1 tabla univariante

Data Frame Summary

datis4

Dimensions: 47 x 59
Duplicates: 0
No Variable Stats / Values Freqs (% of Valid) Graph Valid Missing
1 id [numeric]
Mean (sd) : 58 (33.8)
min ≤ med ≤ max:
4 ≤ 61 ≤ 113
IQR (CV) : 62 (0.6)
 47 distinct values 47 (100.0%) 0 (0.0%)
2 plan [character]
1. DAIR
2. DAIR - DAIR
3. DAIR - DAIR - REC
4. DAIR - REC
29(61.7%)
9(19.1%)
1(2.1%)
8(17.0%)
 47 (100.0%) 0 (0.0%)
3 clasificacion [character]
1. 3
2. 3,5,6
3. 3.4
4. 3.5
29(61.7%)
1(2.1%)
8(17.0%)
9(19.1%)
 47 (100.0%) 0 (0.0%)
4 tipo_ip [character]
1. AGUDA
2. HEMATOGENA
44(93.6%)
3(6.4%)
 47 (100.0%) 0 (0.0%)
5 n_dair [numeric]
Min : 1
Mean : 1.2
Max : 2
1:37(78.7%)
2:10(21.3%)
 47 (100.0%) 0 (0.0%)
6 exito_dair1 [logical]
1. FALSE
2. TRUE
22(46.8%)
25(53.2%)
 47 (100.0%) 0 (0.0%)
7 exito_dair2 [character]
1. FALSE
2. NA
3. TRUE
9(19.1%)
37(78.7%)
1(2.1%)
 47 (100.0%) 0 (0.0%)
8 poly_exchage [character]
1. NO
2. SI
32(68.1%)
15(31.9%)
 47 (100.0%) 0 (0.0%)
9 daystodair_old [numeric]
Mean (sd) : 34.3 (21.4)
min ≤ med ≤ max:
8 ≤ 28 ≤ 88
IQR (CV) : 19.5 (0.6)
 32 distinct values 47 (100.0%) 0 (0.0%)
10 daysurgtodair [numeric]
Mean (sd) : 36.1 (20.9)
min ≤ med ≤ max:
9 ≤ 29 ≤ 88
IQR (CV) : 18.2 (0.6)
 31 distinct values 44 (93.6%) 3 (6.4%)
11 daysintodair [numeric] 1 distinct value
8:3(100.0%)
 3 (6.4%) 44 (93.6%)
12 days1to2dair [numeric]
Mean (sd) : 26.2 (26.4)
min ≤ med ≤ max:
6 ≤ 15.5 ≤ 90
IQR (CV) : 25.2 (1)
6:1(10.0%)
7:1(10.0%)
10:2(20.0%)
14:1(10.0%)
17:1(10.0%)
21:1(10.0%)
40:1(10.0%)
47:1(10.0%)
90:1(10.0%)
 10 (21.3%) 37 (78.7%)
13 follow_up [numeric]
Mean (sd) : 69.1 (34.9)
min ≤ med ≤ max:
24 ≤ 60 ≤ 135
IQR (CV) : 66.5 (0.5)
 27 distinct values 47 (100.0%) 0 (0.0%)
14 final_status [character]
1. FAIL
2. FREE
17(36.2%)
30(63.8%)
 47 (100.0%) 0 (0.0%)
15 lfinal_status [character]
1. FAIL RECURRENT
2. FAIL RESECTION
3. FAIL SAT
4. FREE
7(14.9%)
2(4.3%)
8(17.0%)
30(63.8%)
 47 (100.0%) 0 (0.0%)
16 procedimiento [character]
1. PTC
2. RPTC
32(68.1%)
15(31.9%)
 47 (100.0%) 0 (0.0%)
17 indicacion [character]
1. Artrosis
2. Other
27(57.4%)
20(42.6%)
 47 (100.0%) 0 (0.0%)
18 cementada [character]
1. Cementado
2. NO
5(10.6%)
42(89.4%)
 47 (100.0%) 0 (0.0%)
19 edad [numeric]
Mean (sd) : 66.6 (14.1)
min ≤ med ≤ max:
16 ≤ 70 ≤ 84
IQR (CV) : 21 (0.2)
 28 distinct values 47 (100.0%) 0 (0.0%)
20 sexo [character]
1. H
2. M
35(74.5%)
12(25.5%)
 47 (100.0%) 0 (0.0%)
21 asa [character]
1. I
2. II
3. III
4. IV
5(10.6%)
19(40.4%)
21(44.7%)
2(4.3%)
 47 (100.0%) 0 (0.0%)
22 charlson [numeric]
Mean (sd) : 4.1 (2.2)
min ≤ med ≤ max:
0 ≤ 4 ≤ 9
IQR (CV) : 2.5 (0.5)
0:3(6.4%)
1:3(6.4%)
2:6(12.8%)
3:4(8.5%)
4:13(27.7%)
5:7(14.9%)
6:4(8.5%)
7:4(8.5%)
8:2(4.3%)
9:1(2.1%)
 47 (100.0%) 0 (0.0%)
23 charlson4om [logical]
1. FALSE
2. TRUE
16(34.0%)
31(66.0%)
 47 (100.0%) 0 (0.0%)
24 ecv [logical]
1. FALSE
2. TRUE
30(63.8%)
17(36.2%)
 47 (100.0%) 0 (0.0%)
25 ete_previa [logical]
1. FALSE
2. TRUE
43(91.5%)
4(8.5%)
 47 (100.0%) 0 (0.0%)
26 neumopatia [logical]
1. FALSE
2. TRUE
40(85.1%)
7(14.9%)
 47 (100.0%) 0 (0.0%)
27 hta [logical]
1. FALSE
2. TRUE
23(48.9%)
24(51.1%)
 47 (100.0%) 0 (0.0%)
28 psiquiatrica [logical]
1. FALSE
2. TRUE
43(91.5%)
4(8.5%)
 47 (100.0%) 0 (0.0%)
29 diabetes [logical]
1. FALSE
2. TRUE
38(80.9%)
9(19.1%)
 47 (100.0%) 0 (0.0%)
30 imc [numeric]
Mean (sd) : 29.6 (6.5)
min ≤ med ≤ max:
19 ≤ 29 ≤ 51
IQR (CV) : 7.5 (0.2)
 21 distinct values 47 (100.0%) 0 (0.0%)
31 gastropatía [logical]
1. FALSE
2. TRUE
38(80.9%)
9(19.1%)
 47 (100.0%) 0 (0.0%)
32 inmunodepresion [logical]
1. FALSE
2. TRUE
43(91.5%)
4(8.5%)
 47 (100.0%) 0 (0.0%)
33 malignidad [logical]
1. FALSE
2. TRUE
35(74.5%)
12(25.5%)
 47 (100.0%) 0 (0.0%)
34 renopatia [logical]
1. FALSE
2. TRUE
41(87.2%)
6(12.8%)
 47 (100.0%) 0 (0.0%)
35 reumatismo [logical]
1. FALSE
2. TRUE
35(74.5%)
12(25.5%)
 47 (100.0%) 0 (0.0%)
36 hepatopatia [logical]
1. FALSE
2. TRUE
45(95.7%)
2(4.3%)
 47 (100.0%) 0 (0.0%)
37 antiagregacion [logical]
1. FALSE
2. TRUE
35(74.5%)
12(25.5%)
 47 (100.0%) 0 (0.0%)
38 coagulopatía [logical]
1. FALSE
2. TRUE
43(91.5%)
4(8.5%)
 47 (100.0%) 0 (0.0%)
39 tabaco [logical]
1. FALSE
2. TRUE
23(48.9%)
24(51.1%)
 47 (100.0%) 0 (0.0%)
40 alcohol [logical]
1. FALSE
2. TRUE
37(78.7%)
10(21.3%)
 47 (100.0%) 0 (0.0%)
41 seroma [logical]
1. FALSE
2. TRUE
14(29.8%)
33(70.2%)
 47 (100.0%) 0 (0.0%)
42 hematoma [logical]
1. FALSE
2. TRUE
29(61.7%)
18(38.3%)
 47 (100.0%) 0 (0.0%)
43 skin_infection [logical]
1. FALSE
2. TRUE
28(59.6%)
19(40.4%)
 47 (100.0%) 0 (0.0%)
44 fistula [logical]
1. FALSE
2. TRUE
27(57.4%)
20(42.6%)
 47 (100.0%) 0 (0.0%)
45 fiebre [logical]
1. FALSE
2. TRUE
33(70.2%)
14(29.8%)
 47 (100.0%) 0 (0.0%)
46 hb_preop [numeric]
Mean (sd) : 13.9 (1.5)
min ≤ med ≤ max:
10.3 ≤ 14.2 ≤ 16.2
IQR (CV) : 2.2 (0.1)
 32 distinct values 47 (100.0%) 0 (0.0%)
47 pcr [numeric]
Mean (sd) : 10.1 (10.4)
min ≤ med ≤ max:
0.2 ≤ 6.6 ≤ 41.7
IQR (CV) : 11.2 (1)
 42 distinct values 47 (100.0%) 0 (0.0%)
48 wbc_serum [numeric]
Mean (sd) : 8.6 (3.1)
min ≤ med ≤ max:
3.2 ≤ 7.3 ≤ 14.8
IQR (CV) : 4.5 (0.4)
 36 distinct values 47 (100.0%) 0 (0.0%)
49 hemocultivo+ [logical]
1. FALSE
2. TRUE
44(93.6%)
3(6.4%)
 47 (100.0%) 0 (0.0%)
50 microorganism [character]
1. CoNS
2. SASM
3. Culture negative
4. Polymicrobial
5. S.lugdunensis
6. Corynebacterium spp.
7. E. faecalis
8. L. monocytogenes
9. P. acnes
10. P. aeruginosa
[ 3 others ]
13(27.7%)
13(27.7%)
5(10.6%)
5(10.6%)
3(6.4%)
1(2.1%)
1(2.1%)
1(2.1%)
1(2.1%)
1(2.1%)
3(6.4%)
 47 (100.0%) 0 (0.0%)
51 cultivo+porc [numeric]
Mean (sd) : 62.6 (38.4)
min ≤ med ≤ max:
0 ≤ 66 ≤ 100
IQR (CV) : 67 (0.6)
 15 distinct values 47 (100.0%) 0 (0.0%)
52 cultivo+100 [logical]
1. FALSE
2. TRUE
27(57.4%)
20(42.6%)
 47 (100.0%) 0 (0.0%)
53 germen2dair [character]
1. Culture negative
2. E. faecalis
3. NA
4. Polymicrobial
5. S. lugdunensis
6. SASM
7. Serratia marcesens
5(10.6%)
1(2.1%)
37(78.7%)
1(2.1%)
1(2.1%)
1(2.1%)
1(2.1%)
 47 (100.0%) 0 (0.0%)
54 inf2dair [character]
1. FALSE
2. NA
9(19.1%)
38(80.9%)
 47 (100.0%) 0 (0.0%)
55 exitod [logical]
1. FALSE
2. TRUE
21(44.7%)
26(55.3%)
 47 (100.0%) 0 (0.0%)
56 PTC [logical]
1. FALSE
2. TRUE
15(31.9%)
32(68.1%)
 47 (100.0%) 0 (0.0%)
57 PTR [logical] 1. FALSE
47(100.0%)
 47 (100.0%) 0 (0.0%)
58 RPTC [logical]
1. FALSE
2. TRUE
32(68.1%)
15(31.9%)
 47 (100.0%) 0 (0.0%)
59 RPTR [logical] 1. FALSE
47(100.0%)
 47 (100.0%) 0 (0.0%)

Generated by summarytools 1.0.1 (R version 4.2.2)
2022-12-21

2 p(exito y fracaso) segun rama

2.1 recambio (2)

2.2 recambio (1)

res n est lwr.ci upr.ci
exito 4 0.8 0.28 0.99
fracaso 1 0.2 0.01 0.72

2.3 dair 1 (3)

res n est lwr.ci upr.ci
exito 48 0.57 0.46 0.68
fracaso 36 0.43 0.32 0.54

2.4 recambio (4)

res n est lwr.ci upr.ci
exito 10 0.59 0.33 0.82
fracaso 7 0.41 0.18 0.67

2.5 dair 2 (5)

res n est lwr.ci upr.ci
exito 1 0.08 0.00 0.38
fracaso 11 0.92 0.62 1.00

2.6 recambio (6)

res n est lwr.ci upr.ci
exito 0 0 0.00 0.84
fracaso 2 1 0.16 1.00

3 tabla bivariante

4 daystodair

5 days1to2dair

## Warning: Removed 72 rows containing non-finite values (`stat_bin()`).

6 status final

6.1 free

## single
kable(icbin(10,24-10))
res n est lwr.ci upr.ci
exito 10 0.42 0.22 0.63
fracaso 14 0.58 0.37 0.78 
## second
kable(icbin(0,11))
res n est lwr.ci upr.ci
exito 0 0 0.00 0.28
fracaso 11 1 0.72 1.00

6.2 SAT

## single
kable(icbin(6,24-6))
res n est lwr.ci upr.ci
exito 6 0.25 0.10 0.47
fracaso 18 0.75 0.53 0.90 
## second
kable(icbin(6,11-6))
res n est lwr.ci upr.ci
exito 6 0.55 0.23 0.83
fracaso 5 0.45 0.17 0.77

6.3 resection or fusion

## single
kable(icbin(3,24-3))
res n est lwr.ci upr.ci
exito 3 0.12 0.03 0.32
fracaso 21 0.88 0.68 0.97 
## second
kable(icbin(0,11))
res n est lwr.ci upr.ci
exito 0 0 0.00 0.28
fracaso 11 1 0.72 1.00

6.4 recurrent infection

## single
kable(icbin(5,24-5))
res n est lwr.ci upr.ci
exito 5 0.21 0.07 0.42
fracaso 19 0.79 0.58 0.93 
## second
kable(icbin(5,11-5))
res n est lwr.ci upr.ci
exito 5 0.45 0.17 0.77
fracaso 6 0.55 0.23 0.83 
pp=data.frame(res=c("exito","fracaso","exito","fracaso"), tipo=c("single","single","second","second"), n=c(10,14,0,11))

ggplot(pp, aes(x=n, color=res)) +geom_histogram(position="identity")

ggplot(pp, aes(n, fill = res)) + geom_histogram()

pp %>% ggplot(aes(x = n, y = res, color=tipo)) + geom_col()