |
| sofa_ingreso |
1 |
0.99 |
2.97 |
3.36 |
0.00 |
1.00 |
2.00 |
4.00 |
16.00 |
▇▂▁▁▁ |
| sofa_sn |
1 |
0.99 |
1.51 |
1.60 |
0.00 |
0.00 |
1.00 |
3.00 |
4.00 |
▇▃▁▃▃ |
| sofa_cv |
1 |
0.99 |
0.77 |
1.34 |
0.00 |
0.00 |
0.00 |
1.00 |
4.00 |
▇▁▁▂▁ |
| sofa_res |
1 |
0.99 |
0.90 |
1.03 |
0.00 |
0.00 |
1.00 |
2.00 |
4.00 |
▇▅▃▂▁ |
| sofa_renal |
1 |
0.99 |
0.13 |
0.36 |
0.00 |
0.00 |
0.00 |
0.00 |
2.00 |
▇▁▁▁▁ |
| sofa_higado |
1 |
0.99 |
0.14 |
0.45 |
0.00 |
0.00 |
0.00 |
0.00 |
2.00 |
▇▁▁▁▁ |
| sofa_coag |
2 |
0.98 |
0.25 |
0.55 |
0.00 |
0.00 |
0.00 |
0.00 |
3.00 |
▇▂▁▁▁ |
| neurcx_urg |
0 |
1.00 |
0.11 |
0.32 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| cx_urg |
0 |
1.00 |
0.09 |
0.28 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| cx_no_urg |
0 |
1.00 |
0.17 |
0.45 |
0.00 |
0.00 |
0.00 |
0.00 |
3.00 |
▇▁▁▁▁ |
| ch_24h |
0 |
1.00 |
0.56 |
1.54 |
0.00 |
0.00 |
0.00 |
0.00 |
10.00 |
▇▁▁▁▁ |
| pfc |
0 |
1.00 |
0.23 |
0.82 |
0.00 |
0.00 |
0.00 |
0.00 |
6.00 |
▇▁▁▁▁ |
| fibrinogeno |
0 |
1.00 |
0.02 |
0.13 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| plaquetas |
0 |
1.00 |
0.08 |
0.30 |
0.00 |
0.00 |
0.00 |
0.00 |
2.00 |
▇▁▁▁▁ |
| arterio |
0 |
1.00 |
0.02 |
0.13 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| vm |
0 |
1.00 |
0.53 |
0.50 |
0.00 |
0.00 |
1.00 |
1.00 |
1.00 |
▇▁▁▁▇ |
| vm_dias |
0 |
1.00 |
4.73 |
8.84 |
0.00 |
0.00 |
1.00 |
6.00 |
67.00 |
▇▁▁▁▁ |
| drenaje_toracico |
0 |
1.00 |
0.15 |
0.36 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▂ |
| traqueo |
0 |
1.00 |
0.06 |
0.25 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| pic |
0 |
1.00 |
0.22 |
0.53 |
0.00 |
0.00 |
0.00 |
0.00 |
3.00 |
▇▁▁▁▁ |
| pic_dias |
0 |
1.00 |
1.03 |
2.69 |
0.00 |
0.00 |
0.00 |
0.00 |
14.00 |
▇▁▁▁▁ |
| ptio2 |
0 |
1.00 |
0.02 |
0.15 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| craniectomia |
0 |
1.00 |
0.06 |
0.23 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| vasoactivos |
0 |
1.00 |
0.33 |
0.47 |
0.00 |
0.00 |
0.00 |
1.00 |
1.00 |
▇▁▁▁▃ |
| hemodinamica |
0 |
1.00 |
0.66 |
0.94 |
0.00 |
0.00 |
0.00 |
2.00 |
3.00 |
▇▁▁▃▁ |
| coagu_trauma |
0 |
1.00 |
0.08 |
0.27 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| rabdomiolisis |
0 |
1.00 |
0.09 |
0.28 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| hic |
0 |
1.00 |
0.20 |
0.40 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▂ |
| medidas_hic |
0 |
1.00 |
0.34 |
0.77 |
0.00 |
0.00 |
0.00 |
0.00 |
4.00 |
▇▁▁▁▁ |
| disf_resp |
1 |
0.99 |
0.46 |
0.50 |
0.00 |
0.00 |
0.00 |
1.00 |
1.00 |
▇▁▁▁▇ |
| p_f |
0 |
1.00 |
0.77 |
0.98 |
0.00 |
0.00 |
0.00 |
1.00 |
4.00 |
▇▅▂▁▁ |
| hemo_masiva |
0 |
1.00 |
0.03 |
0.18 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| sdmo |
0 |
1.00 |
0.08 |
0.27 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▁ |
| inf_nosocomial |
0 |
1.00 |
0.26 |
0.44 |
0.00 |
0.00 |
0.00 |
1.00 |
1.00 |
▇▁▁▁▃ |
| leucos |
1 |
0.99 |
6663.93 |
10606.50 |
5.40 |
11.47 |
15.25 |
12425.00 |
88000.00 |
▇▁▁▁▁ |
| nt |
5 |
0.96 |
5162.25 |
10611.92 |
11.30 |
80.27 |
87.80 |
9000.00 |
100000.00 |
▇▁▁▁▁ |
| linfos |
25 |
0.80 |
644.52 |
1246.48 |
0.60 |
6.72 |
15.05 |
900.00 |
5000.00 |
▇▁▁▁▁ |
| eos |
29 |
0.77 |
40.02 |
102.92 |
0.00 |
0.00 |
0.20 |
1.72 |
600.00 |
▇▁▁▁▁ |
| hb |
1 |
0.99 |
115.97 |
1148.32 |
6.70 |
11.57 |
13.15 |
14.30 |
12800.00 |
▇▁▁▁▁ |
| hto |
11 |
0.91 |
38.07 |
5.86 |
20.30 |
34.08 |
38.45 |
42.40 |
51.60 |
▁▃▇▇▂ |
| plq |
1 |
0.99 |
93762.44 |
113073.60 |
34.00 |
163.75 |
265.00 |
187000.00 |
396000.00 |
▇▁▃▂▁ |
| inr |
5 |
0.96 |
1.25 |
0.60 |
0.87 |
1.03 |
1.09 |
1.24 |
6.28 |
▇▁▁▁▁ |
| ap |
8 |
0.94 |
83.00 |
21.43 |
11.00 |
74.00 |
88.00 |
96.00 |
126.00 |
▁▁▃▇▂ |
| ttpa |
7 |
0.94 |
29.66 |
8.52 |
0.74 |
26.85 |
28.70 |
30.95 |
94.00 |
▁▇▁▁▁ |
| fibrinogeno_2 |
11 |
0.91 |
398.53 |
152.07 |
117.00 |
304.25 |
376.00 |
458.00 |
1062.00 |
▅▇▂▁▁ |
| gluc |
6 |
0.95 |
154.04 |
53.58 |
84.00 |
121.00 |
142.00 |
177.00 |
435.00 |
▇▂▁▁▁ |
| urea |
19 |
0.85 |
35.87 |
15.04 |
9.90 |
26.00 |
33.40 |
42.85 |
89.30 |
▅▇▃▁▁ |
| crea |
3 |
0.98 |
0.90 |
0.30 |
0.44 |
0.72 |
0.82 |
1.00 |
2.52 |
▇▅▂▁▁ |
| na |
3 |
0.98 |
136.84 |
4.31 |
108.00 |
136.00 |
137.00 |
138.75 |
150.00 |
▁▁▁▇▁ |
| k |
3 |
0.98 |
3.91 |
0.50 |
2.10 |
3.60 |
3.90 |
4.20 |
5.20 |
▁▂▇▆▂ |
| cl |
32 |
0.74 |
107.25 |
10.14 |
89.00 |
104.00 |
106.00 |
108.00 |
194.00 |
▇▁▁▁▁ |
| ca_ionico |
23 |
0.82 |
5.92 |
13.73 |
0.84 |
4.35 |
4.50 |
4.68 |
143.00 |
▇▁▁▁▁ |
| mg |
53 |
0.58 |
1.84 |
0.28 |
0.90 |
1.70 |
1.81 |
2.00 |
2.80 |
▁▂▇▂▁ |
| p |
54 |
0.57 |
2.96 |
0.79 |
1.10 |
2.50 |
3.00 |
3.41 |
5.32 |
▂▅▇▂▁ |
| alb |
76 |
0.39 |
3.29 |
0.69 |
1.60 |
3.00 |
3.30 |
3.70 |
4.30 |
▂▂▃▇▅ |
| bilit |
38 |
0.70 |
0.79 |
0.55 |
0.13 |
0.50 |
0.65 |
0.89 |
3.40 |
▇▃▁▁▁ |
| ph |
7 |
0.94 |
7.26 |
0.78 |
1.39 |
7.32 |
7.37 |
7.41 |
7.55 |
▁▁▁▁▇ |
| pco2 |
9 |
0.93 |
40.06 |
10.21 |
21.00 |
34.75 |
38.50 |
43.25 |
103.00 |
▇▇▁▁▁ |
| po2 |
15 |
0.88 |
99.35 |
60.74 |
21.00 |
54.25 |
84.00 |
129.75 |
400.00 |
▇▅▁▁▁ |
| hco3 |
8 |
0.94 |
22.51 |
3.49 |
10.90 |
21.00 |
23.00 |
24.80 |
31.30 |
▁▂▇▇▁ |
| eb |
17 |
0.86 |
-2.57 |
3.94 |
-19.90 |
-4.25 |
-2.00 |
-0.08 |
7.00 |
▁▁▃▇▁ |
| lactato |
11 |
0.91 |
2.43 |
1.88 |
0.50 |
1.30 |
1.85 |
2.88 |
13.10 |
▇▂▁▁▁ |
| dest_uci |
0 |
1.00 |
1.63 |
0.77 |
0.00 |
2.00 |
2.00 |
2.00 |
4.00 |
▂▁▇▁▁ |
| dias_uci |
1 |
0.99 |
8.40 |
10.54 |
0.00 |
2.00 |
4.00 |
11.25 |
73.00 |
▇▂▁▁▁ |
| dest_hosp |
1 |
0.99 |
2.43 |
1.27 |
0.00 |
2.00 |
3.00 |
3.00 |
4.00 |
▂▁▁▇▁ |
| ltsv |
1 |
0.99 |
0.17 |
0.38 |
0.00 |
0.00 |
0.00 |
0.00 |
1.00 |
▇▁▁▁▂ |
| m_rankin_alta_hospitalaria |
4 |
0.97 |
2.68 |
1.91 |
1.00 |
1.00 |
2.00 |
4.00 |
6.00 |
▇▂▁▁▂ |
Variable type: POSIXct
| f_nac |
0 |
1.00 |
1928-01-12 00:00:00 |
2007-08-12 00:00:00 |
1961-01-08 00:00:00 |
125 |
| f_trauma |
0 |
1.00 |
2019-01-08 00:00:00 |
2022-11-23 00:00:00 |
2021-04-24 00:00:00 |
114 |
| f_ing_hosp |
0 |
1.00 |
2019-01-08 00:00:00 |
2022-11-23 00:00:00 |
2021-04-24 00:00:00 |
112 |
| f_ing_uci |
0 |
1.00 |
2019-01-08 00:00:00 |
2022-11-23 00:00:00 |
2021-04-24 00:00:00 |
112 |
| h_ing_uci |
0 |
1.00 |
1899-12-31 00:10:00 |
2023-08-23 23:08:00 |
1899-12-31 16:05:00 |
114 |
| f_alta_uci |
0 |
1.00 |
2019-01-10 00:00:00 |
2023-10-25 00:00:00 |
2021-05-12 00:00:00 |
116 |
| f_alta_hosp |
2 |
0.98 |
2019-01-14 00:00:00 |
2023-07-17 00:00:00 |
2021-05-14 00:00:00 |
115 |
| Characteristic |
N = 125 |
| edad |
54.94 (21.21) 60.00 (38.00, 73.00) |
| sexo |
|
| 0 |
95.0 / 125.0 (76.0%) |
| 1 |
30.0 / 125.0 (24.0%) |
| procedencia |
|
| 1 |
100.0 / 125.0 (80.0%) |
| 3 |
25.0 / 125.0 (20.0%) |
| antitromboticos |
|
| 0 |
101.0 / 125.0 (80.8%) |
| 1 |
7.0 / 125.0 (5.6%) |
| 2 |
11.0 / 125.0 (8.8%) |
| 3 |
5.0 / 125.0 (4.0%) |
| 5 |
1.0 / 125.0 (0.8%) |
| mecanismo |
|
| 1 |
32.0 / 125.0 (25.6%) |
| 2 |
6.0 / 125.0 (4.8%) |
| 4 |
26.0 / 125.0 (20.8%) |
| 5 |
5.0 / 125.0 (4.0%) |
| 8 |
28.0 / 125.0 (22.4%) |
| 9 |
9.0 / 125.0 (7.2%) |
| 10 |
2.0 / 125.0 (1.6%) |
| 11 |
1.0 / 125.0 (0.8%) |
| 12 |
5.0 / 125.0 (4.0%) |
| 13 |
1.0 / 125.0 (0.8%) |
| 14 |
1.0 / 125.0 (0.8%) |
| 15 |
9.0 / 125.0 (7.2%) |
| tipo_trauma |
|
| 0 |
119.0 / 125.0 (95.2%) |
| 1 |
6.0 / 125.0 (4.8%) |
| at_prehosp |
|
| 0 |
1.0 / 125.0 (0.8%) |
| 1 |
8.0 / 125.0 (6.4%) |
| 2 |
8.0 / 125.0 (6.4%) |
| 3 |
97.0 / 125.0 (77.6%) |
| 4 |
11.0 / 125.0 (8.8%) |
| iot_pre |
|
| 0 |
93.0 / 125.0 (74.4%) |
| 1 |
32.0 / 125.0 (25.6%) |
| psicot |
|
| 0 |
100.0 / 125.0 (80.0%) |
| 1 |
14.0 / 125.0 (11.2%) |
| 2 |
11.0 / 125.0 (8.8%) |
| drogas |
|
| 0 |
116.0 / 125.0 (92.8%) |
| 1 |
9.0 / 125.0 (7.2%) |
| alcohol |
|
| 0 |
115.0 / 125.0 (92.0%) |
| 1 |
10.0 / 125.0 (8.0%) |
| pupila_ing |
|
| 0 |
104.0 / 125.0 (83.2%) |
| 1 |
10.0 / 125.0 (8.0%) |
| 2 |
11.0 / 125.0 (8.8%) |
| atx |
|
| 0 |
117.0 / 125.0 (93.6%) |
| 1 |
8.0 / 125.0 (6.4%) |
| calcio |
|
| 0 |
121.0 / 125.0 (96.8%) |
| 1 |
4.0 / 125.0 (3.2%) |
| fc |
84.81 (23.26) 85.00 (72.50, 95.50) |
| Unknown |
9 |
| fr |
17.88 (5.83) 16.00 (15.00, 20.00) |
| Unknown |
32 |
| tas |
134.67 (34.93) 130.00 (116.00, 149.00) |
| Unknown |
7 |
| gcs_ing |
11.19 (4.44) 14.00 (7.00, 15.00) |
| Characteristic |
N = 125 |
| rts |
6.83 (1.51) 7.84 (5.96, 7.84) |
| Unknown |
32 |
| t_rts |
|
| 0 |
1.0 / 49.0 (2.0%) |
| 8 |
6.0 / 49.0 (12.2%) |
| 10 |
7.0 / 49.0 (14.3%) |
| 11 |
5.0 / 49.0 (10.2%) |
| 12 |
30.0 / 49.0 (61.2%) |
| Unknown |
76 |
| supervivencia |
87.88 (19.58) 98.80 (80.70, 98.80) |
| Unknown |
32 |
| retrascore |
5.62 (4.53) 5.00 (2.00, 8.00) |
| tce_unico |
|
| 0 |
88.0 / 125.0 (70.4%) |
| 1 |
37.0 / 125.0 (29.6%) |
| gravedad |
|
| 1 |
66.0 / 125.0 (52.8%) |
| 2 |
19.0 / 125.0 (15.2%) |
| 3 |
40.0 / 125.0 (32.0%) |
| marshall |
|
| 0 |
1.0 / 125.0 (0.8%) |
| 1 |
33.0 / 125.0 (26.4%) |
| 2 |
60.0 / 125.0 (48.0%) |
| 3 |
5.0 / 125.0 (4.0%) |
| 4 |
4.0 / 125.0 (3.2%) |
| 5 |
11.0 / 125.0 (8.8%) |
| 6 |
11.0 / 125.0 (8.8%) |
| mais_cyc |
|
| 0 |
15.0 / 125.0 (12.0%) |
| 1 |
6.0 / 125.0 (4.8%) |
| 2 |
19.0 / 125.0 (15.2%) |
| 3 |
26.0 / 125.0 (20.8%) |
| 4 |
24.0 / 125.0 (19.2%) |
| 5 |
35.0 / 125.0 (28.0%) |
| mais_torax |
|
| 0 |
33.0 / 103.0 (32.0%) |
| 2 |
18.0 / 103.0 (17.5%) |
| 3 |
44.0 / 103.0 (42.7%) |
| 4 |
6.0 / 103.0 (5.8%) |
| 5 |
2.0 / 103.0 (1.9%) |
| Unknown |
22 |
| mais_abdomen |
|
| 0 |
55.0 / 85.0 (64.7%) |
| 1 |
1.0 / 85.0 (1.2%) |
| 2 |
18.0 / 85.0 (21.2%) |
| 3 |
7.0 / 85.0 (8.2%) |
| 4 |
3.0 / 85.0 (3.5%) |
| 5 |
1.0 / 85.0 (1.2%) |
| Unknown |
40 |
| mais_extrem |
|
| 0 |
51.0 / 87.0 (58.6%) |
| 1 |
4.0 / 87.0 (4.6%) |
| 2 |
21.0 / 87.0 (24.1%) |
| 3 |
10.0 / 87.0 (11.5%) |
| 4 |
1.0 / 87.0 (1.1%) |
| Unknown |
38 |
| mais_cv |
|
| 2 |
4.0 / 10.0 (40.0%) |
| 3 |
4.0 / 10.0 (40.0%) |
| 4 |
1.0 / 10.0 (10.0%) |
| 5 |
1.0 / 10.0 (10.0%) |
| Unknown |
115 |
| iss |
21.07 (11.36) 22.00 (13.00, 25.00) |
| Characteristic |
N = 125 |
| apache_ii |
16.40 (8.30) 14.50 (10.00, 21.00) |
| Unknown |
3 |
| sofa_ingreso |
2.97 (3.36) 2.00 (1.00, 4.00) |
| Unknown |
1 |
| sofa_sn |
1.51 (1.60) 1.00 (0.00, 3.00) |
| Unknown |
1 |
| sofa_cv |
0.77 (1.34) 0.00 (0.00, 1.00) |
| Unknown |
1 |
| sofa_res |
0.90 (1.03) 1.00 (0.00, 2.00) |
| Unknown |
1 |
| sofa_renal |
1.13 (0.36) 1.00 (1.00, 1.00) |
| Unknown |
1 |
| sofa_higado |
1.14 (0.45) 1.00 (1.00, 1.00) |
| Unknown |
1 |
| sofa_coag |
0.25 (0.55) 0.00 (0.00, 0.00) |
| Unknown |
2 |
| Characteristic |
N = 125 |
| neurcx_urg |
|
| 0 |
111.0 / 125.0 (88.8%) |
| 1 |
14.0 / 125.0 (11.2%) |
| cx_urg |
|
| 0 |
114.0 / 125.0 (91.2%) |
| 1 |
11.0 / 125.0 (8.8%) |
| cx_no_urg |
|
| 0 |
107.0 / 125.0 (85.6%) |
| 1 |
16.0 / 125.0 (12.8%) |
| 2 |
1.0 / 125.0 (0.8%) |
| 3 |
1.0 / 125.0 (0.8%) |
| ch_24h |
|
| 0 |
102.0 / 125.0 (81.6%) |
| 1 |
5.0 / 125.0 (4.0%) |
| 2 |
9.0 / 125.0 (7.2%) |
| 3 |
2.0 / 125.0 (1.6%) |
| 4 |
3.0 / 125.0 (2.4%) |
| 5 |
1.0 / 125.0 (0.8%) |
| 6 |
1.0 / 125.0 (0.8%) |
| 8 |
1.0 / 125.0 (0.8%) |
| 10 |
1.0 / 125.0 (0.8%) |
| pfc |
|
| 0 |
113.0 / 125.0 (90.4%) |
| 1 |
2.0 / 125.0 (1.6%) |
| 2 |
7.0 / 125.0 (5.6%) |
| 3 |
1.0 / 125.0 (0.8%) |
| 4 |
1.0 / 125.0 (0.8%) |
| 6 |
1.0 / 125.0 (0.8%) |
| fibrinogeno |
|
| 0 |
123.0 / 125.0 (98.4%) |
| 1 |
2.0 / 125.0 (1.6%) |
| plaquetas |
|
| 0 |
116.0 / 125.0 (92.8%) |
| 1 |
8.0 / 125.0 (6.4%) |
| 2 |
1.0 / 125.0 (0.8%) |
| arterio |
|
| 0 |
123.0 / 125.0 (98.4%) |
| 1 |
2.0 / 125.0 (1.6%) |
| vm |
|
| 0 |
59.0 / 125.0 (47.2%) |
| 1 |
66.0 / 125.0 (52.8%) |
| vm_dias |
4.73 (8.84) 1.00 (0.00, 6.00) |
| drenaje_toracico |
|
| 0 |
106.0 / 125.0 (84.8%) |
| 1 |
19.0 / 125.0 (15.2%) |
| traqueo |
|
| 0 |
117.0 / 125.0 (93.6%) |
| 1 |
8.0 / 125.0 (6.4%) |
| pic |
|
| 0 |
104.0 / 125.0 (83.2%) |
| 1 |
16.0 / 125.0 (12.8%) |
| 2 |
4.0 / 125.0 (3.2%) |
| 3 |
1.0 / 125.0 (0.8%) |
| pic_dias |
1.03 (2.69) 0.00 (0.00, 0.00) |
| ptio2 |
|
| 0 |
122.0 / 125.0 (97.6%) |
| 1 |
3.0 / 125.0 (2.4%) |
| craniectomia |
|
| 0 |
118.0 / 125.0 (94.4%) |
| 1 |
7.0 / 125.0 (5.6%) |
| vasoactivos |
|
| 0 |
84.0 / 125.0 (67.2%) |
| 1 |
41.0 / 125.0 (32.8%) |
| hemodinamica |
|
| 0 |
82.0 / 125.0 (65.6%) |
| 1 |
4.0 / 125.0 (3.2%) |
| 2 |
38.0 / 125.0 (30.4%) |
| 3 |
1.0 / 125.0 (0.8%) |
## pic_dias
## Min. : 0.000
## 1st Qu.: 0.000
## Median : 0.000
## Mean : 1.032
## 3rd Qu.: 0.000
## Max. :14.000
## pic_dias
## 0 1 2 3 4 5 6 8 9 10 11 12 14
## 103 1 2 4 4 2 1 3 1 1 1 1 1
## pic_dias
## 0 1 2 3 4 5 6 8 9 10 11 12 14
## 0.824 0.008 0.016 0.032 0.032 0.016 0.008 0.024 0.008 0.008 0.008 0.008 0.008
## pic_dias
## Min. : 2.00
## 1st Qu.: 4.00
## Median : 5.00
## Mean : 6.25
## 3rd Qu.: 8.00
## Max. :14.00
## pic_dias
## Min. : 0.000
## 1st Qu.: 0.000
## Median : 0.000
## Mean : 1.032
## 3rd Qu.: 0.000
## Max. :14.000
## vm_dias
## 0 1 2 3 4 5 6 7 8 10 11 12 13 14 15 16 17 18 19 23 25 26 36 67
## 59 15 7 4 4 2 5 2 2 1 4 1 3 1 2 3 1 3 1 1 1 1 1 1
## vm_dias
## 0 1 2 3 4 5 6 7 8 10 11 12 13
## 0.472 0.120 0.056 0.032 0.032 0.016 0.040 0.016 0.016 0.008 0.032 0.008 0.024
## 14 15 16 17 18 19 23 25 26 36 67
## 0.008 0.016 0.024 0.008 0.024 0.008 0.008 0.008 0.008 0.008 0.008
## vm_dias
## Min. : 1.000
## 1st Qu.: 2.000
## Median : 6.000
## Mean : 8.955
## 3rd Qu.:13.000
## Max. :67.000
| Characteristic |
N = 125 |
| coagu_trauma |
|
| 0 |
115.0 / 125.0 (92.0%) |
| 1 |
10.0 / 125.0 (8.0%) |
| rabdomiolisis |
|
| 0 |
114.0 / 125.0 (91.2%) |
| 1 |
11.0 / 125.0 (8.8%) |
| hic |
|
| 0 |
100.0 / 125.0 (80.0%) |
| 1 |
25.0 / 125.0 (20.0%) |
| medidas_hic |
|
| 0 |
98.0 / 125.0 (78.4%) |
| 1 |
16.0 / 125.0 (12.8%) |
| 2 |
8.0 / 125.0 (6.4%) |
| 3 |
1.0 / 125.0 (0.8%) |
| 4 |
2.0 / 125.0 (1.6%) |
| disf_resp |
|
| 0 |
67.0 / 124.0 (54.0%) |
| 1 |
57.0 / 124.0 (46.0%) |
| Unknown |
1 |
| p_f |
|
| 0 |
64.0 / 125.0 (51.2%) |
| 1 |
38.0 / 125.0 (30.4%) |
| 2 |
12.0 / 125.0 (9.6%) |
| 3 |
10.0 / 125.0 (8.0%) |
| 4 |
1.0 / 125.0 (0.8%) |
| hemo_masiva |
|
| 0 |
121.0 / 125.0 (96.8%) |
| 1 |
4.0 / 125.0 (3.2%) |
| sdmo |
|
| 0 |
115.0 / 125.0 (92.0%) |
| 1 |
10.0 / 125.0 (8.0%) |
| inf_nosocomial |
|
| 0 |
92.0 / 125.0 (73.6%) |
| 1 |
33.0 / 125.0 (26.4%) |
## medidas_hic
## 1 2 3 4
## 16 6 1 2
## medidas_hic
## 1 2 3 4
## 0.64 0.24 0.04 0.08
| Characteristic |
N = 125 |
| leucos |
6,663.93 (10,606.50) 15.25 (11.48, 12,425.00) |
| Unknown |
1 |
| nt |
5,162.26 (10,611.92) 87.80 (80.28, 9,000.00) |
| Unknown |
5 |
| linfos |
644.52 (1,246.48) 15.05 (6.73, 900.00) |
| Unknown |
25 |
| eos |
40.03 (102.92) 0.20 (0.00, 1.73) |
| Unknown |
29 |
| hb |
115.97 (1,148.32) 13.15 (11.58, 14.30) |
| Unknown |
1 |
| hto |
38.07 (5.86) 38.45 (34.08, 42.40) |
| Unknown |
11 |
| plq |
93,762.44 (113,073.60) 265.00 (163.75, 187,000.00) |
| Unknown |
1 |
| inr |
1.25 (0.60) 1.09 (1.03, 1.24) |
| Unknown |
5 |
| ap |
83.00 (21.43) 88.00 (74.00, 96.00) |
| Unknown |
8 |
| ttpa |
29.66 (8.52) 28.70 (26.85, 30.95) |
| Unknown |
7 |
| fibrinogeno_2 |
398.53 (152.07) 376.00 (304.25, 458.00) |
| Unknown |
11 |
| gluc |
154.04 (53.58) 142.00 (121.00, 177.00) |
| Unknown |
6 |
| urea |
35.87 (15.04) 33.40 (26.00, 42.85) |
| Unknown |
19 |
| crea |
0.90 (0.30) 0.83 (0.72, 1.00) |
| Unknown |
3 |
| na |
136.84 (4.31) 137.00 (136.00, 138.75) |
| Unknown |
3 |
| k |
3.91 (0.50) 3.90 (3.60, 4.20) |
| Unknown |
3 |
| cl |
107.25 (10.14) 106.00 (104.00, 108.00) |
| Unknown |
32 |
| ca_ionico |
5.92 (13.73) 4.50 (4.35, 4.68) |
| Unknown |
23 |
| mg |
1.84 (0.28) 1.82 (1.70, 2.00) |
| Unknown |
53 |
| p |
2.96 (0.79) 3.00 (2.50, 3.41) |
| Unknown |
54 |
| alb |
3.29 (0.69) 3.30 (3.00, 3.70) |
| Unknown |
76 |
| bilit |
0.79 (0.55) 0.65 (0.50, 0.89) |
| Unknown |
38 |
| ph |
7.26 (0.78) 7.37 (7.32, 7.41) |
| Unknown |
7 |
| pco2 |
40.06 (10.21) 38.50 (34.75, 43.25) |
| Unknown |
9 |
| po2 |
99.35 (60.74) 84.00 (54.25, 129.75) |
| Unknown |
15 |
| hco3 |
22.51 (3.49) 23.00 (21.00, 24.80) |
| Unknown |
8 |
| eb |
-2.57 (3.94) -2.00 (-4.25, -0.08) |
| Unknown |
17 |
| lactato |
2.43 (1.88) 1.85 (1.30, 2.88) |
| Unknown |
11 |
| Characteristic |
N = 125 |
| dest_uci |
|
| 0 |
18.0 / 125.0 (14.4%) |
| 1 |
13.0 / 125.0 (10.4%) |
| 2 |
92.0 / 125.0 (73.6%) |
| 3 |
1.0 / 125.0 (0.8%) |
| 4 |
1.0 / 125.0 (0.8%) |
| dias_uci |
8.40 (10.54) 4.00 (2.00, 11.25) |
| Unknown |
1 |
| est_hosp |
27.29 (131.42) 9.00 (5.00, 20.00) |
| Unknown |
2 |
| dest_hosp |
|
| 0 |
24.0 / 124.0 (19.4%) |
| 1 |
1.0 / 124.0 (0.8%) |
| 2 |
8.0 / 124.0 (6.5%) |
| 3 |
80.0 / 124.0 (64.5%) |
| 4 |
11.0 / 124.0 (8.9%) |
| Unknown |
1 |
| ltsv |
|
| 0 |
103.0 / 124.0 (83.1%) |
| 1 |
21.0 / 124.0 (16.9%) |
| Unknown |
1 |
| m_rankin_alta_hospitalaria |
|
| 1 |
50.0 / 121.0 (41.3%) |
| 2 |
23.0 / 121.0 (19.0%) |
| 3 |
13.0 / 121.0 (10.7%) |
| 4 |
9.0 / 121.0 (7.4%) |
| 5 |
3.0 / 121.0 (2.5%) |
| 6 |
23.0 / 121.0 (19.0%) |
| Unknown |
4 |
Análisis de variables de mas interés en función de exitus, opicu y
dependencia
- Creación de la variable exitus (0=No, 1=Sí), Opicu - ≥75a (0=No,
1=Si), Dependiente -Rankin >3 (0=No, 1=Si)
- Porcentajes y números absolutos de dichas variables
- Análisis de las variables mas interesantes separadas por grupos
- TCE unico VS TCE con mas lesiones
- Opicu VS no Opicu
- Mecanismo lesional en función de si es o no
OPICU
- Dependiente VS no dependiente
- Exitus VS no exitus
- Mortalidad en función de la gravedad del TCE
#crea la variable exitus en función de m_rankin_alta_hospitalaria
#cuando m_rankin_alta_hospitalaria == 6, exitus == 1
#cuando m_rankin_alta_hospitalaria != 6, exitus == 0
tce2 <- tce2 %>%
mutate(exitus = ifelse(m_rankin_alta_hospitalaria == 6, 1, 0))
#explora la variable creada exitus
tce2 %>%
dplyr::select(exitus) %>%
table()
## exitus
## 0 1
## 98 23
#explora la variable creada exitus y calcula los porcentajes
tce2 %>%
dplyr::select(exitus) %>%
table() %>%
proportions()
## exitus
## 0 1
## 0.8099174 0.1900826
#en relidad solo hay 23 fallecidos
#creo otra variable que se llame dependiente
#cuando m_rankin_alta_hospitalaria >3, dependiente == 1
#cuando m_rankin_alta_hospitalaria <=3, dependiente == 0
tce2 <- tce2 %>%
mutate(dependiente = ifelse(m_rankin_alta_hospitalaria > 3, 1, 0))
#explora la variable creada dependencia
tce2 %>%
dplyr::select(dependiente) %>%
table()
## dependiente
## 0 1
## 86 35
#explora la variable creada dependencia y calcula los porcentajes
tce2 %>%
dplyr::select(dependiente) %>%
table() %>%
proportions()
## dependiente
## 0 1
## 0.7107438 0.2892562
#crea la variable opicu para los pacientes con edad > 74 años
#cuando edad > 74, opicu == 1
#cuando edad <= 74, opicu == 0
tce2 <- tce2 %>%
mutate(opicu = ifelse(edad > 74, 1, 0))
#explora la variable creada opicu
tce2 %>%
dplyr::select(opicu) %>%
table()
## opicu
## 0 1
## 96 29
tce2 %>%
dplyr::select(opicu) %>%
table() %>%
proportions()
## opicu
## 0 1
## 0.768 0.232
#crea la variable marshall5vs6 siendo 0 los pacientes con marshall 5 y 1 los pacientes con marshall 6 y el resto son NA
tce2 <- tce2 %>%
mutate(marshall5vs6 = ifelse(marshall == 5, 0, ifelse(marshall == 6, 1, NA)))
#Analisis de tce puro cuando tce_unico == 1 vs resto
#selecciona las variables mas interesantes para hacer la tabla
tce_puro <- tce2 %>%
dplyr::select (tce_unico, edad, sexo, procedencia, antitromboticos, marshall, marshall5vs6, tipo_trauma,
at_prehosp, iot_pre, psicot, drogas, alcohol, pupila_ing, atx, calcio, fc, fr, tas, gcs_ing, retrascore, supervivencia, iss,
apache_ii, sofa_ingreso, neurcx_urg, cx_urg, cx_no_urg,
ch_24h, pfc, fibrinogeno, plaquetas, arterio, vm, drenaje_toracico,
traqueo, pic, ptio2, craniectomia, vasoactivos, hemodinamica,
coagu_trauma, rabdomiolisis, hic, medidas_hic, disf_resp, p_f,
hemo_masiva, sdmo, inf_nosocomial, leucos, nt, linfos, eos, hb, hto,
plq, inr, ap, ttpa, fibrinogeno_2, gluc, urea, crea, na, k, cl,
ca_ionico, mg, p, alb, bilit, ph, pco2, po2, hco3, eb, lactato,
dest_uci, dias_uci, est_hosp, dest_hosp, ltsv, m_rankin_alta_hospitalaria,
exitus, dependiente, opicu)
#crea una tabla con tbl1, en función de tce_unico
tce_puro %>%
tbl_summary(
by = tce_unico,
statistic = list(
all_continuous() ~ "{mean} ({sd}) {median} ({p25}, {p75})",
all_categorical() ~ "{n} / {N} ({p}%)"
),
digits = list(
all_continuous() ~ 2,
all_categorical() ~ 1
)
) %>%
bold_labels() %>%
add_difference()
## Warning for variable 'marshall5vs6':
## simpleWarning in stats::prop.test(df_counts$n, df_counts$N, conf.level = 0.95): Chi-squared approximation may be incorrect
| Characteristic |
0, N = 88 |
1, N = 37 |
Difference |
95% CI |
p-value |
| edad |
53.60 (21.05) 58.00 (37.75, 73.00) |
58.14 (21.53) 66.00 (44.00, 76.00) |
-4.5 |
-13, 3.8 |
0.3 |
| sexo |
|
|
0.08 |
-0.30, 0.46 |
|
| 0 |
66.0 / 88.0 (75.0%) |
29.0 / 37.0 (78.4%) |
|
|
|
| 1 |
22.0 / 88.0 (25.0%) |
8.0 / 37.0 (21.6%) |
|
|
|
| procedencia |
|
|
0.24 |
-0.14, 0.63 |
|
| 1 |
68.0 / 88.0 (77.3%) |
32.0 / 37.0 (86.5%) |
|
|
|
| 3 |
20.0 / 88.0 (22.7%) |
5.0 / 37.0 (13.5%) |
|
|
|
| antitromboticos |
|
|
-0.46 |
-0.85, -0.07 |
|
| 0 |
76.0 / 88.0 (86.4%) |
25.0 / 37.0 (67.6%) |
|
|
|
| 1 |
4.0 / 88.0 (4.5%) |
3.0 / 37.0 (8.1%) |
|
|
|
| 2 |
7.0 / 88.0 (8.0%) |
4.0 / 37.0 (10.8%) |
|
|
|
| 3 |
0.0 / 88.0 (0.0%) |
5.0 / 37.0 (13.5%) |
|
|
|
| 5 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| marshall |
|
|
-0.40 |
-0.78, -0.01 |
|
| 0 |
0.0 / 88.0 (0.0%) |
1.0 / 37.0 (2.7%) |
|
|
|
| 1 |
27.0 / 88.0 (30.7%) |
6.0 / 37.0 (16.2%) |
|
|
|
| 2 |
43.0 / 88.0 (48.9%) |
17.0 / 37.0 (45.9%) |
|
|
|
| 3 |
5.0 / 88.0 (5.7%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 4 |
0.0 / 88.0 (0.0%) |
4.0 / 37.0 (10.8%) |
|
|
|
| 5 |
8.0 / 88.0 (9.1%) |
3.0 / 37.0 (8.1%) |
|
|
|
| 6 |
5.0 / 88.0 (5.7%) |
6.0 / 37.0 (16.2%) |
|
|
|
| marshall5vs6 |
5.0 / 13.0 (38.5%) |
6.0 / 9.0 (66.7%) |
-28% |
-78%, 22% |
0.4 |
| Unknown |
75 |
28 |
|
|
|
| tipo_trauma |
|
|
0.04 |
-0.34, 0.42 |
|
| 0 |
84.0 / 88.0 (95.5%) |
35.0 / 37.0 (94.6%) |
|
|
|
| 1 |
4.0 / 88.0 (4.5%) |
2.0 / 37.0 (5.4%) |
|
|
|
| at_prehosp |
|
|
0.24 |
-0.15, 0.62 |
|
| 0 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 1 |
4.0 / 88.0 (4.5%) |
4.0 / 37.0 (10.8%) |
|
|
|
| 2 |
5.0 / 88.0 (5.7%) |
3.0 / 37.0 (8.1%) |
|
|
|
| 3 |
69.0 / 88.0 (78.4%) |
28.0 / 37.0 (75.7%) |
|
|
|
| 4 |
9.0 / 88.0 (10.2%) |
2.0 / 37.0 (5.4%) |
|
|
|
| iot_pre |
|
|
0.05 |
-0.34, 0.43 |
|
| 0 |
66.0 / 88.0 (75.0%) |
27.0 / 37.0 (73.0%) |
|
|
|
| 1 |
22.0 / 88.0 (25.0%) |
10.0 / 37.0 (27.0%) |
|
|
|
| psicot |
|
|
0.15 |
-0.23, 0.54 |
|
| 0 |
72.0 / 88.0 (81.8%) |
28.0 / 37.0 (75.7%) |
|
|
|
| 1 |
9.0 / 88.0 (10.2%) |
5.0 / 37.0 (13.5%) |
|
|
|
| 2 |
7.0 / 88.0 (8.0%) |
4.0 / 37.0 (10.8%) |
|
|
|
| drogas |
|
|
0.10 |
-0.28, 0.49 |
|
| 0 |
81.0 / 88.0 (92.0%) |
35.0 / 37.0 (94.6%) |
|
|
|
| 1 |
7.0 / 88.0 (8.0%) |
2.0 / 37.0 (5.4%) |
|
|
|
| alcohol |
|
|
0.27 |
-0.12, 0.65 |
|
| 0 |
83.0 / 88.0 (94.3%) |
32.0 / 37.0 (86.5%) |
|
|
|
| 1 |
5.0 / 88.0 (5.7%) |
5.0 / 37.0 (13.5%) |
|
|
|
| pupila_ing |
|
|
0.17 |
-0.22, 0.55 |
|
| 0 |
73.0 / 88.0 (83.0%) |
31.0 / 37.0 (83.8%) |
|
|
|
| 1 |
8.0 / 88.0 (9.1%) |
2.0 / 37.0 (5.4%) |
|
|
|
| 2 |
7.0 / 88.0 (8.0%) |
4.0 / 37.0 (10.8%) |
|
|
|
| atx |
|
|
0.45 |
0.06, 0.84 |
|
| 0 |
80.0 / 88.0 (90.9%) |
37.0 / 37.0 (100.0%) |
|
|
|
| 1 |
8.0 / 88.0 (9.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| calcio |
|
|
0.31 |
-0.08, 0.69 |
|
| 0 |
84.0 / 88.0 (95.5%) |
37.0 / 37.0 (100.0%) |
|
|
|
| 1 |
4.0 / 88.0 (4.5%) |
0.0 / 37.0 (0.0%) |
|
|
|
| fc |
87.46 (25.78) 85.00 (73.00, 98.00) |
78.69 (14.54) 81.00 (69.50, 89.50) |
8.8 |
1.3, 16 |
0.022 |
| Unknown |
7 |
2 |
|
|
|
| fr |
17.38 (5.14) 16.00 (15.00, 18.25) |
19.00 (7.10) 18.00 (15.00, 20.00) |
-1.6 |
-4.6, 1.3 |
0.3 |
| Unknown |
24 |
8 |
|
|
|
| tas |
132.04 (35.51) 130.00 (112.25, 147.00) |
140.67 (33.29) 130.00 (121.00, 149.75) |
-8.6 |
-22, 4.9 |
0.2 |
| Unknown |
6 |
1 |
|
|
|
| gcs_ing |
11.56 (4.37) 14.00 (7.00, 15.00) |
10.32 (4.56) 12.00 (7.00, 14.00) |
1.2 |
-0.53, 3.0 |
0.2 |
| retrascore |
5.15 (4.36) 4.50 (2.00, 7.00) |
6.73 (4.81) 6.00 (3.00, 9.00) |
-1.6 |
-3.4, 0.25 |
0.089 |
| supervivencia |
88.38 (22.06) 98.80 (89.10, 98.80) |
86.77 (12.75) 91.90 (80.70, 98.80) |
1.6 |
-5.6, 8.8 |
0.7 |
| Unknown |
24 |
8 |
|
|
|
| iss |
22.83 (11.74) 22.00 (13.00, 29.00) |
16.89 (9.24) 16.00 (9.00, 25.00) |
5.9 |
2.0, 9.9 |
0.003 |
| apache_ii |
15.86 (7.91) 14.00 (10.00, 20.75) |
17.69 (9.15) 16.50 (11.00, 23.00) |
-1.8 |
-5.3, 1.7 |
0.3 |
| Unknown |
2 |
1 |
|
|
|
| sofa_ingreso |
3.17 (3.56) 2.00 (1.00, 4.50) |
2.49 (2.82) 2.00 (0.00, 3.00) |
0.69 |
-0.51, 1.9 |
0.3 |
| Unknown |
1 |
0 |
|
|
|
| neurcx_urg |
|
|
0.10 |
-0.28, 0.49 |
|
| 0 |
79.0 / 88.0 (89.8%) |
32.0 / 37.0 (86.5%) |
|
|
|
| 1 |
9.0 / 88.0 (10.2%) |
5.0 / 37.0 (13.5%) |
|
|
|
| cx_urg |
|
|
0.53 |
0.14, 0.92 |
|
| 0 |
77.0 / 88.0 (87.5%) |
37.0 / 37.0 (100.0%) |
|
|
|
| 1 |
11.0 / 88.0 (12.5%) |
0.0 / 37.0 (0.0%) |
|
|
|
| cx_no_urg |
|
|
0.55 |
0.16, 0.94 |
|
| 0 |
71.0 / 88.0 (80.7%) |
36.0 / 37.0 (97.3%) |
|
|
|
| 1 |
15.0 / 88.0 (17.0%) |
1.0 / 37.0 (2.7%) |
|
|
|
| 2 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 3 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| ch_24h |
|
|
0.57 |
0.17, 0.96 |
|
| 0 |
66.0 / 88.0 (75.0%) |
36.0 / 37.0 (97.3%) |
|
|
|
| 1 |
5.0 / 88.0 (5.7%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 2 |
8.0 / 88.0 (9.1%) |
1.0 / 37.0 (2.7%) |
|
|
|
| 3 |
2.0 / 88.0 (2.3%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 4 |
3.0 / 88.0 (3.4%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 5 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 6 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 8 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 10 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| pfc |
|
|
0.48 |
0.10, 0.87 |
|
| 0 |
76.0 / 88.0 (86.4%) |
37.0 / 37.0 (100.0%) |
|
|
|
| 1 |
2.0 / 88.0 (2.3%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 2 |
7.0 / 88.0 (8.0%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 3 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 4 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 6 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| fibrinogeno |
|
|
0.22 |
-0.17, 0.60 |
|
| 0 |
86.0 / 88.0 (97.7%) |
37.0 / 37.0 (100.0%) |
|
|
|
| 1 |
2.0 / 88.0 (2.3%) |
0.0 / 37.0 (0.0%) |
|
|
|
| plaquetas |
|
|
0.18 |
-0.21, 0.56 |
|
| 0 |
82.0 / 88.0 (93.2%) |
34.0 / 37.0 (91.9%) |
|
|
|
| 1 |
5.0 / 88.0 (5.7%) |
3.0 / 37.0 (8.1%) |
|
|
|
| 2 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| arterio |
|
|
0.11 |
-0.27, 0.50 |
|
| 0 |
87.0 / 88.0 (98.9%) |
36.0 / 37.0 (97.3%) |
|
|
|
| 1 |
1.0 / 88.0 (1.1%) |
1.0 / 37.0 (2.7%) |
|
|
|
| vm |
|
|
0.11 |
-0.27, 0.50 |
|
| 0 |
43.0 / 88.0 (48.9%) |
16.0 / 37.0 (43.2%) |
|
|
|
| 1 |
45.0 / 88.0 (51.1%) |
21.0 / 37.0 (56.8%) |
|
|
|
| drenaje_toracico |
|
|
0.74 |
0.35, 1.1 |
|
| 0 |
69.0 / 88.0 (78.4%) |
37.0 / 37.0 (100.0%) |
|
|
|
| 1 |
19.0 / 88.0 (21.6%) |
0.0 / 37.0 (0.0%) |
|
|
|
| traqueo |
|
|
0.24 |
-0.15, 0.62 |
|
| 0 |
81.0 / 88.0 (92.0%) |
36.0 / 37.0 (97.3%) |
|
|
|
| 1 |
7.0 / 88.0 (8.0%) |
1.0 / 37.0 (2.7%) |
|
|
|
| pic |
|
|
0.24 |
-0.15, 0.62 |
|
| 0 |
73.0 / 88.0 (83.0%) |
31.0 / 37.0 (83.8%) |
|
|
|
| 1 |
12.0 / 88.0 (13.6%) |
4.0 / 37.0 (10.8%) |
|
|
|
| 2 |
2.0 / 88.0 (2.3%) |
2.0 / 37.0 (5.4%) |
|
|
|
| 3 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| ptio2 |
|
|
0.27 |
-0.12, 0.65 |
|
| 0 |
85.0 / 88.0 (96.6%) |
37.0 / 37.0 (100.0%) |
|
|
|
| 1 |
3.0 / 88.0 (3.4%) |
0.0 / 37.0 (0.0%) |
|
|
|
| craniectomia |
|
|
0.15 |
-0.24, 0.53 |
|
| 0 |
84.0 / 88.0 (95.5%) |
34.0 / 37.0 (91.9%) |
|
|
|
| 1 |
4.0 / 88.0 (4.5%) |
3.0 / 37.0 (8.1%) |
|
|
|
| vasoactivos |
|
|
0.18 |
-0.21, 0.56 |
|
| 0 |
57.0 / 88.0 (64.8%) |
27.0 / 37.0 (73.0%) |
|
|
|
| 1 |
31.0 / 88.0 (35.2%) |
10.0 / 37.0 (27.0%) |
|
|
|
| hemodinamica |
|
|
0.42 |
0.03, 0.81 |
|
| 0 |
54.0 / 88.0 (61.4%) |
28.0 / 37.0 (75.7%) |
|
|
|
| 1 |
4.0 / 88.0 (4.5%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 2 |
29.0 / 88.0 (33.0%) |
9.0 / 37.0 (24.3%) |
|
|
|
| 3 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| coagu_trauma |
|
|
0.51 |
0.12, 0.90 |
|
| 0 |
78.0 / 88.0 (88.6%) |
37.0 / 37.0 (100.0%) |
|
|
|
| 1 |
10.0 / 88.0 (11.4%) |
0.0 / 37.0 (0.0%) |
|
|
|
| rabdomiolisis |
|
|
0.53 |
0.14, 0.92 |
|
| 0 |
77.0 / 88.0 (87.5%) |
37.0 / 37.0 (100.0%) |
|
|
|
| 1 |
11.0 / 88.0 (12.5%) |
0.0 / 37.0 (0.0%) |
|
|
|
| hic |
|
|
0.06 |
-0.33, 0.44 |
|
| 0 |
71.0 / 88.0 (80.7%) |
29.0 / 37.0 (78.4%) |
|
|
|
| 1 |
17.0 / 88.0 (19.3%) |
8.0 / 37.0 (21.6%) |
|
|
|
| medidas_hic |
|
|
-0.11 |
-0.49, 0.27 |
|
| 0 |
70.0 / 88.0 (79.5%) |
28.0 / 37.0 (75.7%) |
|
|
|
| 1 |
11.0 / 88.0 (12.5%) |
5.0 / 37.0 (13.5%) |
|
|
|
| 2 |
5.0 / 88.0 (5.7%) |
3.0 / 37.0 (8.1%) |
|
|
|
| 3 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 4 |
1.0 / 88.0 (1.1%) |
1.0 / 37.0 (2.7%) |
|
|
|
| disf_resp |
|
|
0.32 |
-0.07, 0.70 |
|
| 0 |
43.0 / 87.0 (49.4%) |
24.0 / 37.0 (64.9%) |
|
|
|
| 1 |
44.0 / 87.0 (50.6%) |
13.0 / 37.0 (35.1%) |
|
|
|
| Unknown |
1 |
0 |
|
|
|
| p_f |
|
|
0.45 |
0.06, 0.84 |
|
| 0 |
41.0 / 88.0 (46.6%) |
23.0 / 37.0 (62.2%) |
|
|
|
| 1 |
27.0 / 88.0 (30.7%) |
11.0 / 37.0 (29.7%) |
|
|
|
| 2 |
10.0 / 88.0 (11.4%) |
2.0 / 37.0 (5.4%) |
|
|
|
| 3 |
9.0 / 88.0 (10.2%) |
1.0 / 37.0 (2.7%) |
|
|
|
| 4 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| hemo_masiva |
|
|
0.31 |
-0.08, 0.69 |
|
| 0 |
84.0 / 88.0 (95.5%) |
37.0 / 37.0 (100.0%) |
|
|
|
| 1 |
4.0 / 88.0 (4.5%) |
0.0 / 37.0 (0.0%) |
|
|
|
| sdmo |
|
|
0.31 |
-0.08, 0.70 |
|
| 0 |
79.0 / 88.0 (89.8%) |
36.0 / 37.0 (97.3%) |
|
|
|
| 1 |
9.0 / 88.0 (10.2%) |
1.0 / 37.0 (2.7%) |
|
|
|
| inf_nosocomial |
|
|
0.02 |
-0.36, 0.40 |
|
| 0 |
65.0 / 88.0 (73.9%) |
27.0 / 37.0 (73.0%) |
|
|
|
| 1 |
23.0 / 88.0 (26.1%) |
10.0 / 37.0 (27.0%) |
|
|
|
| leucos |
7,313.21 (11,631.94) 22.20 (11.70, 12,350.00) |
5,137.26 (7,598.17) 14.00 (11.20, 12,500.00) |
2,176 |
-1,325, 5,677 |
0.2 |
| Unknown |
1 |
0 |
|
|
|
| nt |
5,819.00 (12,087.21) 90.30 (80.90, 9,025.00) |
3,629.86 (5,741.62) 86.85 (75.50, 7,950.00) |
2,189 |
-1,038, 5,416 |
0.2 |
| Unknown |
4 |
1 |
|
|
|
| linfos |
628.83 (1,223.24) 14.60 (7.25, 900.00) |
676.36 (1,311.14) 16.90 (6.50, 100.00) |
-48 |
-593, 498 |
0.9 |
| Unknown |
21 |
4 |
|
|
|
| eos |
39.83 (106.37) 0.10 (0.00, 1.78) |
40.46 (96.65) 0.40 (0.10, 1.53) |
-0.64 |
-45, 43 |
>0.9 |
| Unknown |
22 |
7 |
|
|
|
| hb |
159.76 (1,370.94) 13.10 (11.40, 14.20) |
13.02 (1.57) 13.40 (11.90, 14.30) |
147 |
-145, 439 |
0.3 |
| Unknown |
1 |
0 |
|
|
|
| hto |
37.59 (6.14) 38.20 (32.90, 42.28) |
39.12 (5.12) 39.60 (35.30, 43.00) |
-1.5 |
-3.7, 0.66 |
0.2 |
| Unknown |
10 |
1 |
|
|
|
| plq |
101,714.54 (114,660.46) 294.00 (169.00, 202,000.00) |
75,064.24 (108,468.14) 248.00 (158.00, 160,000.00) |
26,650 |
-16,530, 69,830 |
0.2 |
| Unknown |
1 |
0 |
|
|
|
| inr |
1.16 (0.23) 1.09 (1.03, 1.19) |
1.43 (1.00) 1.13 (1.03, 1.29) |
-0.27 |
-0.61, 0.07 |
0.12 |
| Unknown |
5 |
0 |
|
|
|
| ap |
85.14 (17.47) 90.00 (79.00, 96.00) |
78.19 (28.11) 84.00 (68.00, 95.25) |
6.9 |
-3.3, 17 |
0.2 |
| Unknown |
7 |
1 |
|
|
|
| ttpa |
29.40 (9.36) 28.20 (26.00, 30.70) |
30.23 (6.38) 29.00 (27.00, 31.00) |
-0.82 |
-3.8, 2.1 |
0.6 |
| Unknown |
7 |
0 |
|
|
|
| fibrinogeno_2 |
395.32 (156.47) 369.00 (295.00, 452.00) |
405.19 (144.34) 377.00 (319.00, 475.00) |
-9.9 |
-69, 49 |
0.7 |
| Unknown |
11 |
0 |
|
|
|
| gluc |
144.15 (37.58) 139.50 (118.25, 159.25) |
175.97 (74.27) 152.00 (131.00, 210.00) |
-32 |
-58, -5.8 |
0.017 |
| Unknown |
6 |
0 |
|
|
|
| urea |
35.00 (13.06) 32.95 (27.50, 42.30) |
37.88 (18.93) 36.20 (23.90, 46.90) |
-2.9 |
-10, 4.5 |
0.4 |
| Unknown |
14 |
5 |
|
|
|
| crea |
0.89 (0.30) 0.85 (0.72, 0.98) |
0.92 (0.32) 0.80 (0.73, 1.07) |
-0.03 |
-0.15, 0.10 |
0.7 |
| Unknown |
3 |
0 |
|
|
|
| na |
137.55 (2.82) 137.50 (136.00, 139.00) |
135.14 (6.39) 137.00 (133.00, 138.00) |
2.4 |
0.17, 4.6 |
0.036 |
| Unknown |
2 |
1 |
|
|
|
| k |
3.94 (0.51) 4.00 (3.63, 4.20) |
3.85 (0.47) 3.80 (3.58, 4.00) |
0.09 |
-0.10, 0.28 |
0.4 |
| Unknown |
2 |
1 |
|
|
|
| cl |
108.46 (11.79) 107.00 (104.00, 109.00) |
104.70 (4.40) 106.00 (104.00, 107.00) |
3.8 |
0.41, 7.1 |
0.028 |
| Unknown |
25 |
7 |
|
|
|
| ca_ionico |
4.48 (0.70) 4.50 (4.35, 4.69) |
9.21 (24.85) 4.53 (4.40, 4.66) |
-4.7 |
-14, 4.4 |
0.3 |
| Unknown |
17 |
6 |
|
|
|
| mg |
1.83 (0.26) 1.83 (1.70, 2.00) |
1.86 (0.32) 1.80 (1.70, 1.99) |
-0.03 |
-0.18, 0.12 |
0.7 |
| Unknown |
41 |
12 |
|
|
|
| p |
3.03 (0.82) 3.00 (2.50, 3.50) |
2.84 (0.75) 2.95 (2.45, 3.30) |
0.19 |
-0.19, 0.58 |
0.3 |
| Unknown |
43 |
11 |
|
|
|
| alb |
3.18 (0.76) 3.30 (2.60, 3.70) |
3.50 (0.47) 3.40 (3.28, 3.78) |
-0.32 |
-0.68, 0.04 |
0.081 |
| Unknown |
55 |
21 |
|
|
|
| bilit |
0.80 (0.58) 0.63 (0.50, 0.83) |
0.78 (0.50) 0.70 (0.40, 0.94) |
0.02 |
-0.22, 0.25 |
0.9 |
| Unknown |
30 |
8 |
|
|
|
| ph |
7.28 (0.66) 7.37 (7.32, 7.41) |
7.20 (1.02) 7.37 (7.33, 7.43) |
0.08 |
-0.30, 0.47 |
0.7 |
| Unknown |
4 |
3 |
|
|
|
| pco2 |
40.79 (11.34) 39.00 (34.25, 44.00) |
38.29 (6.53) 37.50 (35.00, 40.75) |
2.5 |
-0.84, 5.8 |
0.14 |
| Unknown |
6 |
3 |
|
|
|
| po2 |
96.81 (66.44) 80.00 (48.75, 125.75) |
105.03 (45.90) 103.00 (66.00, 137.50) |
-8.2 |
-30, 14 |
0.5 |
| Unknown |
12 |
3 |
|
|
|
| hco3 |
22.48 (3.59) 23.00 (20.95, 24.75) |
22.58 (3.29) 22.05 (21.30, 24.83) |
-0.10 |
-1.5, 1.3 |
0.9 |
| Unknown |
5 |
3 |
|
|
|
| eb |
-2.69 (4.15) -2.00 (-4.10, -0.60) |
-2.31 (3.47) -2.00 (-4.40, 0.10) |
-0.38 |
-1.9, 1.2 |
0.6 |
| Unknown |
13 |
4 |
|
|
|
| lactato |
2.58 (2.03) 2.00 (1.40, 2.90) |
2.06 (1.40) 1.70 (1.20, 2.60) |
0.51 |
-0.15, 1.2 |
0.13 |
| Unknown |
7 |
4 |
|
|
|
| dest_uci |
|
|
-0.03 |
-0.42, 0.35 |
|
| 0 |
12.0 / 88.0 (13.6%) |
6.0 / 37.0 (16.2%) |
|
|
|
| 1 |
12.0 / 88.0 (13.6%) |
1.0 / 37.0 (2.7%) |
|
|
|
| 2 |
62.0 / 88.0 (70.5%) |
30.0 / 37.0 (81.1%) |
|
|
|
| 3 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 4 |
1.0 / 88.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| dias_uci |
9.16 (11.47) 4.00 (2.00, 13.00) |
6.59 (7.76) 3.00 (2.00, 9.00) |
2.6 |
-0.95, 6.1 |
0.2 |
| Unknown |
1 |
0 |
|
|
|
| est_hosp |
16.98 (18.47) 10.00 (6.00, 20.50) |
51.27 (238.50) 8.00 (4.00, 19.00) |
-34 |
-114, 45 |
0.4 |
| Unknown |
2 |
0 |
|
|
|
| dest_hosp |
|
|
0.09 |
-0.30, 0.47 |
|
| 0 |
16.0 / 87.0 (18.4%) |
8.0 / 37.0 (21.6%) |
|
|
|
| 1 |
1.0 / 87.0 (1.1%) |
0.0 / 37.0 (0.0%) |
|
|
|
| 2 |
5.0 / 87.0 (5.7%) |
3.0 / 37.0 (8.1%) |
|
|
|
| 3 |
57.0 / 87.0 (65.5%) |
23.0 / 37.0 (62.2%) |
|
|
|
| 4 |
8.0 / 87.0 (9.2%) |
3.0 / 37.0 (8.1%) |
|
|
|
| Unknown |
1 |
0 |
|
|
|
| ltsv |
|
|
0.07 |
-0.31, 0.46 |
|
| 0 |
73.0 / 87.0 (83.9%) |
30.0 / 37.0 (81.1%) |
|
|
|
| 1 |
14.0 / 87.0 (16.1%) |
7.0 / 37.0 (18.9%) |
|
|
|
| Unknown |
1 |
0 |
|
|
|
| m_rankin_alta_hospitalaria |
|
|
-0.06 |
-0.45, 0.33 |
|
| 1 |
35.0 / 84.0 (41.7%) |
15.0 / 37.0 (40.5%) |
|
|
|
| 2 |
15.0 / 84.0 (17.9%) |
8.0 / 37.0 (21.6%) |
|
|
|
| 3 |
11.0 / 84.0 (13.1%) |
2.0 / 37.0 (5.4%) |
|
|
|
| 4 |
6.0 / 84.0 (7.1%) |
3.0 / 37.0 (8.1%) |
|
|
|
| 5 |
2.0 / 84.0 (2.4%) |
1.0 / 37.0 (2.7%) |
|
|
|
| 6 |
15.0 / 84.0 (17.9%) |
8.0 / 37.0 (21.6%) |
|
|
|
| Unknown |
4 |
0 |
|
|
|
| exitus |
15.0 / 84.0 (17.9%) |
8.0 / 37.0 (21.6%) |
-3.8% |
-21%, 14% |
0.8 |
| Unknown |
4 |
0 |
|
|
|
| dependiente |
23.0 / 84.0 (27.4%) |
12.0 / 37.0 (32.4%) |
-5.1% |
-25%, 15% |
0.7 |
| Unknown |
4 |
0 |
|
|
|
| opicu |
17.0 / 88.0 (19.3%) |
12.0 / 37.0 (32.4%) |
-13% |
-32%, 6.0% |
0.2 |
#crea una tabla con tb1, en función de opicu
tce_puro %>%
tbl_summary(
by = opicu,
statistic = list(
all_continuous() ~ "{mean} ({sd}) {median} ({p25}, {p75})",
all_categorical() ~ "{n} / {N} ({p}%)"
),
digits = list(
all_continuous() ~ 2,
all_categorical() ~ 1
)
) %>%
bold_labels() %>%
add_difference()
| Characteristic |
0, N = 96 |
1, N = 29 |
Difference |
95% CI |
p-value |
| tce_unico |
|
|
0.33 |
-0.09, 0.75 |
|
| 0 |
71.0 / 96.0 (74.0%) |
17.0 / 29.0 (58.6%) |
|
|
|
| 1 |
25.0 / 96.0 (26.0%) |
12.0 / 29.0 (41.4%) |
|
|
|
| edad |
47.42 (18.31) 48.50 (31.00, 65.00) |
79.86 (4.06) 79.00 (76.00, 82.00) |
-32 |
-36, -28 |
<0.001 |
| sexo |
|
|
0.21 |
-0.21, 0.62 |
|
| 0 |
75.0 / 96.0 (78.1%) |
20.0 / 29.0 (69.0%) |
|
|
|
| 1 |
21.0 / 96.0 (21.9%) |
9.0 / 29.0 (31.0%) |
|
|
|
| procedencia |
|
|
0.34 |
-0.07, 0.76 |
|
| 1 |
74.0 / 96.0 (77.1%) |
26.0 / 29.0 (89.7%) |
|
|
|
| 3 |
22.0 / 96.0 (22.9%) |
3.0 / 29.0 (10.3%) |
|
|
|
| antitromboticos |
|
|
-0.86 |
-1.3, -0.44 |
|
| 0 |
87.0 / 96.0 (90.6%) |
14.0 / 29.0 (48.3%) |
|
|
|
| 1 |
1.0 / 96.0 (1.0%) |
6.0 / 29.0 (20.7%) |
|
|
|
| 2 |
7.0 / 96.0 (7.3%) |
4.0 / 29.0 (13.8%) |
|
|
|
| 3 |
1.0 / 96.0 (1.0%) |
4.0 / 29.0 (13.8%) |
|
|
|
| 5 |
0.0 / 96.0 (0.0%) |
1.0 / 29.0 (3.4%) |
|
|
|
| marshall |
|
|
-0.55 |
-0.97, -0.13 |
|
| 0 |
1.0 / 96.0 (1.0%) |
0.0 / 29.0 (0.0%) |
|
|
|
| 1 |
26.0 / 96.0 (27.1%) |
7.0 / 29.0 (24.1%) |
|
|
|
| 2 |
49.0 / 96.0 (51.0%) |
11.0 / 29.0 (37.9%) |
|
|
|
| 3 |
5.0 / 96.0 (5.2%) |
0.0 / 29.0 (0.0%) |
|
|
|
| 4 |
4.0 / 96.0 (4.2%) |
0.0 / 29.0 (0.0%) |
|
|
|
| 5 |
8.0 / 96.0 (8.3%) |
3.0 / 29.0 (10.3%) |
|
|
|
| 6 |
3.0 / 96.0 (3.1%) |
8.0 / 29.0 (27.6%) |
|
|
|
| marshall5vs6 |
3.0 / 11.0 (27.3%) |
8.0 / 11.0 (72.7%) |
-45% |
-92%, 0.86% |
0.088 |
| Unknown |
85 |
18 |
|
|
|
| tipo_trauma |
|
|
0.09 |
-0.33, 0.50 |
|
| 0 |
91.0 / 96.0 (94.8%) |
28.0 / 29.0 (96.6%) |
|
|
|
| 1 |
5.0 / 96.0 (5.2%) |
1.0 / 29.0 (3.4%) |
|
|
|
| at_prehosp |
|
|
0.09 |
-0.33, 0.50 |
|
| 0 |
0.0 / 96.0 (0.0%) |
1.0 / 29.0 (3.4%) |
|
|
|
| 1 |
8.0 / 96.0 (8.3%) |
0.0 / 29.0 (0.0%) |
|
|
|
| 2 |
6.0 / 96.0 (6.3%) |
2.0 / 29.0 (6.9%) |
|
|
|
| 3 |
71.0 / 96.0 (74.0%) |
26.0 / 29.0 (89.7%) |
|
|
|
| 4 |
11.0 / 96.0 (11.5%) |
0.0 / 29.0 (0.0%) |
|
|
|
| iot_pre |
|
|
0.06 |
-0.36, 0.47 |
|
| 0 |
72.0 / 96.0 (75.0%) |
21.0 / 29.0 (72.4%) |
|
|
|
| 1 |
24.0 / 96.0 (25.0%) |
8.0 / 29.0 (27.6%) |
|
|
|
| psicot |
|
|
0.38 |
-0.04, 0.80 |
|
| 0 |
80.0 / 96.0 (83.3%) |
20.0 / 29.0 (69.0%) |
|
|
|
| 1 |
10.0 / 96.0 (10.4%) |
4.0 / 29.0 (13.8%) |
|
|
|
| 2 |
6.0 / 96.0 (6.3%) |
5.0 / 29.0 (17.2%) |
|
|
|
| drogas |
|
|
0.21 |
-0.21, 0.62 |
|
| 0 |
88.0 / 96.0 (91.7%) |
28.0 / 29.0 (96.6%) |
|
|
|
| 1 |
8.0 / 96.0 (8.3%) |
1.0 / 29.0 (3.4%) |
|
|
|
| alcohol |
|
|
0.48 |
0.06, 0.90 |
|
| 0 |
86.0 / 96.0 (89.6%) |
29.0 / 29.0 (100.0%) |
|
|
|
| 1 |
10.0 / 96.0 (10.4%) |
0.0 / 29.0 (0.0%) |
|
|
|
| pupila_ing |
|
|
0.38 |
-0.04, 0.80 |
|
| 0 |
83.0 / 96.0 (86.5%) |
21.0 / 29.0 (72.4%) |
|
|
|
| 1 |
7.0 / 96.0 (7.3%) |
3.0 / 29.0 (10.3%) |
|
|
|
| 2 |
6.0 / 96.0 (6.3%) |
5.0 / 29.0 (17.2%) |
|
|
|
| atx |
|
|
0.17 |
-0.24, 0.59 |
|
| 0 |
89.0 / 96.0 (92.7%) |
28.0 / 29.0 (96.6%) |
|
|
|
| 1 |
7.0 / 96.0 (7.3%) |
1.0 / 29.0 (3.4%) |
|
|
|
| calcio |
|
|
0.23 |
-0.18, 0.65 |
|
| 0 |
94.0 / 96.0 (97.9%) |
27.0 / 29.0 (93.1%) |
|
|
|
| 1 |
2.0 / 96.0 (2.1%) |
2.0 / 29.0 (6.9%) |
|
|
|
| fc |
88.13 (22.09) 85.00 (75.00, 97.00) |
73.85 (24.08) 70.00 (62.00, 87.50) |
14 |
3.8, 25 |
0.009 |
| Unknown |
7 |
2 |
|
|
|
| fr |
18.30 (5.99) 16.00 (15.00, 20.00) |
16.55 (5.19) 16.50 (15.00, 19.00) |
1.8 |
-0.91, 4.4 |
0.2 |
| Unknown |
25 |
7 |
|
|
|
| tas |
134.50 (28.20) 130.00 (116.00, 147.00) |
135.21 (51.65) 130.50 (113.50, 163.50) |
-0.71 |
-21, 20 |
>0.9 |
| Unknown |
6 |
1 |
|
|
|
| gcs_ing |
11.59 (4.16) 14.00 (7.75, 15.00) |
9.86 (5.14) 11.00 (3.00, 15.00) |
1.7 |
-0.38, 3.8 |
0.11 |
| retrascore |
4.38 (3.67) 4.00 (1.75, 6.00) |
9.72 (4.75) 9.00 (6.00, 12.00) |
-5.3 |
-7.3, -3.4 |
<0.001 |
| supervivencia |
90.07 (16.64) 98.80 (80.70, 98.80) |
80.80 (26.22) 91.90 (80.70, 98.80) |
9.3 |
-2.9, 21 |
0.13 |
| Unknown |
25 |
7 |
|
|
|
| iss |
20.83 (12.17) 20.00 (13.00, 26.00) |
21.86 (8.21) 25.00 (17.00, 25.00) |
-1.0 |
-5.0, 2.9 |
0.6 |
| apache_ii |
14.56 (6.92) 13.00 (9.00, 20.00) |
22.89 (9.54) 23.00 (14.00, 30.50) |
-8.3 |
-12, -4.3 |
<0.001 |
| Unknown |
1 |
2 |
|
|
|
| sofa_ingreso |
2.53 (2.93) 1.00 (0.75, 4.00) |
4.46 (4.27) 3.00 (1.00, 7.00) |
-1.9 |
-3.7, -0.18 |
0.031 |
| Unknown |
0 |
1 |
|
|
|
| neurcx_urg |
|
|
0.04 |
-0.38, 0.45 |
|
| 0 |
85.0 / 96.0 (88.5%) |
26.0 / 29.0 (89.7%) |
|
|
|
| 1 |
11.0 / 96.0 (11.5%) |
3.0 / 29.0 (10.3%) |
|
|
|
| cx_urg |
|
|
0.09 |
-0.32, 0.51 |
|
| 0 |
87.0 / 96.0 (90.6%) |
27.0 / 29.0 (93.1%) |
|
|
|
| 1 |
9.0 / 96.0 (9.4%) |
2.0 / 29.0 (6.9%) |
|
|
|
| cx_no_urg |
|
|
0.68 |
0.26, 1.1 |
|
| 0 |
78.0 / 96.0 (81.3%) |
29.0 / 29.0 (100.0%) |
|
|
|
| 1 |
16.0 / 96.0 (16.7%) |
0.0 / 29.0 (0.0%) |
|
|
|
| 2 |
1.0 / 96.0 (1.0%) |
0.0 / 29.0 (0.0%) |
|
|
|
| 3 |
1.0 / 96.0 (1.0%) |
0.0 / 29.0 (0.0%) |
|
|
|
| ch_24h |
|
|
-0.25 |
-0.66, 0.17 |
|
| 0 |
80.0 / 96.0 (83.3%) |
22.0 / 29.0 (75.9%) |
|
|
|
| 1 |
4.0 / 96.0 (4.2%) |
1.0 / 29.0 (3.4%) |
|
|
|
| 2 |
6.0 / 96.0 (6.3%) |
3.0 / 29.0 (10.3%) |
|
|
|
| 3 |
1.0 / 96.0 (1.0%) |
1.0 / 29.0 (3.4%) |
|
|
|
| 4 |
3.0 / 96.0 (3.1%) |
0.0 / 29.0 (0.0%) |
|
|
|
| 5 |
1.0 / 96.0 (1.0%) |
0.0 / 29.0 (0.0%) |
|
|
|
| 6 |
0.0 / 96.0 (0.0%) |
1.0 / 29.0 (3.4%) |
|
|
|
| 8 |
1.0 / 96.0 (1.0%) |
0.0 / 29.0 (0.0%) |
|
|
|
| 10 |
0.0 / 96.0 (0.0%) |
1.0 / 29.0 (3.4%) |
|
|
|
| pfc |
|
|
-0.28 |
-0.70, 0.13 |
|
| 0 |
88.0 / 96.0 (91.7%) |
25.0 / 29.0 (86.2%) |
|
|
|
| 1 |
2.0 / 96.0 (2.1%) |
0.0 / 29.0 (0.0%) |
|
|
|
| 2 |
5.0 / 96.0 (5.2%) |
2.0 / 29.0 (6.9%) |
|
|
|
| 3 |
0.0 / 96.0 (0.0%) |
1.0 / 29.0 (3.4%) |
|
|
|
| 4 |
1.0 / 96.0 (1.0%) |
0.0 / 29.0 (0.0%) |
|
|
|
| 6 |
0.0 / 96.0 (0.0%) |
1.0 / 29.0 (3.4%) |
|
|
|
| fibrinogeno |
|
|
0.16 |
-0.25, 0.58 |
|
| 0 |
95.0 / 96.0 (99.0%) |
28.0 / 29.0 (96.6%) |
|
|
|
| 1 |
1.0 / 96.0 (1.0%) |
1.0 / 29.0 (3.4%) |
|
|
|
| plaquetas |
|
|
0.27 |
-0.15, 0.69 |
|
| 0 |
90.0 / 96.0 (93.8%) |
26.0 / 29.0 (89.7%) |
|
|
|
| 1 |
6.0 / 96.0 (6.3%) |
2.0 / 29.0 (6.9%) |
|
|
|
| 2 |
0.0 / 96.0 (0.0%) |
1.0 / 29.0 (3.4%) |
|
|
|
| arterio |
|
|
0.16 |
-0.25, 0.58 |
|
| 0 |
95.0 / 96.0 (99.0%) |
28.0 / 29.0 (96.6%) |
|
|
|
| 1 |
1.0 / 96.0 (1.0%) |
1.0 / 29.0 (3.4%) |
|
|
|
| vm |
|
|
0.34 |
-0.08, 0.76 |
|
| 0 |
49.0 / 96.0 (51.0%) |
10.0 / 29.0 (34.5%) |
|
|
|
| 1 |
47.0 / 96.0 (49.0%) |
19.0 / 29.0 (65.5%) |
|
|
|
| drenaje_toracico |
|
|
0.33 |
-0.08, 0.75 |
|
| 0 |
79.0 / 96.0 (82.3%) |
27.0 / 29.0 (93.1%) |
|
|
|
| 1 |
17.0 / 96.0 (17.7%) |
2.0 / 29.0 (6.9%) |
|
|
|
| traqueo |
|
|
0.43 |
0.01, 0.85 |
|
| 0 |
88.0 / 96.0 (91.7%) |
29.0 / 29.0 (100.0%) |
|
|
|
| 1 |
8.0 / 96.0 (8.3%) |
0.0 / 29.0 (0.0%) |
|
|
|
| pic |
|
|
0.29 |
-0.12, 0.71 |
|
| 0 |
78.0 / 96.0 (81.3%) |
26.0 / 29.0 (89.7%) |
|
|
|
| 1 |
14.0 / 96.0 (14.6%) |
2.0 / 29.0 (6.9%) |
|
|
|
| 2 |
3.0 / 96.0 (3.1%) |
1.0 / 29.0 (3.4%) |
|
|
|
| 3 |
1.0 / 96.0 (1.0%) |
0.0 / 29.0 (0.0%) |
|
|
|
| ptio2 |
|
|
0.25 |
-0.16, 0.67 |
|
| 0 |
93.0 / 96.0 (96.9%) |
29.0 / 29.0 (100.0%) |
|
|
|
| 1 |
3.0 / 96.0 (3.1%) |
0.0 / 29.0 (0.0%) |
|
|
|
| craniectomia |
|
|
0.07 |
-0.34, 0.49 |
|
| 0 |
91.0 / 96.0 (94.8%) |
27.0 / 29.0 (93.1%) |
|
|
|
| 1 |
5.0 / 96.0 (5.2%) |
2.0 / 29.0 (6.9%) |
|
|
|
| vasoactivos |
|
|
0.14 |
-0.27, 0.56 |
|
| 0 |
66.0 / 96.0 (68.8%) |
18.0 / 29.0 (62.1%) |
|
|
|
| 1 |
30.0 / 96.0 (31.3%) |
11.0 / 29.0 (37.9%) |
|
|
|
| hemodinamica |
|
|
0.27 |
-0.14, 0.69 |
|
| 0 |
64.0 / 96.0 (66.7%) |
18.0 / 29.0 (62.1%) |
|
|
|
| 1 |
3.0 / 96.0 (3.1%) |
1.0 / 29.0 (3.4%) |
|
|
|
| 2 |
29.0 / 96.0 (30.2%) |
9.0 / 29.0 (31.0%) |
|
|
|
| 3 |
0.0 / 96.0 (0.0%) |
1.0 / 29.0 (3.4%) |
|
|
|
| coagu_trauma |
|
|
0.05 |
-0.36, 0.47 |
|
| 0 |
88.0 / 96.0 (91.7%) |
27.0 / 29.0 (93.1%) |
|
|
|
| 1 |
8.0 / 96.0 (8.3%) |
2.0 / 29.0 (6.9%) |
|
|
|
| rabdomiolisis |
|
|
0.09 |
-0.32, 0.51 |
|
| 0 |
87.0 / 96.0 (90.6%) |
27.0 / 29.0 (93.1%) |
|
|
|
| 1 |
9.0 / 96.0 (9.4%) |
2.0 / 29.0 (6.9%) |
|
|
|
| hic |
|
|
0.24 |
-0.18, 0.65 |
|
| 0 |
79.0 / 96.0 (82.3%) |
21.0 / 29.0 (72.4%) |
|
|
|
| 1 |
17.0 / 96.0 (17.7%) |
8.0 / 29.0 (27.6%) |
|
|
|
| medidas_hic |
|
|
-0.49 |
-0.91, -0.07 |
|
| 0 |
79.0 / 96.0 (82.3%) |
19.0 / 29.0 (65.5%) |
|
|
|
| 1 |
11.0 / 96.0 (11.5%) |
5.0 / 29.0 (17.2%) |
|
|
|
| 2 |
6.0 / 96.0 (6.3%) |
2.0 / 29.0 (6.9%) |
|
|
|
| 3 |
0.0 / 96.0 (0.0%) |
1.0 / 29.0 (3.4%) |
|
|
|
| 4 |
0.0 / 96.0 (0.0%) |
2.0 / 29.0 (6.9%) |
|
|
|
| disf_resp |
|
|
0.06 |
-0.36, 0.48 |
|
| 0 |
52.0 / 95.0 (54.7%) |
15.0 / 29.0 (51.7%) |
|
|
|
| 1 |
43.0 / 95.0 (45.3%) |
14.0 / 29.0 (48.3%) |
|
|
|
| Unknown |
1 |
0 |
|
|
|
| p_f |
|
|
-0.21 |
-0.63, 0.20 |
|
| 0 |
50.0 / 96.0 (52.1%) |
14.0 / 29.0 (48.3%) |
|
|
|
| 1 |
32.0 / 96.0 (33.3%) |
6.0 / 29.0 (20.7%) |
|
|
|
| 2 |
6.0 / 96.0 (6.3%) |
6.0 / 29.0 (20.7%) |
|
|
|
| 3 |
7.0 / 96.0 (7.3%) |
3.0 / 29.0 (10.3%) |
|
|
|
| 4 |
1.0 / 96.0 (1.0%) |
0.0 / 29.0 (0.0%) |
|
|
|
| hemo_masiva |
|
|
0.23 |
-0.18, 0.65 |
|
| 0 |
94.0 / 96.0 (97.9%) |
27.0 / 29.0 (93.1%) |
|
|
|
| 1 |
2.0 / 96.0 (2.1%) |
2.0 / 29.0 (6.9%) |
|
|
|
| sdmo |
|
|
0.11 |
-0.31, 0.52 |
|
| 0 |
89.0 / 96.0 (92.7%) |
26.0 / 29.0 (89.7%) |
|
|
|
| 1 |
7.0 / 96.0 (7.3%) |
3.0 / 29.0 (10.3%) |
|
|
|
| inf_nosocomial |
|
|
0.03 |
-0.38, 0.45 |
|
| 0 |
71.0 / 96.0 (74.0%) |
21.0 / 29.0 (72.4%) |
|
|
|
| 1 |
25.0 / 96.0 (26.0%) |
8.0 / 29.0 (27.6%) |
|
|
|
| leucos |
6,256.60 (10,994.19) 14.60 (11.45, 12,350.00) |
7,998.30 (9,273.33) 6,700.00 (12.30, 12,500.00) |
-1,742 |
-5,868, 2,385 |
0.4 |
| Unknown |
1 |
0 |
|
|
|
| nt |
4,786.00 (11,447.82) 86.60 (79.65, 7,550.00) |
6,342.91 (7,447.18) 3,800.00 (84.90, 10,600.00) |
-1,557 |
-5,206, 2,092 |
0.4 |
| Unknown |
5 |
0 |
|
|
|
| linfos |
570.69 (1,266.18) 14.50 (6.65, 76.00) |
865.99 (1,182.23) 30.30 (9.30, 1,300.00) |
-295 |
-856, 265 |
0.3 |
| Unknown |
21 |
4 |
|
|
|
| eos |
37.42 (104.61) 0.20 (0.00, 1.30) |
48.30 (99.17) 0.20 (0.00, 3.80) |
-11 |
-60, 38 |
0.7 |
| Unknown |
23 |
6 |
|
|
|
| hb |
13.05 (1.91) 13.20 (11.60, 14.40) |
453.12 (2,374.64) 12.90 (11.00, 13.60) |
-440 |
-1,343, 463 |
0.3 |
| Unknown |
1 |
0 |
|
|
|
| hto |
38.52 (5.58) 38.60 (34.30, 42.65) |
36.61 (6.59) 38.30 (33.15, 40.90) |
1.9 |
-0.92, 4.7 |
0.2 |
| Unknown |
9 |
2 |
|
|
|
| plq |
86,678.44 (110,728.28) 250.00 (169.00, 183,000.00) |
116,968.62 (119,483.75) 150,000.00 (154.00, 208,000.00) |
-30,290 |
-80,536, 19,956 |
0.2 |
| Unknown |
1 |
0 |
|
|
|
| inr |
1.16 (0.24) 1.08 (1.01, 1.24) |
1.51 (1.11) 1.13 (1.05, 1.33) |
-0.35 |
-0.78, 0.07 |
0.10 |
| Unknown |
5 |
0 |
|
|
|
| ap |
85.36 (18.12) 89.00 (74.25, 97.00) |
75.15 (29.02) 85.00 (70.50, 93.00) |
10 |
-1.8, 22 |
0.093 |
| Unknown |
6 |
2 |
|
|
|
| ttpa |
28.79 (8.51) 28.10 (26.00, 30.20) |
32.33 (8.10) 30.00 (28.00, 33.00) |
-3.5 |
-7.1, -0.01 |
0.049 |
| Unknown |
7 |
0 |
|
|
|
| fibrinogeno_2 |
384.08 (136.68) 368.50 (304.25, 440.75) |
442.89 (187.79) 423.00 (323.25, 490.00) |
-59 |
-137, 19 |
0.13 |
| Unknown |
10 |
1 |
|
|
|
| gluc |
144.00 (38.87) 139.00 (118.50, 154.00) |
186.68 (77.88) 177.50 (137.75, 213.50) |
-43 |
-74, -12 |
0.009 |
| Unknown |
5 |
1 |
|
|
|
| urea |
33.12 (13.69) 31.50 (24.80, 40.05) |
45.79 (15.80) 44.00 (33.00, 57.40) |
-13 |
-20, -5.3 |
0.001 |
| Unknown |
13 |
6 |
|
|
|
| crea |
0.86 (0.28) 0.80 (0.70, 0.95) |
1.04 (0.33) 0.98 (0.80, 1.19) |
-0.18 |
-0.32, -0.04 |
0.012 |
| Unknown |
2 |
1 |
|
|
|
| na |
136.90 (4.63) 137.00 (136.00, 139.00) |
136.62 (3.14) 137.00 (135.00, 138.00) |
0.28 |
-1.2, 1.8 |
0.7 |
| Unknown |
3 |
0 |
|
|
|
| k |
3.88 (0.53) 3.80 (3.50, 4.20) |
4.02 (0.38) 4.00 (3.80, 4.20) |
-0.14 |
-0.32, 0.04 |
0.12 |
| Unknown |
3 |
0 |
|
|
|
| cl |
106.28 (4.84) 106.00 (104.00, 108.75) |
111.00 (20.30) 107.00 (104.50, 108.00) |
-4.7 |
-15, 5.1 |
0.3 |
| Unknown |
22 |
10 |
|
|
|
| ca_ionico |
6.36 (15.60) 4.50 (4.36, 4.70) |
4.40 (0.39) 4.54 (4.31, 4.63) |
2.0 |
-1.5, 5.5 |
0.3 |
| Unknown |
17 |
6 |
|
|
|
| mg |
1.84 (0.28) 1.83 (1.68, 2.00) |
1.84 (0.27) 1.80 (1.71, 1.92) |
0.00 |
-0.17, 0.17 |
>0.9 |
| Unknown |
38 |
15 |
|
|
|
| p |
2.99 (0.78) 3.00 (2.50, 3.41) |
2.84 (0.87) 2.75 (2.35, 3.25) |
0.15 |
-0.39, 0.68 |
0.6 |
| Unknown |
39 |
15 |
|
|
|
| alb |
3.32 (0.75) 3.50 (3.00, 3.90) |
3.13 (0.24) 3.20 (3.08, 3.30) |
0.19 |
-0.10, 0.48 |
0.2 |
| Unknown |
55 |
21 |
|
|
|
| bilit |
0.81 (0.59) 0.65 (0.50, 0.90) |
0.69 (0.32) 0.65 (0.50, 0.80) |
0.12 |
-0.09, 0.34 |
0.2 |
| Unknown |
25 |
13 |
|
|
|
| ph |
7.30 (0.63) 7.38 (7.34, 7.41) |
7.13 (1.12) 7.37 (7.30, 7.41) |
0.17 |
-0.28, 0.63 |
0.4 |
| Unknown |
6 |
1 |
|
|
|
| pco2 |
38.98 (7.21) 39.00 (34.00, 43.00) |
43.43 (16.14) 38.00 (36.00, 45.75) |
-4.4 |
-11, 2.0 |
0.2 |
| Unknown |
8 |
1 |
|
|
|
| po2 |
102.31 (63.53) 85.00 (58.00, 129.50) |
90.26 (51.27) 81.00 (44.50, 131.00) |
12 |
-12, 36 |
0.3 |
| Unknown |
13 |
2 |
|
|
|
| hco3 |
22.52 (3.52) 23.00 (21.00, 24.60) |
22.49 (3.47) 22.60 (21.05, 24.90) |
0.03 |
-1.5, 1.6 |
>0.9 |
| Unknown |
6 |
2 |
|
|
|
| eb |
-2.34 (3.76) -1.95 (-3.98, -0.25) |
-3.32 (4.45) -2.45 (-6.75, -0.03) |
0.99 |
-0.97, 2.9 |
0.3 |
| Unknown |
14 |
3 |
|
|
|
| lactato |
2.23 (1.49) 1.90 (1.25, 2.80) |
3.06 (2.72) 1.80 (1.50, 3.90) |
-0.83 |
-1.9, 0.28 |
0.14 |
| Unknown |
9 |
2 |
|
|
|
| dest_uci |
|
|
0.57 |
0.15, 0.99 |
|
| 0 |
8.0 / 96.0 (8.3%) |
10.0 / 29.0 (34.5%) |
|
|
|
| 1 |
12.0 / 96.0 (12.5%) |
1.0 / 29.0 (3.4%) |
|
|
|
| 2 |
74.0 / 96.0 (77.1%) |
18.0 / 29.0 (62.1%) |
|
|
|
| 3 |
1.0 / 96.0 (1.0%) |
0.0 / 29.0 (0.0%) |
|
|
|
| 4 |
1.0 / 96.0 (1.0%) |
0.0 / 29.0 (0.0%) |
|
|
|
| dias_uci |
9.02 (11.53) 4.00 (2.00, 12.00) |
6.34 (5.94) 4.00 (2.00, 11.00) |
2.7 |
-0.54, 5.9 |
0.10 |
| Unknown |
1 |
0 |
|
|
|
| est_hosp |
15.38 (16.48) 8.50 (5.00, 19.00) |
65.90 (268.95) 11.00 (4.00, 22.00) |
-51 |
-153, 52 |
0.3 |
| Unknown |
2 |
0 |
|
|
|
| dest_hosp |
|
|
0.93 |
0.50, 1.4 |
|
| 0 |
9.0 / 95.0 (9.5%) |
15.0 / 29.0 (51.7%) |
|
|
|
| 1 |
0.0 / 95.0 (0.0%) |
1.0 / 29.0 (3.4%) |
|
|
|
| 2 |
8.0 / 95.0 (8.4%) |
0.0 / 29.0 (0.0%) |
|
|
|
| 3 |
70.0 / 95.0 (73.7%) |
10.0 / 29.0 (34.5%) |
|
|
|
| 4 |
8.0 / 95.0 (8.4%) |
3.0 / 29.0 (10.3%) |
|
|
|
| Unknown |
1 |
0 |
|
|
|
| ltsv |
|
|
0.90 |
0.47, 1.3 |
|
| 0 |
87.0 / 95.0 (91.6%) |
16.0 / 29.0 (55.2%) |
|
|
|
| 1 |
8.0 / 95.0 (8.4%) |
13.0 / 29.0 (44.8%) |
|
|
|
| Unknown |
1 |
0 |
|
|
|
| m_rankin_alta_hospitalaria |
|
|
-0.99 |
-1.4, -0.55 |
|
| 1 |
44.0 / 92.0 (47.8%) |
6.0 / 29.0 (20.7%) |
|
|
|
| 2 |
21.0 / 92.0 (22.8%) |
2.0 / 29.0 (6.9%) |
|
|
|
| 3 |
8.0 / 92.0 (8.7%) |
5.0 / 29.0 (17.2%) |
|
|
|
| 4 |
8.0 / 92.0 (8.7%) |
1.0 / 29.0 (3.4%) |
|
|
|
| 5 |
2.0 / 92.0 (2.2%) |
1.0 / 29.0 (3.4%) |
|
|
|
| 6 |
9.0 / 92.0 (9.8%) |
14.0 / 29.0 (48.3%) |
|
|
|
| Unknown |
4 |
0 |
|
|
|
| exitus |
9.0 / 92.0 (9.8%) |
14.0 / 29.0 (48.3%) |
-38% |
-60%, -17% |
<0.001 |
| Unknown |
4 |
0 |
|
|
|
| dependiente |
19.0 / 92.0 (20.7%) |
16.0 / 29.0 (55.2%) |
-35% |
-57%, -12% |
<0.001 |
| Unknown |
4 |
0 |
|
|
|
#crea una tabla cruzada del mecanismo lesional en función de opicu
#y añade pruebas de significación
tce2 %>%
tbl_cross(
row = mecanismo,
col = opicu,
percent = "col"
) %>%
bold_labels() %>%
add_p()
|
opicu
|
Total |
p-value |
| 0 |
1 |
| mecanismo |
|
|
|
0.017 |
| 1 |
15 (16%) |
17 (59%) |
32 (26%) |
|
| 2 |
6 (6.3%) |
0 (0%) |
6 (4.8%) |
|
| 4 |
21 (22%) |
5 (17%) |
26 (21%) |
|
| 5 |
5 (5.2%) |
0 (0%) |
5 (4.0%) |
|
| 8 |
24 (25%) |
4 (14%) |
28 (22%) |
|
| 9 |
7 (7.3%) |
2 (6.9%) |
9 (7.2%) |
|
| 10 |
2 (2.1%) |
0 (0%) |
2 (1.6%) |
|
| 11 |
1 (1.0%) |
0 (0%) |
1 (0.8%) |
|
| 12 |
5 (5.2%) |
0 (0%) |
5 (4.0%) |
|
| 13 |
1 (1.0%) |
0 (0%) |
1 (0.8%) |
|
| 14 |
1 (1.0%) |
0 (0%) |
1 (0.8%) |
|
| 15 |
8 (8.3%) |
1 (3.4%) |
9 (7.2%) |
|
| Total |
96 (100%) |
29 (100%) |
125 (100%) |
|
#crea una tabla con tbl1, en función de dependencia
tce_puro %>%
tbl_summary(
by = dependiente,
statistic = list(
all_continuous() ~ "{mean} ({sd}) {median} ({p25}, {p75})",
all_categorical() ~ "{n} / {N} ({p}%)"
),
digits = list(
all_continuous() ~ 2,
all_categorical() ~ 1
)
) %>%
bold_labels() %>%
add_difference()
## 4 observations missing `dependiente` have been removed. To include these observations, use `forcats::fct_na_value_to_level()` on `dependiente` column before passing to `tbl_summary()`.
## Warning for variable 'marshall5vs6':
## simpleWarning in stats::prop.test(df_counts$n, df_counts$N, conf.level = 0.95): Chi-squared approximation may be incorrect
| Characteristic |
0, N = 86 |
1, N = 35 |
Difference |
95% CI |
p-value |
| tce_unico |
|
|
0.11 |
-0.28, 0.51 |
|
| 0 |
61.0 / 86.0 (70.9%) |
23.0 / 35.0 (65.7%) |
|
|
|
| 1 |
25.0 / 86.0 (29.1%) |
12.0 / 35.0 (34.3%) |
|
|
|
| edad |
51.01 (20.64) 49.00 (32.50, 68.00) |
65.77 (19.14) 73.00 (53.00, 80.50) |
-15 |
-23, -6.9 |
<0.001 |
| sexo |
|
|
0.06 |
-0.34, 0.45 |
|
| 0 |
66.0 / 86.0 (76.7%) |
26.0 / 35.0 (74.3%) |
|
|
|
| 1 |
20.0 / 86.0 (23.3%) |
9.0 / 35.0 (25.7%) |
|
|
|
| procedencia |
|
|
0.44 |
0.04, 0.83 |
|
| 1 |
65.0 / 86.0 (75.6%) |
32.0 / 35.0 (91.4%) |
|
|
|
| 3 |
21.0 / 86.0 (24.4%) |
3.0 / 35.0 (8.6%) |
|
|
|
| antitromboticos |
|
|
-0.41 |
-0.81, -0.02 |
|
| 0 |
73.0 / 86.0 (84.9%) |
25.0 / 35.0 (71.4%) |
|
|
|
| 1 |
4.0 / 86.0 (4.7%) |
3.0 / 35.0 (8.6%) |
|
|
|
| 2 |
8.0 / 86.0 (9.3%) |
2.0 / 35.0 (5.7%) |
|
|
|
| 3 |
1.0 / 86.0 (1.2%) |
4.0 / 35.0 (11.4%) |
|
|
|
| 5 |
0.0 / 86.0 (0.0%) |
1.0 / 35.0 (2.9%) |
|
|
|
| marshall |
|
|
-1.0 |
-1.5, -0.63 |
|
| 0 |
1.0 / 86.0 (1.2%) |
0.0 / 35.0 (0.0%) |
|
|
|
| 1 |
27.0 / 86.0 (31.4%) |
4.0 / 35.0 (11.4%) |
|
|
|
| 2 |
47.0 / 86.0 (54.7%) |
11.0 / 35.0 (31.4%) |
|
|
|
| 3 |
1.0 / 86.0 (1.2%) |
4.0 / 35.0 (11.4%) |
|
|
|
| 4 |
3.0 / 86.0 (3.5%) |
1.0 / 35.0 (2.9%) |
|
|
|
| 5 |
6.0 / 86.0 (7.0%) |
5.0 / 35.0 (14.3%) |
|
|
|
| 6 |
1.0 / 86.0 (1.2%) |
10.0 / 35.0 (28.6%) |
|
|
|
| marshall5vs6 |
1.0 / 7.0 (14.3%) |
10.0 / 15.0 (66.7%) |
-52% |
-98%, -6.7% |
0.067 |
| Unknown |
79 |
20 |
|
|
|
| tipo_trauma |
|
|
0.15 |
-0.25, 0.54 |
|
| 0 |
81.0 / 86.0 (94.2%) |
34.0 / 35.0 (97.1%) |
|
|
|
| 1 |
5.0 / 86.0 (5.8%) |
1.0 / 35.0 (2.9%) |
|
|
|
| at_prehosp |
|
|
0.31 |
-0.09, 0.70 |
|
| 0 |
0.0 / 86.0 (0.0%) |
1.0 / 35.0 (2.9%) |
|
|
|
| 1 |
5.0 / 86.0 (5.8%) |
3.0 / 35.0 (8.6%) |
|
|
|
| 2 |
7.0 / 86.0 (8.1%) |
1.0 / 35.0 (2.9%) |
|
|
|
| 3 |
63.0 / 86.0 (73.3%) |
30.0 / 35.0 (85.7%) |
|
|
|
| 4 |
11.0 / 86.0 (12.8%) |
0.0 / 35.0 (0.0%) |
|
|
|
| iot_pre |
|
|
0.45 |
0.06, 0.85 |
|
| 0 |
69.0 / 86.0 (80.2%) |
21.0 / 35.0 (60.0%) |
|
|
|
| 1 |
17.0 / 86.0 (19.8%) |
14.0 / 35.0 (40.0%) |
|
|
|
| psicot |
|
|
0.27 |
-0.12, 0.67 |
|
| 0 |
71.0 / 86.0 (82.6%) |
25.0 / 35.0 (71.4%) |
|
|
|
| 1 |
8.0 / 86.0 (9.3%) |
6.0 / 35.0 (17.1%) |
|
|
|
| 2 |
7.0 / 86.0 (8.1%) |
4.0 / 35.0 (11.4%) |
|
|
|
| drogas |
|
|
0.48 |
0.09, 0.88 |
|
| 0 |
77.0 / 86.0 (89.5%) |
35.0 / 35.0 (100.0%) |
|
|
|
| 1 |
9.0 / 86.0 (10.5%) |
0.0 / 35.0 (0.0%) |
|
|
|
| alcohol |
|
|
0.31 |
-0.09, 0.70 |
|
| 0 |
77.0 / 86.0 (89.5%) |
34.0 / 35.0 (97.1%) |
|
|
|
| 1 |
9.0 / 86.0 (10.5%) |
1.0 / 35.0 (2.9%) |
|
|
|
| pupila_ing |
|
|
1.0 |
0.62, 1.5 |
|
| 0 |
82.0 / 86.0 (95.3%) |
20.0 / 35.0 (57.1%) |
|
|
|
| 1 |
4.0 / 86.0 (4.7%) |
6.0 / 35.0 (17.1%) |
|
|
|
| 2 |
0.0 / 86.0 (0.0%) |
9.0 / 35.0 (25.7%) |
|
|
|
| atx |
|
|
0.25 |
-0.14, 0.65 |
|
| 0 |
82.0 / 86.0 (95.3%) |
31.0 / 35.0 (88.6%) |
|
|
|
| 1 |
4.0 / 86.0 (4.7%) |
4.0 / 35.0 (11.4%) |
|
|
|
| calcio |
|
|
0.35 |
-0.05, 0.74 |
|
| 0 |
85.0 / 86.0 (98.8%) |
32.0 / 35.0 (91.4%) |
|
|
|
| 1 |
1.0 / 86.0 (1.2%) |
3.0 / 35.0 (8.6%) |
|
|
|
| fc |
83.09 (18.68) 83.50 (70.75, 93.00) |
87.38 (32.23) 86.00 (76.00, 100.00) |
-4.3 |
-17, 8.0 |
0.5 |
| Unknown |
6 |
3 |
|
|
|
| fr |
17.80 (5.52) 16.00 (15.00, 19.00) |
17.74 (6.36) 18.00 (15.00, 20.00) |
0.06 |
-2.8, 2.9 |
>0.9 |
| Unknown |
22 |
8 |
|
|
|
| tas |
133.35 (28.24) 129.00 (116.00, 149.00) |
141.18 (46.91) 133.00 (118.25, 166.50) |
-7.8 |
-25, 9.6 |
0.4 |
| Unknown |
6 |
1 |
|
|
|
| gcs_ing |
12.69 (3.43) 15.00 (11.25, 15.00) |
7.57 (4.54) 7.00 (3.00, 12.50) |
5.1 |
3.4, 6.8 |
<0.001 |
| retrascore |
3.59 (2.66) 3.50 (1.00, 5.00) |
10.46 (4.66) 10.00 (7.50, 14.00) |
-6.9 |
-8.6, -5.2 |
<0.001 |
| supervivencia |
94.42 (8.10) 98.80 (91.90, 98.80) |
71.55 (28.39) 80.70 (60.50, 94.35) |
23 |
11, 34 |
<0.001 |
| Unknown |
22 |
8 |
|
|
|
| iss |
17.63 (9.66) 17.00 (10.00, 25.00) |
29.23 (11.04) 25.00 (25.00, 34.00) |
-12 |
-16, -7.3 |
<0.001 |
| apache_ii |
13.66 (6.69) 13.00 (9.00, 17.00) |
23.88 (7.94) 24.00 (20.00, 30.00) |
-10 |
-13, -7.1 |
<0.001 |
| Unknown |
1 |
2 |
|
|
|
| sofa_ingreso |
1.79 (2.18) 1.00 (0.00, 3.00) |
5.91 (4.10) 5.00 (3.00, 8.75) |
-4.1 |
-5.6, -2.6 |
<0.001 |
| Unknown |
0 |
1 |
|
|
|
| neurcx_urg |
|
|
0.15 |
-0.24, 0.55 |
|
| 0 |
78.0 / 86.0 (90.7%) |
30.0 / 35.0 (85.7%) |
|
|
|
| 1 |
8.0 / 86.0 (9.3%) |
5.0 / 35.0 (14.3%) |
|
|
|
| cx_urg |
|
|
0.39 |
-0.01, 0.78 |
|
| 0 |
83.0 / 86.0 (96.5%) |
30.0 / 35.0 (85.7%) |
|
|
|
| 1 |
3.0 / 86.0 (3.5%) |
5.0 / 35.0 (14.3%) |
|
|
|
| cx_no_urg |
|
|
0.23 |
-0.16, 0.62 |
|
| 0 |
74.0 / 86.0 (86.0%) |
30.0 / 35.0 (85.7%) |
|
|
|
| 1 |
10.0 / 86.0 (11.6%) |
5.0 / 35.0 (14.3%) |
|
|
|
| 2 |
1.0 / 86.0 (1.2%) |
0.0 / 35.0 (0.0%) |
|
|
|
| 3 |
1.0 / 86.0 (1.2%) |
0.0 / 35.0 (0.0%) |
|
|
|
| ch_24h |
|
|
-0.42 |
-0.82, -0.02 |
|
| 0 |
76.0 / 86.0 (88.4%) |
24.0 / 35.0 (68.6%) |
|
|
|
| 1 |
1.0 / 86.0 (1.2%) |
3.0 / 35.0 (8.6%) |
|
|
|
| 2 |
6.0 / 86.0 (7.0%) |
3.0 / 35.0 (8.6%) |
|
|
|
| 3 |
2.0 / 86.0 (2.3%) |
0.0 / 35.0 (0.0%) |
|
|
|
| 4 |
0.0 / 86.0 (0.0%) |
2.0 / 35.0 (5.7%) |
|
|
|
| 5 |
0.0 / 86.0 (0.0%) |
1.0 / 35.0 (2.9%) |
|
|
|
| 6 |
0.0 / 86.0 (0.0%) |
1.0 / 35.0 (2.9%) |
|
|
|
| 8 |
0.0 / 86.0 (0.0%) |
1.0 / 35.0 (2.9%) |
|
|
|
| 10 |
1.0 / 86.0 (1.2%) |
0.0 / 35.0 (0.0%) |
|
|
|
| pfc |
|
|
-0.67 |
-1.1, -0.27 |
|
| 0 |
85.0 / 86.0 (98.8%) |
25.0 / 35.0 (71.4%) |
|
|
|
| 1 |
0.0 / 86.0 (0.0%) |
2.0 / 35.0 (5.7%) |
|
|
|
| 2 |
0.0 / 86.0 (0.0%) |
6.0 / 35.0 (17.1%) |
|
|
|
| 3 |
1.0 / 86.0 (1.2%) |
0.0 / 35.0 (0.0%) |
|
|
|
| 4 |
0.0 / 86.0 (0.0%) |
1.0 / 35.0 (2.9%) |
|
|
|
| 6 |
0.0 / 86.0 (0.0%) |
1.0 / 35.0 (2.9%) |
|
|
|
| fibrinogeno |
|
|
0.15 |
-0.24, 0.55 |
|
| 0 |
85.0 / 86.0 (98.8%) |
35.0 / 35.0 (100.0%) |
|
|
|
| 1 |
1.0 / 86.0 (1.2%) |
0.0 / 35.0 (0.0%) |
|
|
|
| plaquetas |
|
|
0.47 |
0.07, 0.87 |
|
| 0 |
83.0 / 86.0 (96.5%) |
29.0 / 35.0 (82.9%) |
|
|
|
| 1 |
3.0 / 86.0 (3.5%) |
5.0 / 35.0 (14.3%) |
|
|
|
| 2 |
0.0 / 86.0 (0.0%) |
1.0 / 35.0 (2.9%) |
|
|
|
| arterio |
|
|
0.12 |
-0.27, 0.51 |
|
| 0 |
85.0 / 86.0 (98.8%) |
34.0 / 35.0 (97.1%) |
|
|
|
| 1 |
1.0 / 86.0 (1.2%) |
1.0 / 35.0 (2.9%) |
|
|
|
| vm |
|
|
1.4 |
0.94, 1.8 |
|
| 0 |
54.0 / 86.0 (62.8%) |
3.0 / 35.0 (8.6%) |
|
|
|
| 1 |
32.0 / 86.0 (37.2%) |
32.0 / 35.0 (91.4%) |
|
|
|
| drenaje_toracico |
|
|
0.16 |
-0.23, 0.56 |
|
| 0 |
74.0 / 86.0 (86.0%) |
28.0 / 35.0 (80.0%) |
|
|
|
| 1 |
12.0 / 86.0 (14.0%) |
7.0 / 35.0 (20.0%) |
|
|
|
| traqueo |
|
|
0.16 |
-0.24, 0.55 |
|
| 0 |
82.0 / 86.0 (95.3%) |
32.0 / 35.0 (91.4%) |
|
|
|
| 1 |
4.0 / 86.0 (4.7%) |
3.0 / 35.0 (8.6%) |
|
|
|
| pic |
|
|
0.70 |
0.30, 1.1 |
|
| 0 |
77.0 / 86.0 (89.5%) |
23.0 / 35.0 (65.7%) |
|
|
|
| 1 |
8.0 / 86.0 (9.3%) |
8.0 / 35.0 (22.9%) |
|
|
|
| 2 |
0.0 / 86.0 (0.0%) |
4.0 / 35.0 (11.4%) |
|
|
|
| 3 |
1.0 / 86.0 (1.2%) |
0.0 / 35.0 (0.0%) |
|
|
|
| ptio2 |
|
|
0.25 |
-0.14, 0.65 |
|
| 0 |
85.0 / 86.0 (98.8%) |
33.0 / 35.0 (94.3%) |
|
|
|
| 1 |
1.0 / 86.0 (1.2%) |
2.0 / 35.0 (5.7%) |
|
|
|
| craniectomia |
|
|
0.16 |
-0.24, 0.55 |
|
| 0 |
82.0 / 86.0 (95.3%) |
32.0 / 35.0 (91.4%) |
|
|
|
| 1 |
4.0 / 86.0 (4.7%) |
3.0 / 35.0 (8.6%) |
|
|
|
| vasoactivos |
|
|
0.87 |
0.46, 1.3 |
|
| 0 |
68.0 / 86.0 (79.1%) |
14.0 / 35.0 (40.0%) |
|
|
|
| 1 |
18.0 / 86.0 (20.9%) |
21.0 / 35.0 (60.0%) |
|
|
|
| hemodinamica |
|
|
0.98 |
0.57, 1.4 |
|
| 0 |
66.0 / 86.0 (76.7%) |
14.0 / 35.0 (40.0%) |
|
|
|
| 1 |
4.0 / 86.0 (4.7%) |
0.0 / 35.0 (0.0%) |
|
|
|
| 2 |
16.0 / 86.0 (18.6%) |
20.0 / 35.0 (57.1%) |
|
|
|
| 3 |
0.0 / 86.0 (0.0%) |
1.0 / 35.0 (2.9%) |
|
|
|
| coagu_trauma |
|
|
0.71 |
0.30, 1.1 |
|
| 0 |
86.0 / 86.0 (100.0%) |
28.0 / 35.0 (80.0%) |
|
|
|
| 1 |
0.0 / 86.0 (0.0%) |
7.0 / 35.0 (20.0%) |
|
|
|
| rabdomiolisis |
|
|
0.25 |
-0.14, 0.65 |
|
| 0 |
82.0 / 86.0 (95.3%) |
31.0 / 35.0 (88.6%) |
|
|
|
| 1 |
4.0 / 86.0 (4.7%) |
4.0 / 35.0 (11.4%) |
|
|
|
| hic |
|
|
1.1 |
0.66, 1.5 |
|
| 0 |
79.0 / 86.0 (91.9%) |
17.0 / 35.0 (48.6%) |
|
|
|
| 1 |
7.0 / 86.0 (8.1%) |
18.0 / 35.0 (51.4%) |
|
|
|
| medidas_hic |
|
|
-0.95 |
-1.4, -0.54 |
|
| 0 |
79.0 / 86.0 (91.9%) |
15.0 / 35.0 (42.9%) |
|
|
|
| 1 |
3.0 / 86.0 (3.5%) |
13.0 / 35.0 (37.1%) |
|
|
|
| 2 |
4.0 / 86.0 (4.7%) |
4.0 / 35.0 (11.4%) |
|
|
|
| 3 |
0.0 / 86.0 (0.0%) |
1.0 / 35.0 (2.9%) |
|
|
|
| 4 |
0.0 / 86.0 (0.0%) |
2.0 / 35.0 (5.7%) |
|
|
|
| disf_resp |
|
|
0.78 |
0.37, 1.2 |
|
| 0 |
55.0 / 85.0 (64.7%) |
10.0 / 35.0 (28.6%) |
|
|
|
| 1 |
30.0 / 85.0 (35.3%) |
25.0 / 35.0 (71.4%) |
|
|
|
| Unknown |
1 |
0 |
|
|
|
| p_f |
|
|
-0.83 |
-1.2, -0.42 |
|
| 0 |
53.0 / 86.0 (61.6%) |
9.0 / 35.0 (25.7%) |
|
|
|
| 1 |
25.0 / 86.0 (29.1%) |
12.0 / 35.0 (34.3%) |
|
|
|
| 2 |
4.0 / 86.0 (4.7%) |
8.0 / 35.0 (22.9%) |
|
|
|
| 3 |
3.0 / 86.0 (3.5%) |
6.0 / 35.0 (17.1%) |
|
|
|
| 4 |
1.0 / 86.0 (1.2%) |
0.0 / 35.0 (0.0%) |
|
|
|
| hemo_masiva |
|
|
0.51 |
0.11, 0.91 |
|
| 0 |
86.0 / 86.0 (100.0%) |
31.0 / 35.0 (88.6%) |
|
|
|
| 1 |
0.0 / 86.0 (0.0%) |
4.0 / 35.0 (11.4%) |
|
|
|
| sdmo |
|
|
0.77 |
0.37, 1.2 |
|
| 0 |
85.0 / 86.0 (98.8%) |
26.0 / 35.0 (74.3%) |
|
|
|
| 1 |
1.0 / 86.0 (1.2%) |
9.0 / 35.0 (25.7%) |
|
|
|
| inf_nosocomial |
|
|
0.64 |
0.24, 1.0 |
|
| 0 |
71.0 / 86.0 (82.6%) |
19.0 / 35.0 (54.3%) |
|
|
|
| 1 |
15.0 / 86.0 (17.4%) |
16.0 / 35.0 (45.7%) |
|
|
|
| leucos |
6,767.59 (11,493.59) 15.60 (11.50, 12,200.00) |
6,947.01 (8,749.22) 15.30 (11.55, 13,950.00) |
-179 |
-4,027, 3,668 |
>0.9 |
| Unknown |
1 |
0 |
|
|
|
| nt |
5,451.49 (11,944.22) 87.90 (80.10, 8,325.00) |
4,845.02 (6,887.11) 88.55 (83.35, 9,475.00) |
606 |
-2,934, 4,147 |
0.7 |
| Unknown |
2 |
3 |
|
|
|
| linfos |
727.29 (1,346.20) 16.90 (7.50, 1,000.00) |
489.03 (1,040.82) 11.80 (6.15, 365.15) |
238 |
-277, 753 |
0.4 |
| Unknown |
17 |
8 |
|
|
|
| eos |
45.95 (110.99) 0.30 (0.00, 2.65) |
31.07 (88.30) 0.10 (0.00, 0.40) |
15 |
-29, 59 |
0.5 |
| Unknown |
20 |
9 |
|
|
|
| hb |
163.51 (1,386.94) 13.40 (11.90, 14.40) |
12.08 (2.26) 12.30 (10.65, 13.40) |
151 |
-148, 451 |
0.3 |
| Unknown |
1 |
0 |
|
|
|
| hto |
38.94 (5.15) 40.05 (35.18, 42.73) |
35.75 (7.06) 35.90 (31.40, 40.25) |
3.2 |
0.38, 6.0 |
0.027 |
| Unknown |
6 |
4 |
|
|
|
| plq |
101,889.15 (118,016.89) 271.00 (169.00, 214,000.00) |
81,124.37 (103,494.80) 250.00 (153.50, 160,500.00) |
20,765 |
-22,449, 63,979 |
0.3 |
| Unknown |
1 |
0 |
|
|
|
| inr |
1.19 (0.60) 1.08 (1.00, 1.17) |
1.38 (0.60) 1.19 (1.05, 1.39) |
-0.19 |
-0.44, 0.05 |
0.12 |
| Unknown |
4 |
1 |
|
|
|
| ap |
86.90 (17.87) 90.00 (80.00, 97.50) |
74.73 (26.97) 77.00 (65.00, 93.00) |
12 |
1.9, 22 |
0.021 |
| Unknown |
6 |
2 |
|
|
|
| ttpa |
29.28 (9.22) 28.50 (26.00, 30.70) |
30.82 (7.08) 29.00 (27.00, 32.80) |
-1.5 |
-4.7, 1.7 |
0.3 |
| Unknown |
5 |
2 |
|
|
|
| fibrinogeno_2 |
410.81 (157.67) 378.00 (305.25, 451.25) |
376.84 (137.38) 391.00 (254.00, 470.50) |
34 |
-26, 94 |
0.3 |
| Unknown |
8 |
3 |
|
|
|
| gluc |
141.10 (40.88) 136.50 (113.25, 152.00) |
186.52 (68.63) 177.00 (144.00, 212.00) |
-45 |
-71, -20 |
<0.001 |
| Unknown |
4 |
2 |
|
|
|
| urea |
34.53 (15.84) 33.00 (24.85, 41.33) |
38.87 (13.19) 39.20 (27.80, 48.60) |
-4.3 |
-10, 1.8 |
0.2 |
| Unknown |
12 |
6 |
|
|
|
| crea |
0.87 (0.27) 0.83 (0.73, 0.98) |
0.99 (0.36) 0.89 (0.73, 1.35) |
-0.12 |
-0.26, 0.02 |
0.10 |
| Unknown |
1 |
2 |
|
|
|
| na |
136.89 (4.48) 137.00 (136.00, 138.00) |
136.50 (4.14) 137.00 (135.00, 139.00) |
0.39 |
-1.3, 2.1 |
0.7 |
| Unknown |
2 |
1 |
|
|
|
| k |
3.88 (0.54) 3.80 (3.50, 4.20) |
4.01 (0.37) 4.00 (3.83, 4.20) |
-0.14 |
-0.31, 0.04 |
0.12 |
| Unknown |
2 |
1 |
|
|
|
| cl |
107.37 (11.76) 105.00 (104.00, 108.00) |
106.92 (4.99) 107.00 (106.00, 109.00) |
0.45 |
-3.1, 4.0 |
0.8 |
| Unknown |
21 |
10 |
|
|
|
| ca_ionico |
6.62 (16.69) 4.52 (4.40, 4.70) |
4.46 (0.29) 4.40 (4.30, 4.60) |
2.2 |
-1.9, 6.2 |
0.3 |
| Unknown |
17 |
6 |
|
|
|
| mg |
1.91 (0.30) 1.90 (1.71, 2.04) |
1.73 (0.20) 1.77 (1.58, 1.90) |
0.18 |
0.06, 0.30 |
0.005 |
| Unknown |
41 |
11 |
|
|
|
| p |
2.91 (0.74) 2.90 (2.50, 3.30) |
3.06 (0.87) 3.10 (2.61, 3.60) |
-0.15 |
-0.57, 0.28 |
0.5 |
| Unknown |
42 |
11 |
|
|
|
| alb |
3.35 (0.63) 3.50 (3.18, 3.70) |
3.14 (0.77) 3.25 (2.63, 3.65) |
0.21 |
-0.23, 0.66 |
0.3 |
| Unknown |
58 |
17 |
|
|
|
| bilit |
0.74 (0.48) 0.65 (0.48, 0.81) |
0.93 (0.73) 0.67 (0.50, 0.95) |
-0.19 |
-0.52, 0.14 |
0.2 |
| Unknown |
26 |
11 |
|
|
|
| ph |
7.21 (0.94) 7.37 (7.33, 7.41) |
7.36 (0.11) 7.37 (7.33, 7.42) |
-0.15 |
-0.36, 0.07 |
0.2 |
| Unknown |
7 |
0 |
|
|
|
| pco2 |
41.16 (9.93) 39.30 (36.00, 44.00) |
38.09 (10.79) 36.00 (32.00, 40.00) |
3.1 |
-1.3, 7.4 |
0.2 |
| Unknown |
8 |
1 |
|
|
|
| po2 |
94.17 (64.75) 74.00 (49.00, 121.00) |
106.64 (49.40) 104.00 (69.00, 135.00) |
-12 |
-35, 10 |
0.3 |
| Unknown |
13 |
2 |
|
|
|
| hco3 |
23.19 (3.14) 23.50 (21.90, 25.15) |
21.41 (3.56) 21.50 (19.55, 23.40) |
1.8 |
0.38, 3.2 |
0.013 |
| Unknown |
8 |
0 |
|
|
|
| eb |
-2.10 (3.56) -1.65 (-3.73, 0.10) |
-3.23 (4.33) -2.15 (-5.15, -0.73) |
1.1 |
-0.67, 2.9 |
0.2 |
| Unknown |
12 |
5 |
|
|
|
| lactato |
2.00 (1.06) 1.70 (1.20, 2.50) |
3.17 (2.53) 2.50 (1.50, 3.50) |
-1.2 |
-2.1, -0.25 |
0.014 |
| Unknown |
9 |
2 |
|
|
|
| dest_uci |
|
|
1.0 |
0.63, 1.5 |
|
| 0 |
0.0 / 86.0 (0.0%) |
18.0 / 35.0 (51.4%) |
|
|
|
| 1 |
11.0 / 86.0 (12.8%) |
0.0 / 35.0 (0.0%) |
|
|
|
| 2 |
74.0 / 86.0 (86.0%) |
16.0 / 35.0 (45.7%) |
|
|
|
| 3 |
1.0 / 86.0 (1.2%) |
0.0 / 35.0 (0.0%) |
|
|
|
| 4 |
0.0 / 86.0 (0.0%) |
1.0 / 35.0 (2.9%) |
|
|
|
| dias_uci |
6.90 (8.30) 4.00 (2.00, 7.75) |
12.20 (14.41) 8.00 (3.00, 16.50) |
-5.3 |
-11, -0.07 |
0.047 |
| est_hosp |
14.02 (13.26) 9.00 (6.00, 19.00) |
61.43 (244.66) 12.00 (4.00, 27.00) |
-47 |
-131, 37 |
0.3 |
| Unknown |
1 |
0 |
|
|
|
| dest_hosp |
|
|
1.3 |
0.88, 1.7 |
|
| 0 |
1.0 / 86.0 (1.2%) |
23.0 / 35.0 (65.7%) |
|
|
|
| 1 |
1.0 / 86.0 (1.2%) |
0.0 / 35.0 (0.0%) |
|
|
|
| 2 |
7.0 / 86.0 (8.1%) |
0.0 / 35.0 (0.0%) |
|
|
|
| 3 |
74.0 / 86.0 (86.0%) |
5.0 / 35.0 (14.3%) |
|
|
|
| 4 |
3.0 / 86.0 (3.5%) |
7.0 / 35.0 (20.0%) |
|
|
|
| ltsv |
|
|
1.7 |
1.3, 2.2 |
|
| 0 |
86.0 / 86.0 (100.0%) |
14.0 / 35.0 (40.0%) |
|
|
|
| 1 |
0.0 / 86.0 (0.0%) |
21.0 / 35.0 (60.0%) |
|
|
|
| m_rankin_alta_hospitalaria |
|
|
-4.7 |
-5.5, -4.0 |
|
| 1 |
50.0 / 86.0 (58.1%) |
0.0 / 35.0 (0.0%) |
|
|
|
| 2 |
23.0 / 86.0 (26.7%) |
0.0 / 35.0 (0.0%) |
|
|
|
| 3 |
13.0 / 86.0 (15.1%) |
0.0 / 35.0 (0.0%) |
|
|
|
| 4 |
0.0 / 86.0 (0.0%) |
9.0 / 35.0 (25.7%) |
|
|
|
| 5 |
0.0 / 86.0 (0.0%) |
3.0 / 35.0 (8.6%) |
|
|
|
| 6 |
0.0 / 86.0 (0.0%) |
23.0 / 35.0 (65.7%) |
|
|
|
| exitus |
0.0 / 86.0 (0.0%) |
23.0 / 35.0 (65.7%) |
-66% |
-83%, -48% |
<0.001 |
| opicu |
13.0 / 86.0 (15.1%) |
16.0 / 35.0 (45.7%) |
-31% |
-51%, -10% |
<0.001 |
#crea una tabla analizando los datos, en función de la mortalidad
tce_puro %>%
tbl_summary(
by = exitus,
statistic = list(
all_continuous() ~ "{mean} ({sd}) {median} ({p25}, {p75})",
all_categorical() ~ "{n} / {N} ({p}%)"
),
digits = list(
all_continuous() ~ 2,
all_categorical() ~ 1
)
) %>%
bold_labels() %>%
add_difference()
## 4 observations missing `exitus` have been removed. To include these observations, use `forcats::fct_na_value_to_level()` on `exitus` column before passing to `tbl_summary()`.
## Warning for variable 'marshall5vs6':
## simpleWarning in stats::prop.test(df_counts$n, df_counts$N, conf.level = 0.95): Chi-squared approximation may be incorrect
| Characteristic |
0, N = 98 |
1, N = 23 |
Difference |
95% CI |
p-value |
| tce_unico |
|
|
0.11 |
-0.34, 0.57 |
|
| 0 |
69.0 / 98.0 (70.4%) |
15.0 / 23.0 (65.2%) |
|
|
|
| 1 |
29.0 / 98.0 (29.6%) |
8.0 / 23.0 (34.8%) |
|
|
|
| edad |
51.45 (20.60) 53.00 (34.75, 68.00) |
71.61 (15.60) 77.00 (69.00, 81.00) |
-20 |
-28, -12 |
<0.001 |
| sexo |
|
|
0.07 |
-0.39, 0.52 |
|
| 0 |
74.0 / 98.0 (75.5%) |
18.0 / 23.0 (78.3%) |
|
|
|
| 1 |
24.0 / 98.0 (24.5%) |
5.0 / 23.0 (21.7%) |
|
|
|
| procedencia |
|
|
0.22 |
-0.23, 0.68 |
|
| 1 |
77.0 / 98.0 (78.6%) |
20.0 / 23.0 (87.0%) |
|
|
|
| 3 |
21.0 / 98.0 (21.4%) |
3.0 / 23.0 (13.0%) |
|
|
|
| antitromboticos |
|
|
-0.45 |
-0.91, 0.00 |
|
| 0 |
83.0 / 98.0 (84.7%) |
15.0 / 23.0 (65.2%) |
|
|
|
| 1 |
4.0 / 98.0 (4.1%) |
3.0 / 23.0 (13.0%) |
|
|
|
| 2 |
8.0 / 98.0 (8.2%) |
2.0 / 23.0 (8.7%) |
|
|
|
| 3 |
3.0 / 98.0 (3.1%) |
2.0 / 23.0 (8.7%) |
|
|
|
| 5 |
0.0 / 98.0 (0.0%) |
1.0 / 23.0 (4.3%) |
|
|
|
| marshall |
|
|
-1.5 |
-2.0, -1.0 |
|
| 0 |
1.0 / 98.0 (1.0%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 1 |
30.0 / 98.0 (30.6%) |
1.0 / 23.0 (4.3%) |
|
|
|
| 2 |
54.0 / 98.0 (55.1%) |
4.0 / 23.0 (17.4%) |
|
|
|
| 3 |
1.0 / 98.0 (1.0%) |
4.0 / 23.0 (17.4%) |
|
|
|
| 4 |
3.0 / 98.0 (3.1%) |
1.0 / 23.0 (4.3%) |
|
|
|
| 5 |
7.0 / 98.0 (7.1%) |
4.0 / 23.0 (17.4%) |
|
|
|
| 6 |
2.0 / 98.0 (2.0%) |
9.0 / 23.0 (39.1%) |
|
|
|
| marshall5vs6 |
2.0 / 9.0 (22.2%) |
9.0 / 13.0 (69.2%) |
-47% |
-93%, -0.63% |
0.083 |
| Unknown |
89 |
10 |
|
|
|
| tipo_trauma |
|
|
0.04 |
-0.42, 0.49 |
|
| 0 |
93.0 / 98.0 (94.9%) |
22.0 / 23.0 (95.7%) |
|
|
|
| 1 |
5.0 / 98.0 (5.1%) |
1.0 / 23.0 (4.3%) |
|
|
|
| at_prehosp |
|
|
0.36 |
-0.09, 0.82 |
|
| 0 |
0.0 / 98.0 (0.0%) |
1.0 / 23.0 (4.3%) |
|
|
|
| 1 |
6.0 / 98.0 (6.1%) |
2.0 / 23.0 (8.7%) |
|
|
|
| 2 |
7.0 / 98.0 (7.1%) |
1.0 / 23.0 (4.3%) |
|
|
|
| 3 |
74.0 / 98.0 (75.5%) |
19.0 / 23.0 (82.6%) |
|
|
|
| 4 |
11.0 / 98.0 (11.2%) |
0.0 / 23.0 (0.0%) |
|
|
|
| iot_pre |
|
|
0.73 |
0.26, 1.2 |
|
| 0 |
79.0 / 98.0 (80.6%) |
11.0 / 23.0 (47.8%) |
|
|
|
| 1 |
19.0 / 98.0 (19.4%) |
12.0 / 23.0 (52.2%) |
|
|
|
| psicot |
|
|
0.34 |
-0.11, 0.80 |
|
| 0 |
77.0 / 98.0 (78.6%) |
19.0 / 23.0 (82.6%) |
|
|
|
| 1 |
13.0 / 98.0 (13.3%) |
1.0 / 23.0 (4.3%) |
|
|
|
| 2 |
8.0 / 98.0 (8.2%) |
3.0 / 23.0 (13.0%) |
|
|
|
| drogas |
|
|
0.45 |
-0.01, 0.91 |
|
| 0 |
89.0 / 98.0 (90.8%) |
23.0 / 23.0 (100.0%) |
|
|
|
| 1 |
9.0 / 98.0 (9.2%) |
0.0 / 23.0 (0.0%) |
|
|
|
| alcohol |
|
|
0.48 |
0.02, 0.93 |
|
| 0 |
88.0 / 98.0 (89.8%) |
23.0 / 23.0 (100.0%) |
|
|
|
| 1 |
10.0 / 98.0 (10.2%) |
0.0 / 23.0 (0.0%) |
|
|
|
| pupila_ing |
|
|
1.2 |
0.70, 1.7 |
|
| 0 |
91.0 / 98.0 (92.9%) |
11.0 / 23.0 (47.8%) |
|
|
|
| 1 |
6.0 / 98.0 (6.1%) |
4.0 / 23.0 (17.4%) |
|
|
|
| 2 |
1.0 / 98.0 (1.0%) |
8.0 / 23.0 (34.8%) |
|
|
|
| atx |
|
|
0.44 |
-0.02, 0.90 |
|
| 0 |
94.0 / 98.0 (95.9%) |
19.0 / 23.0 (82.6%) |
|
|
|
| 1 |
4.0 / 98.0 (4.1%) |
4.0 / 23.0 (17.4%) |
|
|
|
| calcio |
|
|
0.48 |
0.03, 0.94 |
|
| 0 |
97.0 / 98.0 (99.0%) |
20.0 / 23.0 (87.0%) |
|
|
|
| 1 |
1.0 / 98.0 (1.0%) |
3.0 / 23.0 (13.0%) |
|
|
|
| fc |
85.15 (21.72) 84.00 (72.00, 94.50) |
80.67 (29.47) 85.00 (70.00, 100.00) |
4.5 |
-9.6, 19 |
0.5 |
| Unknown |
7 |
2 |
|
|
|
| fr |
18.04 (5.48) 16.00 (15.00, 19.00) |
16.72 (6.81) 17.50 (15.00, 19.75) |
1.3 |
-2.3, 4.9 |
0.5 |
| Unknown |
25 |
5 |
|
|
|
| tas |
133.90 (27.26) 130.00 (118.50, 148.50) |
142.74 (55.91) 130.00 (113.00, 196.00) |
-8.8 |
-34, 16 |
0.5 |
| Unknown |
7 |
0 |
|
|
|
| gcs_ing |
12.38 (3.50) 14.00 (9.25, 15.00) |
6.22 (4.54) 3.00 (3.00, 8.00) |
6.2 |
4.1, 8.2 |
<0.001 |
| retrascore |
3.98 (3.02) 4.00 (2.00, 5.75) |
12.39 (3.74) 11.00 (9.50, 14.50) |
-8.4 |
-10, -6.7 |
<0.001 |
| supervivencia |
94.00 (8.13) 98.80 (91.90, 98.80) |
61.82 (30.00) 64.45 (42.20, 80.70) |
32 |
17, 47 |
<0.001 |
| Unknown |
25 |
5 |
|
|
|
| iss |
18.67 (10.27) 17.00 (12.25, 25.00) |
30.83 (10.55) 25.00 (25.00, 34.00) |
-12 |
-17, -7.2 |
<0.001 |
| apache_ii |
14.19 (6.70) 13.50 (9.00, 18.00) |
26.68 (7.55) 27.00 (22.50, 32.00) |
-12 |
-16, -8.9 |
<0.001 |
| Unknown |
2 |
1 |
|
|
|
| sofa_ingreso |
1.97 (2.27) 1.00 (0.00, 3.00) |
7.36 (4.09) 7.00 (4.00, 9.75) |
-5.4 |
-7.3, -3.5 |
<0.001 |
| Unknown |
0 |
1 |
|
|
|
| neurcx_urg |
|
|
0.24 |
-0.21, 0.70 |
|
| 0 |
89.0 / 98.0 (90.8%) |
19.0 / 23.0 (82.6%) |
|
|
|
| 1 |
9.0 / 98.0 (9.2%) |
4.0 / 23.0 (17.4%) |
|
|
|
| cx_urg |
|
|
0.10 |
-0.36, 0.55 |
|
| 0 |
92.0 / 98.0 (93.9%) |
21.0 / 23.0 (91.3%) |
|
|
|
| 1 |
6.0 / 98.0 (6.1%) |
2.0 / 23.0 (8.7%) |
|
|
|
| cx_no_urg |
|
|
0.41 |
-0.05, 0.87 |
|
| 0 |
82.0 / 98.0 (83.7%) |
22.0 / 23.0 (95.7%) |
|
|
|
| 1 |
14.0 / 98.0 (14.3%) |
1.0 / 23.0 (4.3%) |
|
|
|
| 2 |
1.0 / 98.0 (1.0%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 3 |
1.0 / 98.0 (1.0%) |
0.0 / 23.0 (0.0%) |
|
|
|
| ch_24h |
|
|
-0.59 |
-1.1, -0.13 |
|
| 0 |
87.0 / 98.0 (88.8%) |
13.0 / 23.0 (56.5%) |
|
|
|
| 1 |
1.0 / 98.0 (1.0%) |
3.0 / 23.0 (13.0%) |
|
|
|
| 2 |
6.0 / 98.0 (6.1%) |
3.0 / 23.0 (13.0%) |
|
|
|
| 3 |
2.0 / 98.0 (2.0%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 4 |
1.0 / 98.0 (1.0%) |
1.0 / 23.0 (4.3%) |
|
|
|
| 5 |
0.0 / 98.0 (0.0%) |
1.0 / 23.0 (4.3%) |
|
|
|
| 6 |
0.0 / 98.0 (0.0%) |
1.0 / 23.0 (4.3%) |
|
|
|
| 8 |
0.0 / 98.0 (0.0%) |
1.0 / 23.0 (4.3%) |
|
|
|
| 10 |
1.0 / 98.0 (1.0%) |
0.0 / 23.0 (0.0%) |
|
|
|
| pfc |
|
|
-0.77 |
-1.2, -0.30 |
|
| 0 |
95.0 / 98.0 (96.9%) |
15.0 / 23.0 (65.2%) |
|
|
|
| 1 |
1.0 / 98.0 (1.0%) |
1.0 / 23.0 (4.3%) |
|
|
|
| 2 |
1.0 / 98.0 (1.0%) |
5.0 / 23.0 (21.7%) |
|
|
|
| 3 |
1.0 / 98.0 (1.0%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 4 |
0.0 / 98.0 (0.0%) |
1.0 / 23.0 (4.3%) |
|
|
|
| 6 |
0.0 / 98.0 (0.0%) |
1.0 / 23.0 (4.3%) |
|
|
|
| fibrinogeno |
|
|
0.14 |
-0.31, 0.60 |
|
| 0 |
97.0 / 98.0 (99.0%) |
23.0 / 23.0 (100.0%) |
|
|
|
| 1 |
1.0 / 98.0 (1.0%) |
0.0 / 23.0 (0.0%) |
|
|
|
| plaquetas |
|
|
0.69 |
0.23, 1.2 |
|
| 0 |
95.0 / 98.0 (96.9%) |
17.0 / 23.0 (73.9%) |
|
|
|
| 1 |
3.0 / 98.0 (3.1%) |
5.0 / 23.0 (21.7%) |
|
|
|
| 2 |
0.0 / 98.0 (0.0%) |
1.0 / 23.0 (4.3%) |
|
|
|
| arterio |
|
|
0.21 |
-0.25, 0.66 |
|
| 0 |
97.0 / 98.0 (99.0%) |
22.0 / 23.0 (95.7%) |
|
|
|
| 1 |
1.0 / 98.0 (1.0%) |
1.0 / 23.0 (4.3%) |
|
|
|
| vm |
|
|
1.2 |
0.70, 1.7 |
|
| 0 |
55.0 / 98.0 (56.1%) |
2.0 / 23.0 (8.7%) |
|
|
|
| 1 |
43.0 / 98.0 (43.9%) |
21.0 / 23.0 (91.3%) |
|
|
|
| drenaje_toracico |
|
|
0.09 |
-0.36, 0.55 |
|
| 0 |
82.0 / 98.0 (83.7%) |
20.0 / 23.0 (87.0%) |
|
|
|
| 1 |
16.0 / 98.0 (16.3%) |
3.0 / 23.0 (13.0%) |
|
|
|
| traqueo |
|
|
0.39 |
-0.06, 0.85 |
|
| 0 |
91.0 / 98.0 (92.9%) |
23.0 / 23.0 (100.0%) |
|
|
|
| 1 |
7.0 / 98.0 (7.1%) |
0.0 / 23.0 (0.0%) |
|
|
|
| pic |
|
|
0.84 |
0.37, 1.3 |
|
| 0 |
87.0 / 98.0 (88.8%) |
13.0 / 23.0 (56.5%) |
|
|
|
| 1 |
9.0 / 98.0 (9.2%) |
7.0 / 23.0 (30.4%) |
|
|
|
| 2 |
1.0 / 98.0 (1.0%) |
3.0 / 23.0 (13.0%) |
|
|
|
| 3 |
1.0 / 98.0 (1.0%) |
0.0 / 23.0 (0.0%) |
|
|
|
| ptio2 |
|
|
0.36 |
-0.09, 0.82 |
|
| 0 |
97.0 / 98.0 (99.0%) |
21.0 / 23.0 (91.3%) |
|
|
|
| 1 |
1.0 / 98.0 (1.0%) |
2.0 / 23.0 (8.7%) |
|
|
|
| craniectomia |
|
|
0.14 |
-0.31, 0.60 |
|
| 0 |
93.0 / 98.0 (94.9%) |
21.0 / 23.0 (91.3%) |
|
|
|
| 1 |
5.0 / 98.0 (5.1%) |
2.0 / 23.0 (8.7%) |
|
|
|
| vasoactivos |
|
|
1.0 |
0.57, 1.5 |
|
| 0 |
75.0 / 98.0 (76.5%) |
7.0 / 23.0 (30.4%) |
|
|
|
| 1 |
23.0 / 98.0 (23.5%) |
16.0 / 23.0 (69.6%) |
|
|
|
| hemodinamica |
|
|
1.1 |
0.66, 1.6 |
|
| 0 |
73.0 / 98.0 (74.5%) |
7.0 / 23.0 (30.4%) |
|
|
|
| 1 |
4.0 / 98.0 (4.1%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 2 |
21.0 / 98.0 (21.4%) |
15.0 / 23.0 (65.2%) |
|
|
|
| 3 |
0.0 / 98.0 (0.0%) |
1.0 / 23.0 (4.3%) |
|
|
|
| coagu_trauma |
|
|
0.64 |
0.18, 1.1 |
|
| 0 |
96.0 / 98.0 (98.0%) |
18.0 / 23.0 (78.3%) |
|
|
|
| 1 |
2.0 / 98.0 (2.0%) |
5.0 / 23.0 (21.7%) |
|
|
|
| rabdomiolisis |
|
|
0.10 |
-0.36, 0.55 |
|
| 0 |
92.0 / 98.0 (93.9%) |
21.0 / 23.0 (91.3%) |
|
|
|
| 1 |
6.0 / 98.0 (6.1%) |
2.0 / 23.0 (8.7%) |
|
|
|
| hic |
|
|
1.4 |
0.89, 1.9 |
|
| 0 |
88.0 / 98.0 (89.8%) |
8.0 / 23.0 (34.8%) |
|
|
|
| 1 |
10.0 / 98.0 (10.2%) |
15.0 / 23.0 (65.2%) |
|
|
|
| medidas_hic |
|
|
-1.1 |
-1.6, -0.65 |
|
| 0 |
87.0 / 98.0 (88.8%) |
7.0 / 23.0 (30.4%) |
|
|
|
| 1 |
6.0 / 98.0 (6.1%) |
10.0 / 23.0 (43.5%) |
|
|
|
| 2 |
5.0 / 98.0 (5.1%) |
3.0 / 23.0 (13.0%) |
|
|
|
| 3 |
0.0 / 98.0 (0.0%) |
1.0 / 23.0 (4.3%) |
|
|
|
| 4 |
0.0 / 98.0 (0.0%) |
2.0 / 23.0 (8.7%) |
|
|
|
| disf_resp |
|
|
0.89 |
0.42, 1.4 |
|
| 0 |
60.0 / 97.0 (61.9%) |
5.0 / 23.0 (21.7%) |
|
|
|
| 1 |
37.0 / 97.0 (38.1%) |
18.0 / 23.0 (78.3%) |
|
|
|
| Unknown |
1 |
0 |
|
|
|
| p_f |
|
|
-0.96 |
-1.4, -0.49 |
|
| 0 |
58.0 / 98.0 (59.2%) |
4.0 / 23.0 (17.4%) |
|
|
|
| 1 |
29.0 / 98.0 (29.6%) |
8.0 / 23.0 (34.8%) |
|
|
|
| 2 |
5.0 / 98.0 (5.1%) |
7.0 / 23.0 (30.4%) |
|
|
|
| 3 |
5.0 / 98.0 (5.1%) |
4.0 / 23.0 (17.4%) |
|
|
|
| 4 |
1.0 / 98.0 (1.0%) |
0.0 / 23.0 (0.0%) |
|
|
|
| hemo_masiva |
|
|
0.65 |
0.19, 1.1 |
|
| 0 |
98.0 / 98.0 (100.0%) |
19.0 / 23.0 (82.6%) |
|
|
|
| 1 |
0.0 / 98.0 (0.0%) |
4.0 / 23.0 (17.4%) |
|
|
|
| sdmo |
|
|
0.93 |
0.46, 1.4 |
|
| 0 |
96.0 / 98.0 (98.0%) |
15.0 / 23.0 (65.2%) |
|
|
|
| 1 |
2.0 / 98.0 (2.0%) |
8.0 / 23.0 (34.8%) |
|
|
|
| inf_nosocomial |
|
|
0.25 |
-0.20, 0.71 |
|
| 0 |
75.0 / 98.0 (76.5%) |
15.0 / 23.0 (65.2%) |
|
|
|
| 1 |
23.0 / 98.0 (23.5%) |
8.0 / 23.0 (34.8%) |
|
|
|
| leucos |
6,564.44 (11,072.35) 15.30 (11.50, 12,300.00) |
7,897.36 (9,287.68) 17.80 (11.55, 14,100.00) |
-1,333 |
-5,865, 3,199 |
0.6 |
| Unknown |
1 |
0 |
|
|
|
| nt |
5,211.67 (11,410.23) 87.90 (80.45, 8,450.00) |
5,612.24 (7,345.56) 86.30 (80.20, 10,600.00) |
-401 |
-4,400, 3,599 |
0.8 |
| Unknown |
3 |
2 |
|
|
|
| linfos |
652.56 (1,292.40) 14.90 (7.10, 600.00) |
691.58 (1,191.06) 17.20 (6.30, 1,000.00) |
-39 |
-674, 595 |
>0.9 |
| Unknown |
21 |
4 |
|
|
|
| eos |
41.02 (105.70) 0.25 (0.00, 1.85) |
44.74 (104.03) 0.10 (0.00, 0.78) |
-3.7 |
-60, 53 |
0.9 |
| Unknown |
24 |
5 |
|
|
|
| hb |
144.83 (1,298.32) 13.30 (11.80, 14.40) |
11.84 (2.39) 12.30 (10.30, 13.40) |
133 |
-129, 395 |
0.3 |
| Unknown |
1 |
0 |
|
|
|
| hto |
38.72 (5.28) 39.35 (35.03, 42.68) |
35.16 (7.47) 37.30 (30.90, 40.40) |
3.6 |
0.01, 7.1 |
0.049 |
| Unknown |
8 |
2 |
|
|
|
| plq |
97,113.57 (115,746.16) 251.00 (169.00, 208,000.00) |
90,431.09 (108,263.44) 278.00 (155.50, 174,500.00) |
6,682 |
-44,987, 58,352 |
0.8 |
| Unknown |
1 |
0 |
|
|
|
| inr |
1.21 (0.59) 1.08 (1.00, 1.18) |
1.41 (0.64) 1.19 (1.07, 1.38) |
-0.20 |
-0.50, 0.10 |
0.2 |
| Unknown |
5 |
0 |
|
|
|
| ap |
85.85 (19.22) 90.00 (79.75, 97.00) |
72.38 (27.60) 76.00 (65.00, 93.00) |
13 |
0.39, 27 |
0.044 |
| Unknown |
6 |
2 |
|
|
|
| ttpa |
29.11 (8.71) 28.45 (26.00, 30.63) |
32.31 (8.09) 30.00 (27.08, 35.45) |
-3.2 |
-7.2, 0.76 |
0.11 |
| Unknown |
6 |
1 |
|
|
|
| fibrinogeno_2 |
408.64 (153.67) 385.00 (306.00, 452.00) |
368.24 (144.82) 358.00 (243.00, 469.00) |
40 |
-32, 113 |
0.3 |
| Unknown |
9 |
2 |
|
|
|
| gluc |
146.74 (52.89) 137.50 (118.00, 153.75) |
187.19 (48.14) 187.00 (150.00, 212.00) |
-40 |
-65, -16 |
0.002 |
| Unknown |
4 |
2 |
|
|
|
| urea |
34.73 (15.31) 33.00 (25.00, 41.60) |
40.88 (13.99) 40.10 (28.50, 49.00) |
-6.1 |
-14, 1.6 |
0.12 |
| Unknown |
12 |
6 |
|
|
|
| crea |
0.86 (0.27) 0.80 (0.72, 0.97) |
1.09 (0.39) 0.90 (0.76, 1.40) |
-0.22 |
-0.41, -0.04 |
0.018 |
| Unknown |
1 |
2 |
|
|
|
| na |
136.75 (4.36) 137.00 (136.00, 138.00) |
136.91 (4.53) 137.00 (135.25, 139.00) |
-0.16 |
-2.3, 2.0 |
0.9 |
| Unknown |
2 |
1 |
|
|
|
| k |
3.91 (0.54) 3.90 (3.60, 4.20) |
3.93 (0.32) 4.00 (3.80, 4.18) |
-0.02 |
-0.19, 0.16 |
0.8 |
| Unknown |
2 |
1 |
|
|
|
| cl |
107.21 (11.08) 106.00 (104.00, 108.00) |
107.40 (5.18) 108.00 (106.00, 109.50) |
-0.19 |
-3.9, 3.5 |
>0.9 |
| Unknown |
23 |
8 |
|
|
|
| ca_ionico |
6.36 (15.60) 4.52 (4.40, 4.70) |
4.40 (0.34) 4.35 (4.23, 4.58) |
2.0 |
-1.5, 5.4 |
0.3 |
| Unknown |
19 |
4 |
|
|
|
| mg |
1.89 (0.28) 1.90 (1.72, 2.02) |
1.67 (0.22) 1.64 (1.50, 1.90) |
0.22 |
0.08, 0.36 |
0.003 |
| Unknown |
44 |
8 |
|
|
|
| p |
2.96 (0.73) 3.00 (2.50, 3.40) |
2.95 (0.99) 3.00 (2.25, 3.40) |
0.01 |
-0.56, 0.59 |
>0.9 |
| Unknown |
45 |
8 |
|
|
|
| alb |
3.36 (0.63) 3.50 (3.15, 3.70) |
2.98 (0.82) 3.10 (2.50, 3.40) |
0.38 |
-0.20, 0.96 |
0.2 |
| Unknown |
63 |
12 |
|
|
|
| bilit |
0.78 (0.57) 0.65 (0.46, 0.89) |
0.85 (0.51) 0.67 (0.60, 0.90) |
-0.07 |
-0.39, 0.25 |
0.7 |
| Unknown |
28 |
9 |
|
|
|
| ph |
7.23 (0.88) 7.37 (7.33, 7.41) |
7.36 (0.13) 7.37 (7.33, 7.43) |
-0.13 |
-0.32, 0.06 |
0.2 |
| Unknown |
7 |
0 |
|
|
|
| pco2 |
40.56 (9.53) 39.00 (35.00, 43.00) |
38.96 (12.82) 36.00 (30.00, 42.50) |
1.6 |
-4.2, 7.4 |
0.6 |
| Unknown |
9 |
0 |
|
|
|
| po2 |
95.41 (62.55) 77.00 (49.75, 124.75) |
108.14 (51.61) 113.00 (69.25, 133.50) |
-13 |
-39, 13 |
0.3 |
| Unknown |
14 |
1 |
|
|
|
| hco3 |
22.92 (3.18) 23.20 (21.63, 24.95) |
21.55 (3.89) 22.00 (20.00, 23.40) |
1.4 |
-0.42, 3.2 |
0.13 |
| Unknown |
8 |
0 |
|
|
|
| eb |
-2.18 (3.50) -1.65 (-4.00, 0.03) |
-3.45 (4.90) -2.60 (-5.23, -0.73) |
1.3 |
-1.1, 3.7 |
0.3 |
| Unknown |
14 |
3 |
|
|
|
| lactato |
2.06 (1.14) 1.80 (1.20, 2.60) |
3.56 (2.91) 3.00 (1.60, 4.30) |
-1.5 |
-2.8, -0.15 |
0.031 |
| Unknown |
9 |
2 |
|
|
|
| dest_uci |
|
|
2.3 |
1.8, 2.8 |
|
| 0 |
0.0 / 98.0 (0.0%) |
18.0 / 23.0 (78.3%) |
|
|
|
| 1 |
11.0 / 98.0 (11.2%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 2 |
85.0 / 98.0 (86.7%) |
5.0 / 23.0 (21.7%) |
|
|
|
| 3 |
1.0 / 98.0 (1.0%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 4 |
1.0 / 98.0 (1.0%) |
0.0 / 23.0 (0.0%) |
|
|
|
| dias_uci |
8.69 (11.38) 4.00 (2.00, 10.75) |
7.30 (6.79) 4.00 (2.00, 13.00) |
1.4 |
-2.3, 5.0 |
0.4 |
| est_hosp |
16.37 (16.18) 10.00 (6.00, 21.00) |
76.26 (302.55) 6.00 (2.00, 19.00) |
-60 |
-191, 71 |
0.4 |
| Unknown |
1 |
0 |
|
|
|
| dest_hosp |
|
|
7.6 |
6.6, 8.7 |
|
| 0 |
1.0 / 98.0 (1.0%) |
23.0 / 23.0 (100.0%) |
|
|
|
| 1 |
1.0 / 98.0 (1.0%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 2 |
7.0 / 98.0 (7.1%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 3 |
79.0 / 98.0 (80.6%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 4 |
10.0 / 98.0 (10.2%) |
0.0 / 23.0 (0.0%) |
|
|
|
| ltsv |
|
|
3.5 |
2.8, 4.1 |
|
| 0 |
97.0 / 98.0 (99.0%) |
3.0 / 23.0 (13.0%) |
|
|
|
| 1 |
1.0 / 98.0 (1.0%) |
20.0 / 23.0 (87.0%) |
|
|
|
| m_rankin_alta_hospitalaria |
|
|
-5.1 |
-5.9, -4.3 |
|
| 1 |
50.0 / 98.0 (51.0%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 2 |
23.0 / 98.0 (23.5%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 3 |
13.0 / 98.0 (13.3%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 4 |
9.0 / 98.0 (9.2%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 5 |
3.0 / 98.0 (3.1%) |
0.0 / 23.0 (0.0%) |
|
|
|
| 6 |
0.0 / 98.0 (0.0%) |
23.0 / 23.0 (100.0%) |
|
|
|
| dependiente |
12.0 / 98.0 (12.2%) |
23.0 / 23.0 (100.0%) |
-88% |
-97%, -79% |
<0.001 |
| opicu |
15.0 / 98.0 (15.3%) |
14.0 / 23.0 (60.9%) |
-46% |
-69%, -22% |
<0.001 |
#calcula la mortalidad en función de la gravedad del TCE
tce2 %>%
tbl_cross(
row = mecanismo,
col = opicu,
percent = "col"
) %>%
bold_labels() %>%
add_p()
|
opicu
|
Total |
p-value |
| 0 |
1 |
| mecanismo |
|
|
|
0.017 |
| 1 |
15 (16%) |
17 (59%) |
32 (26%) |
|
| 2 |
6 (6.3%) |
0 (0%) |
6 (4.8%) |
|
| 4 |
21 (22%) |
5 (17%) |
26 (21%) |
|
| 5 |
5 (5.2%) |
0 (0%) |
5 (4.0%) |
|
| 8 |
24 (25%) |
4 (14%) |
28 (22%) |
|
| 9 |
7 (7.3%) |
2 (6.9%) |
9 (7.2%) |
|
| 10 |
2 (2.1%) |
0 (0%) |
2 (1.6%) |
|
| 11 |
1 (1.0%) |
0 (0%) |
1 (0.8%) |
|
| 12 |
5 (5.2%) |
0 (0%) |
5 (4.0%) |
|
| 13 |
1 (1.0%) |
0 (0%) |
1 (0.8%) |
|
| 14 |
1 (1.0%) |
0 (0%) |
1 (0.8%) |
|
| 15 |
8 (8.3%) |
1 (3.4%) |
9 (7.2%) |
|
| Total |
96 (100%) |
29 (100%) |
125 (100%) |
|
Días de Uci y VM en función de si el paciente es OPICU o
dependiente
- Días de UCI en función de paciente dependiente o no
dependiente
- Días de VM en función de paciente dependiente o no
dependiente
- Dias de UCI en función de paciente OPICU o no
OPICU
- Días de VM en función de paciente OPICU o no
OPICU
#crea una tabla con resumen de dias de uci y días de VM, en función de dependencia
tce2 %>%
tbl_summary(
include = c(dias_uci, est_hosp),
by = dependiente,
statistic = list(
all_continuous() ~ "{mean} ({sd}) {median} ({p25}, {p75})",
all_categorical() ~ "{n} / {N} ({p}%)"
),
digits = list(
all_continuous() ~ 2,
all_categorical() ~ 1
)
) %>%
bold_labels() %>%
add_difference()
## 4 observations missing `dependiente` have been removed. To include these observations, use `forcats::fct_na_value_to_level()` on `dependiente` column before passing to `tbl_summary()`.
| Characteristic |
0, N = 86 |
1, N = 35 |
Difference |
95% CI |
p-value |
| dias_uci |
6.90 (8.30) 4.00 (2.00, 7.75) |
12.20 (14.41) 8.00 (3.00, 16.50) |
-5.3 |
-11, -0.07 |
0.047 |
| est_hosp |
14.02 (13.26) 9.00 (6.00, 19.00) |
61.43 (244.66) 12.00 (4.00, 27.00) |
-47 |
-131, 37 |
0.3 |
| Unknown |
1 |
0 |
|
|
|
tce2 %>%
filter(vm == 1) %>%
tbl_summary(
include = vm_dias,
by = dependiente,
statistic = list(
all_continuous() ~ "{mean} ({sd}) {median} ({p25}, {p75})",
all_categorical() ~ "{n} / {N} ({p}%)"
),
digits = list(
all_continuous() ~ 2,
all_categorical() ~ 1
)
) %>%
bold_labels() %>%
add_difference()
## 2 observations missing `dependiente` have been removed. To include these observations, use `forcats::fct_na_value_to_level()` on `dependiente` column before passing to `tbl_summary()`.
| Characteristic |
0, N = 32 |
1, N = 32 |
Difference |
95% CI |
p-value |
| vm_dias |
8.69 (8.71) 6.00 (1.00, 14.25) |
9.22 (12.45) 5.00 (2.00, 13.00) |
-0.53 |
-5.9, 4.9 |
0.8 |
#crea una tabla con descriptivos de días de uci y días de VM, en función de opicu
tce2 %>%
tbl_summary(
include = c(dias_uci, est_hosp),
by = opicu,
statistic = list(
all_continuous() ~ "{mean} ({sd}) {median} ({p25}, {p75})",
all_categorical() ~ "{n} / {N} ({p}%)"
),
digits = list(
all_continuous() ~ 2,
all_categorical() ~ 1
)
) %>%
bold_labels() %>%
add_difference()
| Characteristic |
0, N = 96 |
1, N = 29 |
Difference |
95% CI |
p-value |
| dias_uci |
9.02 (11.53) 4.00 (2.00, 12.00) |
6.34 (5.94) 4.00 (2.00, 11.00) |
2.7 |
-0.54, 5.9 |
0.10 |
| Unknown |
1 |
0 |
|
|
|
| est_hosp |
15.38 (16.48) 8.50 (5.00, 19.00) |
65.90 (268.95) 11.00 (4.00, 22.00) |
-51 |
-153, 52 |
0.3 |
| Unknown |
2 |
0 |
|
|
|
tce2 %>%
filter(vm == 1) %>%
tbl_summary(
include = vm_dias,
by = opicu,
statistic = list(
all_continuous() ~ "{mean} ({sd}) {median} ({p25}, {p75})",
all_categorical() ~ "{n} / {N} ({p}%)"
),
digits = list(
all_continuous() ~ 2,
all_categorical() ~ 1
)
) %>%
bold_labels() %>%
add_difference()
| Characteristic |
0, N = 47 |
1, N = 19 |
Difference |
95% CI |
p-value |
| vm_dias |
10.49 (11.80) 6.00 (2.00, 15.50) |
5.16 (4.76) 3.00 (1.00, 8.50) |
5.3 |
1.3, 9.4 |
0.011 |
Regresión logistica
- 4 modelos de regresión logística
- Añade al último modelo GCS al ingreso, Glu, lactato, urea y cre
#crea una regresión logistica con la variable exitus como dependiente
#con las odds ratios y los intervalos de confianza
modelo1 <- glm(exitus ~ edad + sexo + gcs_ing + retrascore+ iss +
apache_ii + sofa_ingreso, data = tce_puro, family = binomial(link = "logit"))
#me muestra las variables del modelo con las odds ratios y los intervalos de confianza
summary(modelo1)
##
## Call:
## glm(formula = exitus ~ edad + sexo + gcs_ing + retrascore + iss +
## apache_ii + sofa_ingreso, family = binomial(link = "logit"),
## data = tce_puro)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.12065 -0.13355 -0.02981 -0.00420 2.23541
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -13.82775 4.69382 -2.946 0.00322 **
## edad 0.11502 0.05262 2.186 0.02883 *
## sexo1 -0.66084 1.22924 -0.538 0.59085
## gcs_ing -0.19369 0.18146 -1.067 0.28579
## retrascore 0.36448 0.21416 1.702 0.08877 .
## iss 0.14274 0.06271 2.276 0.02283 *
## apache_ii -0.07075 0.09173 -0.771 0.44053
## sofa_ingreso 0.33883 0.20197 1.678 0.09342 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 110.124 on 116 degrees of freedom
## Residual deviance: 31.046 on 109 degrees of freedom
## (8 observations deleted due to missingness)
## AIC: 47.046
##
## Number of Fisher Scoring iterations: 8
t1 <- tbl_regression(modelo1, exponentiate = TRUE)
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
t1
| Characteristic |
OR |
95% CI |
p-value |
| edad |
1.12 |
1.03, 1.27 |
0.029 |
| sexo |
|
|
|
| 0 |
— |
— |
|
| 1 |
0.52 |
0.04, 5.22 |
0.6 |
| gcs_ing |
0.82 |
0.55, 1.15 |
0.3 |
| retrascore |
1.44 |
0.97, 2.35 |
0.089 |
| iss |
1.15 |
1.03, 1.33 |
0.023 |
| apache_ii |
0.93 |
0.76, 1.10 |
0.4 |
| sofa_ingreso |
1.40 |
0.98, 2.21 |
0.093 |
#crea un modelo con la variable exitus como dependiente
#y los valores de parámetros de analítica
modelo2 <- glm(exitus ~ hto + ap + ttpa + gluc + urea + crea + mg +
alb + ph + hco3 + lactato,
data = tce_puro, family = binomial(link = "logit"))
#muestra las variables del modelo2
summary(modelo2)
##
## Call:
## glm(formula = exitus ~ hto + ap + ttpa + gluc + urea + crea +
## mg + alb + ph + hco3 + lactato, family = binomial(link = "logit"),
## data = tce_puro)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.6868 -0.3982 -0.1477 0.2217 2.9085
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 3.536253 18.787625 0.188 0.8507
## hto -0.112886 0.135945 -0.830 0.4063
## ap 0.011185 0.042254 0.265 0.7912
## ttpa 0.497046 0.279238 1.780 0.0751 .
## gluc 0.005530 0.009341 0.592 0.5538
## urea -0.014507 0.064836 -0.224 0.8229
## crea 3.342835 2.987311 1.119 0.2631
## mg -9.091236 4.380223 -2.076 0.0379 *
## alb 1.009243 1.220229 0.827 0.4082
## ph -0.390180 1.575236 -0.248 0.8044
## hco3 -0.170362 0.199808 -0.853 0.3939
## lactato 0.031822 0.546829 0.058 0.9536
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 44.403 on 38 degrees of freedom
## Residual deviance: 21.756 on 27 degrees of freedom
## (86 observations deleted due to missingness)
## AIC: 45.756
##
## Number of Fisher Scoring iterations: 7
t2 <- tbl_regression(modelo2, exponentiate = TRUE)
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
t2
| Characteristic |
OR |
95% CI |
p-value |
| hto |
0.89 |
0.65, 1.15 |
0.4 |
| ap |
1.01 |
0.93, 1.11 |
0.8 |
| ttpa |
1.64 |
1.04, 3.30 |
0.075 |
| gluc |
1.01 |
0.99, 1.03 |
0.6 |
| urea |
0.99 |
0.85, 1.13 |
0.8 |
| crea |
28.3 |
0.19, 90,595 |
0.3 |
| mg |
0.00 |
0.00, 0.14 |
0.038 |
| alb |
2.74 |
0.26, 39.9 |
0.4 |
| ph |
0.68 |
0.13, NA |
0.8 |
| hco3 |
0.84 |
0.52, 1.19 |
0.4 |
| lactato |
1.03 |
0.30, 3.14 |
>0.9 |
#crea un modelo conjunto con la variable exitus como dependiente
#y las variables de los modelos 1 y 2
modelo3 <- glm(exitus ~ edad + gcs_ing + retrascore + iss +
apache_ii + hto + ap + ttpa + gluc + urea + crea + mg + lactato,
data = tce_puro, family = binomial(link = "logit"))
#muestra las variables del modelo3 con odds ratios e intervalos de confianza
summary(modelo3)
##
## Call:
## glm(formula = exitus ~ edad + gcs_ing + retrascore + iss + apache_ii +
## hto + ap + ttpa + gluc + urea + crea + mg + lactato, family = binomial(link = "logit"),
## data = tce_puro)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.88448 -0.13257 -0.02046 -0.00296 2.01155
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -18.976891 19.149288 -0.991 0.322
## edad 0.049065 0.088700 0.553 0.580
## gcs_ing -0.380730 0.326408 -1.166 0.243
## retrascore 0.279517 0.487894 0.573 0.567
## iss 0.242832 0.244265 0.994 0.320
## apache_ii -0.049208 0.306214 -0.161 0.872
## hto 0.107566 0.166426 0.646 0.518
## ap 0.003081 0.055511 0.056 0.956
## ttpa 0.256150 0.347682 0.737 0.461
## gluc -0.003237 0.014641 -0.221 0.825
## urea -0.016427 0.104978 -0.156 0.876
## crea 8.150086 12.361416 0.659 0.510
## mg -3.394673 6.065742 -0.560 0.576
## lactato -0.931462 1.204149 -0.774 0.439
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 60.490 on 60 degrees of freedom
## Residual deviance: 15.194 on 47 degrees of freedom
## (64 observations deleted due to missingness)
## AIC: 43.194
##
## Number of Fisher Scoring iterations: 10
t3 <- tbl_regression(modelo3, exponentiate = TRUE)
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
t3
| Characteristic |
OR |
95% CI |
p-value |
| edad |
1.05 |
0.87, 1.31 |
0.6 |
| gcs_ing |
0.68 |
0.26, 1.22 |
0.2 |
| retrascore |
1.32 |
0.60, 6.53 |
0.6 |
| iss |
1.27 |
1.00, 3.44 |
0.3 |
| apache_ii |
0.95 |
0.35, 1.61 |
0.9 |
| hto |
1.11 |
0.74, 1.74 |
0.5 |
| ap |
1.00 |
0.89, 1.14 |
>0.9 |
| ttpa |
1.29 |
0.79, 3.20 |
0.5 |
| gluc |
1.00 |
0.96, 1.03 |
0.8 |
| urea |
0.98 |
0.74, 1.20 |
0.9 |
| crea |
3,464 |
0.01, 2,365,071,750,154,421,952,053,248 |
0.5 |
| mg |
0.03 |
0.00, 2,444 |
0.6 |
| lactato |
0.39 |
0.00, 2.69 |
0.4 |
#crea un modelo con la variable exitus como dependiente
#y las variables de los modelos 1 y 2
modelo4 <- glm(exitus ~ edad + iss +ttpa + mg,
data = tce_puro, family = binomial(link = "logit"))
#muestra las variables del modelo4 con odds ratios e intervalos de confianza
summary(modelo4)
##
## Call:
## glm(formula = exitus ~ edad + iss + ttpa + mg, family = binomial(link = "logit"),
## data = tce_puro)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -2.37052 -0.31782 -0.10873 -0.01971 1.81262
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -10.59141 5.70331 -1.857 0.0633 .
## edad 0.08636 0.03459 2.497 0.0125 *
## iss 0.13742 0.05663 2.427 0.0152 *
## ttpa 0.24250 0.14257 1.701 0.0890 .
## mg -3.70980 2.19723 -1.688 0.0913 .
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 71.761 on 67 degrees of freedom
## Residual deviance: 30.801 on 63 degrees of freedom
## (57 observations deleted due to missingness)
## AIC: 40.801
##
## Number of Fisher Scoring iterations: 7
t4 <- tbl_regression(modelo4, exponentiate = TRUE)
t4
| Characteristic |
OR |
95% CI |
p-value |
| edad |
1.09 |
1.03, 1.18 |
0.013 |
| iss |
1.15 |
1.05, 1.32 |
0.015 |
| ttpa |
1.27 |
1.03, 1.83 |
0.089 |
| mg |
0.02 |
0.00, 1.25 |
0.091 |
#crea un modelo con la variable exitus como dependiente
#y las variables de los modelos 1 y 2 junto a GCS al ingreso, Glu, lactato, urea y cre
modelo5 <- glm(exitus ~ edad + gluc + lactato + urea + crea + gcs_ing + iss +ttpa + mg, data = tce2, family = binomial(link = "logit"))
summary(modelo5)
##
## Call:
## glm(formula = exitus ~ edad + gluc + lactato + urea + crea +
## gcs_ing + iss + ttpa + mg, family = binomial(link = "logit"),
## data = tce2)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.62450 -0.15328 -0.05030 -0.00379 2.58950
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -8.366846 11.792704 -0.709 0.4780
## edad 0.135481 0.069391 1.952 0.0509 .
## gluc -0.007679 0.010296 -0.746 0.4558
## lactato 0.403507 0.579199 0.697 0.4860
## urea -0.033833 0.076949 -0.440 0.6602
## crea 3.396026 5.475760 0.620 0.5351
## gcs_ing -0.427538 0.215662 -1.982 0.0474 *
## iss 0.113302 0.073730 1.537 0.1244
## ttpa 0.147845 0.261534 0.565 0.5719
## mg -3.354266 3.741116 -0.897 0.3699
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 67.731 on 64 degrees of freedom
## Residual deviance: 18.884 on 55 degrees of freedom
## (60 observations deleted due to missingness)
## AIC: 38.884
##
## Number of Fisher Scoring iterations: 8
t5 <- tbl_regression(modelo5, exponentiate = TRUE)
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
t5
| Characteristic |
OR |
95% CI |
p-value |
| edad |
1.15 |
1.04, 1.41 |
0.051 |
| gluc |
0.99 |
0.97, 1.01 |
0.5 |
| lactato |
1.50 |
0.51, 5.61 |
0.5 |
| urea |
0.97 |
0.81, 1.13 |
0.7 |
| crea |
29.8 |
0.00, 22,278,787 |
0.5 |
| gcs_ing |
0.65 |
0.34, 0.91 |
0.047 |
| iss |
1.12 |
0.99, 1.36 |
0.12 |
| ttpa |
1.16 |
0.81, 2.27 |
0.6 |
| mg |
0.03 |
0.00, 30.5 |
0.4 |
#retiro las variables menos relevantes
modelo6 <- glm(exitus ~ edad + gluc + gcs_ing + lactato + iss + mg, data = tce2, family = binomial(link = "logit"))
summary(modelo6)
##
## Call:
## glm(formula = exitus ~ edad + gluc + gcs_ing + lactato + iss +
## mg, family = binomial(link = "logit"), data = tce2)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.44805 -0.20415 -0.04598 -0.00312 2.95385
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -2.317640 7.159386 -0.324 0.7461
## edad 0.144537 0.059156 2.443 0.0146 *
## gluc -0.006144 0.008694 -0.707 0.4797
## gcs_ing -0.465297 0.184065 -2.528 0.0115 *
## lactato 0.483690 0.534916 0.904 0.3659
## iss 0.095615 0.062076 1.540 0.1235
## mg -3.647557 3.461804 -1.054 0.2920
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 68.211 on 65 degrees of freedom
## Residual deviance: 19.622 on 59 degrees of freedom
## (59 observations deleted due to missingness)
## AIC: 33.622
##
## Number of Fisher Scoring iterations: 8
t6 <- tbl_regression(modelo6, exponentiate = TRUE)
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
t6
| Characteristic |
OR |
95% CI |
p-value |
| edad |
1.16 |
1.05, 1.34 |
0.015 |
| gluc |
0.99 |
0.97, 1.01 |
0.5 |
| gcs_ing |
0.63 |
0.39, 0.85 |
0.011 |
| lactato |
1.62 |
0.64, 5.69 |
0.4 |
| iss |
1.10 |
0.98, 1.28 |
0.12 |
| mg |
0.03 |
0.00, 9.69 |
0.3 |
#el mg y el lactato parece que actuan como factores de confusón por lo que los mantemgo en el modelo
#resumen de los modelos
tbl_merge(
tbls = list(t1, t2, t3, t4, t5, t6),
tab_spanner = c("**M1**", "**M2**", "**M3**", "**M4**", "**M5**", "**M6**")
)
| Characteristic |
M1
|
M2
|
M3
|
M4
|
M5
|
M6
|
| OR |
95% CI |
p-value |
OR |
95% CI |
p-value |
OR |
95% CI |
p-value |
OR |
95% CI |
p-value |
OR |
95% CI |
p-value |
OR |
95% CI |
p-value |
| edad |
1.12 |
1.03, 1.27 |
0.029 |
|
|
|
1.05 |
0.87, 1.31 |
0.6 |
1.09 |
1.03, 1.18 |
0.013 |
1.15 |
1.04, 1.41 |
0.051 |
1.16 |
1.05, 1.34 |
0.015 |
| sexo |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 0 |
— |
— |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| 1 |
0.52 |
0.04, 5.22 |
0.6 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| gcs_ing |
0.82 |
0.55, 1.15 |
0.3 |
|
|
|
0.68 |
0.26, 1.22 |
0.2 |
|
|
|
0.65 |
0.34, 0.91 |
0.047 |
0.63 |
0.39, 0.85 |
0.011 |
| retrascore |
1.44 |
0.97, 2.35 |
0.089 |
|
|
|
1.32 |
0.60, 6.53 |
0.6 |
|
|
|
|
|
|
|
|
|
| iss |
1.15 |
1.03, 1.33 |
0.023 |
|
|
|
1.27 |
1.00, 3.44 |
0.3 |
1.15 |
1.05, 1.32 |
0.015 |
1.12 |
0.99, 1.36 |
0.12 |
1.10 |
0.98, 1.28 |
0.12 |
| apache_ii |
0.93 |
0.76, 1.10 |
0.4 |
|
|
|
0.95 |
0.35, 1.61 |
0.9 |
|
|
|
|
|
|
|
|
|
| sofa_ingreso |
1.40 |
0.98, 2.21 |
0.093 |
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
| hto |
|
|
|
0.89 |
0.65, 1.15 |
0.4 |
1.11 |
0.74, 1.74 |
0.5 |
|
|
|
|
|
|
|
|
|
| ap |
|
|
|
1.01 |
0.93, 1.11 |
0.8 |
1.00 |
0.89, 1.14 |
>0.9 |
|
|
|
|
|
|
|
|
|
| ttpa |
|
|
|
1.64 |
1.04, 3.30 |
0.075 |
1.29 |
0.79, 3.20 |
0.5 |
1.27 |
1.03, 1.83 |
0.089 |
1.16 |
0.81, 2.27 |
0.6 |
|
|
|
| gluc |
|
|
|
1.01 |
0.99, 1.03 |
0.6 |
1.00 |
0.96, 1.03 |
0.8 |
|
|
|
0.99 |
0.97, 1.01 |
0.5 |
0.99 |
0.97, 1.01 |
0.5 |
| urea |
|
|
|
0.99 |
0.85, 1.13 |
0.8 |
0.98 |
0.74, 1.20 |
0.9 |
|
|
|
0.97 |
0.81, 1.13 |
0.7 |
|
|
|
| crea |
|
|
|
28.3 |
0.19, 90,595 |
0.3 |
3,464 |
0.01, 2,365,071,750,154,421,952,053,248 |
0.5 |
|
|
|
29.8 |
0.00, 22,278,787 |
0.5 |
|
|
|
| mg |
|
|
|
0.00 |
0.00, 0.14 |
0.038 |
0.03 |
0.00, 2,444 |
0.6 |
0.02 |
0.00, 1.25 |
0.091 |
0.03 |
0.00, 30.5 |
0.4 |
0.03 |
0.00, 9.69 |
0.3 |
| alb |
|
|
|
2.74 |
0.26, 39.9 |
0.4 |
|
|
|
|
|
|
|
|
|
|
|
|
| ph |
|
|
|
0.68 |
0.13, NA |
0.8 |
|
|
|
|
|
|
|
|
|
|
|
|
| hco3 |
|
|
|
0.84 |
0.52, 1.19 |
0.4 |
|
|
|
|
|
|
|
|
|
|
|
|
| lactato |
|
|
|
1.03 |
0.30, 3.14 |
>0.9 |
0.39 |
0.00, 2.69 |
0.4 |
|
|
|
1.50 |
0.51, 5.61 |
0.5 |
1.62 |
0.64, 5.69 |
0.4 |
Modelos de regresión logística con la variable “dependencia”
como variable dependiente
#crea una regresión logistica con la variable dependiente como var ependiente
modelo7 <- glm(dependiente ~ edad + sexo + gcs_ing + retrascore + iss + gcs_ing
+ apache_ii + sofa_ingreso, data = tce2, family = binomial(link = "logit"))
#me muestra las variables del modelo con las odds ratios y los intervalos de confianza
summary(modelo7)
##
## Call:
## glm(formula = dependiente ~ edad + sexo + gcs_ing + retrascore +
## iss + gcs_ing + apache_ii + sofa_ingreso, family = binomial(link = "logit"),
## data = tce2)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.6265 -0.4660 -0.1771 0.1095 3.2585
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -6.632419 1.907752 -3.477 0.000508 ***
## edad 0.008689 0.026390 0.329 0.741954
## sexo1 0.621843 0.819626 0.759 0.448037
## gcs_ing -0.008962 0.118404 -0.076 0.939669
## retrascore 0.406849 0.185617 2.192 0.028389 *
## iss 0.087135 0.033407 2.608 0.009101 **
## apache_ii -0.012072 0.059403 -0.203 0.838961
## sofa_ingreso 0.173147 0.142354 1.216 0.223866
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 137.291 on 116 degrees of freedom
## Residual deviance: 66.347 on 109 degrees of freedom
## (8 observations deleted due to missingness)
## AIC: 82.347
##
## Number of Fisher Scoring iterations: 6
t7 <- tbl_regression(modelo7, exponentiate = TRUE)
t7
| Characteristic |
OR |
95% CI |
p-value |
| edad |
1.01 |
0.96, 1.06 |
0.7 |
| sexo |
|
|
|
| 0 |
— |
— |
|
| 1 |
1.86 |
0.38, 10.1 |
0.4 |
| gcs_ing |
0.99 |
0.79, 1.26 |
>0.9 |
| retrascore |
1.50 |
1.08, 2.25 |
0.028 |
| iss |
1.09 |
1.03, 1.17 |
0.009 |
| apache_ii |
0.99 |
0.88, 1.11 |
0.8 |
| sofa_ingreso |
1.19 |
0.90, 1.59 |
0.2 |
#crea un modelo con la variable dependencia como dependiente
#y los valores de parámetros de analítica
modelo8 <- glm(dependiente ~ hto + ap + ttpa + gluc + urea + crea + mg +
alb + ph + hco3 + lactato,
data = tce2, family = binomial(link = "logit"))
#muestra las variables del modelo2
summary(modelo8)
##
## Call:
## glm(formula = dependiente ~ hto + ap + ttpa + gluc + urea + crea +
## mg + alb + ph + hco3 + lactato, family = binomial(link = "logit"),
## data = tce2)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.68364 -0.60170 -0.05705 0.56356 2.45989
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) 3.12797 19.40863 0.161 0.8720
## hto -0.13703 0.10951 -1.251 0.2108
## ap -0.01350 0.03373 -0.400 0.6889
## ttpa 0.18806 0.19348 0.972 0.3311
## gluc 0.02927 0.01471 1.989 0.0467 *
## urea -0.03423 0.06433 -0.532 0.5947
## crea -0.37654 2.23642 -0.168 0.8663
## mg -5.31652 2.81941 -1.886 0.0593 .
## alb 0.72814 0.79390 0.917 0.3591
## ph 0.62195 2.11288 0.294 0.7685
## hco3 -0.17642 0.15788 -1.117 0.2638
## lactato 0.39608 0.50984 0.777 0.4372
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 53.423 on 38 degrees of freedom
## Residual deviance: 28.129 on 27 degrees of freedom
## (86 observations deleted due to missingness)
## AIC: 52.129
##
## Number of Fisher Scoring iterations: 8
t8 <- tbl_regression(modelo8, exponentiate = TRUE)
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
t8
| Characteristic |
OR |
95% CI |
p-value |
| hto |
0.87 |
0.68, 1.07 |
0.2 |
| ap |
0.99 |
0.91, 1.05 |
0.7 |
| ttpa |
1.21 |
0.90, 1.85 |
0.3 |
| gluc |
1.03 |
1.01, 1.07 |
0.047 |
| urea |
0.97 |
0.83, 1.09 |
0.6 |
| crea |
0.69 |
0.01, 78.9 |
0.9 |
| mg |
0.00 |
0.00, 0.85 |
0.059 |
| alb |
2.07 |
0.47, 13.0 |
0.4 |
| ph |
1.86 |
0.42, NA |
0.8 |
| hco3 |
0.84 |
0.57, 1.11 |
0.3 |
| lactato |
1.49 |
0.56, 4.51 |
0.4 |
modelo9 <- glm(dependiente ~ edad + gluc + retrascore + gcs_ing + lactato + iss + mg, data = tce2, family = binomial(link = "logit"))
summary(modelo9)
##
## Call:
## glm(formula = dependiente ~ edad + gluc + retrascore + gcs_ing +
## lactato + iss + mg, family = binomial(link = "logit"), data = tce2)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.3965 -0.4696 -0.1862 0.1582 2.6857
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -4.258360 4.174396 -1.020 0.3077
## edad 0.010132 0.032028 0.316 0.7517
## gluc 0.005965 0.006808 0.876 0.3809
## retrascore 0.302059 0.235259 1.284 0.1992
## gcs_ing -0.176908 0.169319 -1.045 0.2961
## lactato 0.682520 0.490276 1.392 0.1639
## iss 0.078655 0.045103 1.744 0.0812 .
## mg -0.677317 1.595467 -0.425 0.6712
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 85.338 on 65 degrees of freedom
## Residual deviance: 38.409 on 58 degrees of freedom
## (59 observations deleted due to missingness)
## AIC: 54.409
##
## Number of Fisher Scoring iterations: 6
t9 <- tbl_regression(modelo9, exponentiate = TRUE)
## Warning: glm.fit: fitted probabilities numerically 0 or 1 occurred
t9
| Characteristic |
OR |
95% CI |
p-value |
| edad |
1.01 |
0.95, 1.08 |
0.8 |
| gluc |
1.01 |
0.99, 1.02 |
0.4 |
| retrascore |
1.35 |
0.90, 2.29 |
0.2 |
| gcs_ing |
0.84 |
0.59, 1.17 |
0.3 |
| lactato |
1.98 |
0.81, 5.74 |
0.2 |
| iss |
1.08 |
1.00, 1.20 |
0.081 |
| mg |
0.51 |
0.02, 10.4 |
0.7 |
modelo10 <- glm(dependiente ~ edad + gluc + gcs_ing + lactato + crea +iss, data = tce2, family = binomial(link = "logit"))
summary(modelo10)
##
## Call:
## glm(formula = dependiente ~ edad + gluc + gcs_ing + lactato +
## crea + iss, family = binomial(link = "logit"), data = tce2)
##
## Deviance Residuals:
## Min 1Q Median 3Q Max
## -1.6254 -0.5019 -0.2472 0.3028 2.6808
##
## Coefficients:
## Estimate Std. Error z value Pr(>|z|)
## (Intercept) -4.006231 1.836002 -2.182 0.029107 *
## edad 0.041874 0.017371 2.411 0.015925 *
## gluc 0.006490 0.005633 1.152 0.249245
## gcs_ing -0.257528 0.078116 -3.297 0.000978 ***
## lactato 0.332305 0.242427 1.371 0.170456
## crea -0.885397 1.406161 -0.630 0.528920
## iss 0.101020 0.031593 3.198 0.001386 **
## ---
## Signif. codes: 0 '***' 0.001 '**' 0.01 '*' 0.05 '.' 0.1 ' ' 1
##
## (Dispersion parameter for binomial family taken to be 1)
##
## Null deviance: 127.423 on 104 degrees of freedom
## Residual deviance: 68.855 on 98 degrees of freedom
## (20 observations deleted due to missingness)
## AIC: 82.855
##
## Number of Fisher Scoring iterations: 6
t10 <- tbl_regression(modelo10, exponentiate = TRUE)
t10
| Characteristic |
OR |
95% CI |
p-value |
| edad |
1.04 |
1.01, 1.08 |
0.016 |
| gluc |
1.01 |
1.00, 1.02 |
0.2 |
| gcs_ing |
0.77 |
0.65, 0.89 |
<0.001 |
| lactato |
1.39 |
0.89, 2.32 |
0.2 |
| crea |
0.41 |
0.02, 6.59 |
0.5 |
| iss |
1.11 |
1.04, 1.18 |
0.001 |
#el mg sigue actuando como factor de confusión, pero la variación de la OR no es muy grande, así que se puede considerar no incluirlo en el modelo
tbl_merge(
tbls = list(t7, t8, t9, t10),
tab_spanner = c("**M7**", "**M8**", "**M9**", "**M10**")
)
| Characteristic |
M7
|
M8
|
M9
|
M10
|
| OR |
95% CI |
p-value |
OR |
95% CI |
p-value |
OR |
95% CI |
p-value |
OR |
95% CI |
p-value |
| edad |
1.01 |
0.96, 1.06 |
0.7 |
|
|
|
1.01 |
0.95, 1.08 |
0.8 |
1.04 |
1.01, 1.08 |
0.016 |
| sexo |
|
|
|
|
|
|
|
|
|
|
|
|
| 0 |
— |
— |
|
|
|
|
|
|
|
|
|
|
| 1 |
1.86 |
0.38, 10.1 |
0.4 |
|
|
|
|
|
|
|
|
|
| gcs_ing |
0.99 |
0.79, 1.26 |
>0.9 |
|
|
|
0.84 |
0.59, 1.17 |
0.3 |
0.77 |
0.65, 0.89 |
<0.001 |
| retrascore |
1.50 |
1.08, 2.25 |
0.028 |
|
|
|
1.35 |
0.90, 2.29 |
0.2 |
|
|
|
| iss |
1.09 |
1.03, 1.17 |
0.009 |
|
|
|
1.08 |
1.00, 1.20 |
0.081 |
1.11 |
1.04, 1.18 |
0.001 |
| apache_ii |
0.99 |
0.88, 1.11 |
0.8 |
|
|
|
|
|
|
|
|
|
| sofa_ingreso |
1.19 |
0.90, 1.59 |
0.2 |
|
|
|
|
|
|
|
|
|
| hto |
|
|
|
0.87 |
0.68, 1.07 |
0.2 |
|
|
|
|
|
|
| ap |
|
|
|
0.99 |
0.91, 1.05 |
0.7 |
|
|
|
|
|
|
| ttpa |
|
|
|
1.21 |
0.90, 1.85 |
0.3 |
|
|
|
|
|
|
| gluc |
|
|
|
1.03 |
1.01, 1.07 |
0.047 |
1.01 |
0.99, 1.02 |
0.4 |
1.01 |
1.00, 1.02 |
0.2 |
| urea |
|
|
|
0.97 |
0.83, 1.09 |
0.6 |
|
|
|
|
|
|
| crea |
|
|
|
0.69 |
0.01, 78.9 |
0.9 |
|
|
|
0.41 |
0.02, 6.59 |
0.5 |
| mg |
|
|
|
0.00 |
0.00, 0.85 |
0.059 |
0.51 |
0.02, 10.4 |
0.7 |
|
|
|
| alb |
|
|
|
2.07 |
0.47, 13.0 |
0.4 |
|
|
|
|
|
|
| ph |
|
|
|
1.86 |
0.42, NA |
0.8 |
|
|
|
|
|
|
| hco3 |
|
|
|
0.84 |
0.57, 1.11 |
0.3 |
|
|
|
|
|
|
| lactato |
|
|
|
1.49 |
0.56, 4.51 |
0.4 |
1.98 |
0.81, 5.74 |
0.2 |
1.39 |
0.89, 2.32 |
0.2 |
#compara el rendimiento de los modelos del 1 al 6, aquellos relacionados con la mortalidad
library(easystats)
## Warning: package 'easystats' was built under R version 4.2.3
## # Attaching packages: easystats 0.7.0 (red = needs update)
## ✖ bayestestR 0.13.1 ✔ correlation 0.8.4
## ✖ datawizard 0.9.0 ✖ effectsize 0.8.6
## ✖ insight 0.19.7 ✖ modelbased 0.8.6
## ✖ performance 0.10.8 ✖ parameters 0.21.3
## ✔ report 0.5.8 ✖ see 0.8.1
##
## Restart the R-Session and update packages with `easystats::easystats_update()`.
compare_performance(modelo1, modelo2, modelo3, modelo4, modelo5, modelo6)
## When comparing models, please note that probably not all models were fit
## from same data.
## # Comparison of Model Performance Indices
##
## Name | Model | AIC (weights) | AICc (weights) | BIC (weights) | Tjur's R2 | RMSE | Sigma | Log_loss | Score_log | Score_spherical | PCP
## ---------------------------------------------------------------------------------------------------------------------------------------------
## modelo1 | glm | 47.0 (0.001) | 48.4 (0.002) | 69.1 (<.001) | 0.723 | 0.205 | 0.534 | 0.133 | -10.887 | 0.077 | 0.918
## modelo2 | glm | 45.8 (0.002) | 57.8 (<.001) | 65.7 (<.001) | 0.588 | 0.267 | 0.898 | 0.279 | -4.061 | 0.119 | 0.843
## modelo3 | glm | 43.2 (0.008) | 52.3 (<.001) | 72.7 (<.001) | 0.755 | 0.200 | 0.569 | 0.125 | -7.871 | 0.108 | 0.923
## modelo4 | glm | 40.8 (0.025) | 41.8 (0.042) | 51.9 (0.186) | 0.591 | 0.268 | 0.699 | 0.226 | -7.829 | 0.093 | 0.859
## modelo5 | glm | 38.9 (0.065) | 43.0 (0.023) | 60.6 (0.002) | 0.747 | 0.205 | 0.586 | 0.145 | -11.814 | 0.101 | 0.914
## modelo6 | glm | 33.6 (0.900) | 35.6 (0.934) | 48.9 (0.812) | 0.757 | 0.191 | 0.577 | 0.149 | -9.624 | 0.101 | 0.919
#según esto, el mejor modelo es el 5
compare_performance(modelo7, modelo8, modelo9, modelo10)
## When comparing models, please note that probably not all models were fit
## from same data.
## # Comparison of Model Performance Indices
##
## Name | Model | AIC (weights) | AICc (weights) | BIC (weights) | Tjur's R2 | RMSE | Sigma | Log_loss | Score_log | Score_spherical | PCP
## ----------------------------------------------------------------------------------------------------------------------------------------------
## modelo7 | glm | 82.3 (<.001) | 83.7 (<.001) | 104.4 (<.001) | 0.589 | 0.275 | 0.780 | 0.284 | -21.027 | 0.058 | 0.837
## modelo8 | glm | 52.1 (0.758) | 64.1 (0.027) | 72.1 (0.479) | 0.548 | 0.327 | 1.021 | 0.361 | -18.200 | 0.081 | 0.778
## modelo9 | glm | 54.4 (0.242) | 56.9 (0.973) | 71.9 (0.521) | 0.606 | 0.300 | 0.814 | 0.291 | -26.380 | 0.072 | 0.821
## modelo10 | glm | 82.9 (<.001) | 84.0 (<.001) | 101.4 (<.001) | 0.523 | 0.313 | 0.838 | 0.328 | -18.819 | 0.056 | 0.802
#según esto, el mejor modelo es el 10
#carga el paquete pROC
library(pROC)
## Type 'citation("pROC")' for a citation.
##
## Attaching package: 'pROC'
## The following object is masked from 'package:parameters':
##
## ci
## The following objects are masked from 'package:bayestestR':
##
## auc, ci
## The following objects are masked from 'package:stats':
##
## cov, smooth, var
modelo10 <- glm(dependiente ~ edad + gluc + gcs_ing + lactato + crea +iss, data = tce2, family = binomial(link = "logit"), na.action = na.exclude)
# Predecir las probabilidades
probabilidades <- predict(modelo10, type = "response")
# Calcular el AUC
auc <- roc(dependiente ~ probabilidades, data = tce2)
## Setting levels: control = 0, case = 1
## Setting direction: controls < cases
auc
##
## Call:
## roc.formula(formula = dependiente ~ probabilidades, data = tce2)
##
## Data: probabilidades in 74 controls (dependiente 0) < 31 cases (dependiente 1).
## Area under the curve: 0.9024
ci.auc(auc)
## 95% CI: 0.8311-0.9737 (DeLong)
plot(auc)
Estudio sin los pacientes con LTSV
En este apartado se va a realizar un estudio sin los pacientes con
LTSV, ya que estos pacientes pueden estar afectando a la validez del
modelo predictivo. Aún así, hay que tener en cuenta que se tratan de 14
desenlaces combinados (mortalidad y dependencia) y que son muy pocos
para que el análisis tenga la potencia necesaria. Probablemente esto se
vea reflejado en la pérdida de significación estadística de algunas
variables.
# Vemos las diferencias en las variables seleccionadas en función de si LTSV o no
tce2 %>%
tbl_summary(
include = c(edad, gluc, gcs_ing, lactato, crea, iss),
by = ltsv,
statistic = list(
all_continuous() ~ "{mean} ({sd}) {median} ({p25}, {p75})",
all_categorical() ~ "{n} / {N} ({p}%)"
),
digits = list(
all_continuous() ~ 2,
all_categorical() ~ 1
)
) %>%
bold_labels() %>%
add_difference()
## 1 observations missing `ltsv` have been removed. To include these observations, use `forcats::fct_na_value_to_level()` on `ltsv` column before passing to `tbl_summary()`.
| Characteristic |
0, N = 103 |
1, N = 21 |
Difference |
95% CI |
p-value |
| edad |
51.37 (20.58) 53.00 (35.50, 68.00) |
72.19 (15.75) 77.00 (70.00, 82.00) |
-21 |
-29, -13 |
<0.001 |
| gluc |
145.30 (43.21) 139.00 (118.50, 154.00) |
202.32 (75.00) 200.00 (152.00, 224.00) |
-57 |
-94, -20 |
0.004 |
| Unknown |
4 |
2 |
|
|
|
| gcs_ing |
12.14 (3.79) 14.00 (9.00, 15.00) |
6.38 (4.44) 3.00 (3.00, 8.00) |
5.8 |
3.6, 7.9 |
<0.001 |
| lactato |
2.11 (1.18) 1.80 (1.30, 2.70) |
3.54 (2.97) 3.00 (1.55, 4.20) |
-1.4 |
-2.9, 0.02 |
0.053 |
| Unknown |
9 |
2 |
|
|
|
| crea |
0.86 (0.27) 0.80 (0.72, 0.97) |
1.11 (0.39) 1.00 (0.83, 1.42) |
-0.25 |
-0.44, -0.05 |
0.015 |
| Unknown |
1 |
2 |
|
|
|
| iss |
19.07 (10.74) 17.00 (13.00, 25.00) |
29.86 (9.25) 25.00 (25.00, 34.00) |
-11 |
-15, -6.1 |
<0.001 |
# Excluyo los pacientes con LTSV == 1
tce3 <- tce2 %>%
filter(ltsv == 0)
# Vuelvo a ajustar el modelo
modelo11 <- glm(dependiente ~ edad + gluc + gcs_ing + lactato + crea +iss , data = tce3, family = binomial(link = "logit"), na.action = na.exclude)
t11 <- tbl_regression(modelo11, exponentiate = TRUE)
## Warning in tcm * w: longer object length is not a multiple of shorter object
## length
## Warning in tcm * y * w: longer object length is not a multiple of shorter
## object length
## Warning in y * w: longer object length is not a multiple of shorter object
## length
t11
| Characteristic |
OR |
95% CI |
p-value |
| edad |
1.02 |
0.99, 1.06 |
0.3 |
| gluc |
1.01 |
0.99, 1.02 |
0.5 |
| gcs_ing |
0.81 |
0.67, 0.96 |
0.017 |
| lactato |
1.59 |
0.88, 3.02 |
0.13 |
| crea |
0.11 |
0.00, 5.17 |
0.3 |
| iss |
1.09 |
1.02, 1.17 |
0.010 |
# Predecir las probabilidades
probabilidades <- predict(modelo11, type = "response")
# Calcular el AUC
auc <- roc(dependiente ~ probabilidades, data = tce3)
## Setting levels: control = 0, case = 1
## Setting direction: controls < cases
auc
##
## Call:
## roc.formula(formula = dependiente ~ probabilidades, data = tce3)
##
## Data: probabilidades in 74 controls (dependiente 0) < 14 cases (dependiente 1).
## Area under the curve: 0.8388
ci.auc(auc)
## 95% CI: 0.7194-0.9582 (DeLong)
plot(auc)
Modelos incluyendo las alteraciones pupilares
Se juntan los grupos 1 y 2 de las alteraciones pupilares, ya que son
muy pocos pacientes. El modelo 12 incluye los pacientes con LTSV El
modelo 13 excluye los pacientes con LTSV
#recodifica la variable pupila_ing creando una nueva variable pupila_ing_2. Si pupila_ing es 0, pupila_ing_2 es 0 y si es 1 o 2, es 1
tce2 <- tce2 %>%
mutate(pupila_ing_2 = ifelse(pupila_ing == 0, 0, 1))
# Vemos las diferencias en las variables seleccionadas en función de si LTSV o no
tce2 %>%
tbl_summary(
include = c(edad, gluc, gcs_ing, lactato, crea, iss, pupila_ing, pupila_ing_2),
by = ltsv,
statistic = list(
all_continuous() ~ "{mean} ({sd}) {median} ({p25}, {p75})",
all_categorical() ~ "{n} / {N} ({p}%)"
),
digits = list(
all_continuous() ~ 2,
all_categorical() ~ 1
)
) %>%
bold_labels() %>%
add_difference()
## 1 observations missing `ltsv` have been removed. To include these observations, use `forcats::fct_na_value_to_level()` on `ltsv` column before passing to `tbl_summary()`.
## Warning for variable 'pupila_ing_2':
## simpleWarning in stats::prop.test(df_counts$n, df_counts$N, conf.level = 0.95): Chi-squared approximation may be incorrect
| Characteristic |
0, N = 103 |
1, N = 21 |
Difference |
95% CI |
p-value |
| edad |
51.37 (20.58) 53.00 (35.50, 68.00) |
72.19 (15.75) 77.00 (70.00, 82.00) |
-21 |
-29, -13 |
<0.001 |
| gluc |
145.30 (43.21) 139.00 (118.50, 154.00) |
202.32 (75.00) 200.00 (152.00, 224.00) |
-57 |
-94, -20 |
0.004 |
| Unknown |
4 |
2 |
|
|
|
| gcs_ing |
12.14 (3.79) 14.00 (9.00, 15.00) |
6.38 (4.44) 3.00 (3.00, 8.00) |
5.8 |
3.6, 7.9 |
<0.001 |
| lactato |
2.11 (1.18) 1.80 (1.30, 2.70) |
3.54 (2.97) 3.00 (1.55, 4.20) |
-1.4 |
-2.9, 0.02 |
0.053 |
| Unknown |
9 |
2 |
|
|
|
| crea |
0.86 (0.27) 0.80 (0.72, 0.97) |
1.11 (0.39) 1.00 (0.83, 1.42) |
-0.25 |
-0.44, -0.05 |
0.015 |
| Unknown |
1 |
2 |
|
|
|
| iss |
19.07 (10.74) 17.00 (13.00, 25.00) |
29.86 (9.25) 25.00 (25.00, 34.00) |
-11 |
-15, -6.1 |
<0.001 |
| pupila_ing |
|
|
0.93 |
0.45, 1.4 |
|
| 0 |
92.0 / 103.0 (89.3%) |
11.0 / 21.0 (52.4%) |
|
|
|
| 1 |
7.0 / 103.0 (6.8%) |
3.0 / 21.0 (14.3%) |
|
|
|
| 2 |
4.0 / 103.0 (3.9%) |
7.0 / 21.0 (33.3%) |
|
|
|
| pupila_ing_2 |
11.0 / 103.0 (10.7%) |
10.0 / 21.0 (47.6%) |
-37% |
-62%, -12% |
<0.001 |
# Vuelvo a ajustar el modelo incluyendo la variable pupila_ing_2 y los pacientes con LTSV
modelo12 <- glm(dependiente ~ edad + gluc + gcs_ing + lactato + crea +iss + pupila_ing_2, data = tce2, family = binomial(link = "logit"), na.action = na.exclude)
t12 <- tbl_regression(modelo12, exponentiate = TRUE)
## Warning in tcm * w: longer object length is not a multiple of shorter object
## length
## Warning in tcm * y * w: longer object length is not a multiple of shorter
## object length
## Warning in y * w: longer object length is not a multiple of shorter object
## length
t12
| Characteristic |
OR |
95% CI |
p-value |
| edad |
1.04 |
1.01, 1.08 |
0.029 |
| gluc |
1.01 |
1.00, 1.02 |
0.2 |
| gcs_ing |
0.81 |
0.68, 0.94 |
0.009 |
| lactato |
1.40 |
0.87, 2.37 |
0.2 |
| crea |
0.40 |
0.02, 6.79 |
0.5 |
| iss |
1.10 |
1.03, 1.17 |
0.004 |
| pupila_ing_2 |
5.49 |
0.63, 67.6 |
0.14 |
# Predecir las probabilidades
probabilidades <- predict(modelo12, type = "response")
# Calcular el AUC
auc <- roc(dependiente ~ probabilidades, data = tce2)
## Setting levels: control = 0, case = 1
## Setting direction: controls < cases
auc
##
## Call:
## roc.formula(formula = dependiente ~ probabilidades, data = tce2)
##
## Data: probabilidades in 74 controls (dependiente 0) < 31 cases (dependiente 1).
## Area under the curve: 0.9002
ci.auc(auc)
## 95% CI: 0.829-0.9713 (DeLong)
plot(auc)
# Excluyo los pacientes con LTSV == 1
tce3 <- tce2 %>%
filter(ltsv == 0)
# Vuelvo a ajustar el modelo
modelo13 <- glm(dependiente ~ edad + gluc + gcs_ing + lactato + crea +iss + pupila_ing_2, data = tce3, family = binomial(link = "logit"), na.action = na.exclude)
t13 <- tbl_regression(modelo13, exponentiate = TRUE)
## Warning in tcm * w: longer object length is not a multiple of shorter object
## length
## Warning in tcm * y * w: longer object length is not a multiple of shorter
## object length
## Warning in y * w: longer object length is not a multiple of shorter object
## length
t13
| Characteristic |
OR |
95% CI |
p-value |
| edad |
1.02 |
0.98, 1.06 |
0.4 |
| gluc |
1.00 |
0.99, 1.02 |
0.6 |
| gcs_ing |
0.85 |
0.69, 1.02 |
0.084 |
| lactato |
1.68 |
0.90, 3.38 |
0.12 |
| crea |
0.10 |
0.00, 5.71 |
0.3 |
| iss |
1.08 |
1.01, 1.15 |
0.029 |
| pupila_ing_2 |
6.81 |
0.70, 79.7 |
0.10 |
# Predecir las probabilidades
probabilidades <- predict(modelo13, type = "response")
# Calcular el AUC
auc <- roc(dependiente ~ probabilidades, data = tce3)
## Setting levels: control = 0, case = 1
## Setting direction: controls < cases
auc
##
## Call:
## roc.formula(formula = dependiente ~ probabilidades, data = tce3)
##
## Data: probabilidades in 74 controls (dependiente 0) < 14 cases (dependiente 1).
## Area under the curve: 0.8282
ci.auc(auc)
## 95% CI: 0.7027-0.9537 (DeLong)
plot(auc)
