Myocardial work predicts rehospitalization after acute myocardial infarction
minci4
https://rpubs.com/alex_istrate/
1 INDRODUCTION
Myocardial deformation imaging using two-dimensional speckle-tracking echocardiography (STE) has become a very useful technique for the assessment of left ventricular (LV) function after acute myocardial infarction (AMI). However, it has been showed that changes in afterload could alter strain calculation, leading to misinterpretation of the results.
Myocardial work (MW) is a new parameter that integrates both strain and afterload, through dynamic non-invasive LV pressure measurements. MW has showed superiority compared to LV global longitudinal strain (GLS) for coronary artery disease prediction, but is not yet validated as a prognostic parameter for long-term risk assessment after AMI.
2 PURPOSE
The aim of this study is to see whether MW could stand as a prognostic marker for patients with coronary artery disease and if it is superior to GLS for short- and long-term risk assessment.
3 METHODS
Forty-five patients with ST-elevation and non-ST-elevation MI, regardless of interested territory, admitted in our Cardiology Department between 1st and 31st of August were included. Patients with history of coronary artery disease, heart failure with reduced ejection fraction or severe hypertension were not included. We evaluated GLS and global MW index (GWI) 3-5 days after percutaneous revascularization. GWI was calculated as the product of strain x systolic blood pressure. Patients were divided in two groups: Group 1 – patients that presented rehospitalization for cardiac decompensation, including new coronary event or heart failure symptoms and Group 2 – patients without rehospitalization, at 4-month follow-up. We then compared GLS and GWI between the two groups and the relation between GLS and GWI in group 1.
4 RESULTS
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Describe baza_de_date (tbl_df, tbl, data.frame):
data frame: 45 obs. of 7 variables
43 complete cases (95.6%)
Nr ColName Class NAs Levels Label
1 Diagnosis factor . (2): 1-STEMI, Diagnosis
2-NSTEMI
2 Age (years) numeric . Age (years)
3 Sex factor . (2): 1-F, 2-M Sex
4 Culprit vessel factor 2 (4.4%) (3): 1-LAD, Culprit vessel
2-RCA, 3-LCX
5 GLS-2d numeric . GLS-2d
6 GWI numeric . Global
myocardial
work index
7 Rehospitalization factor . (2): 1-yes, Rehospitalizati...
2-no
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1 - Diagnosis (factor - dichotomous) :
Diagnosis
length n NAs unique
45 45 0 2
100.0% 0.0%
freq perc lci.95 uci.95'
STEMI 31 68.9% 54.3% 80.5%
NSTEMI 14 31.1% 19.5% 45.7%
' 95%-CI Wilson
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2 - Age (years) (numeric) :
Age (years)
length n NAs unique 0s mean meanCI
45 45 0 31 0 64.29 59.99
100.0% 0.0% 0.0% 68.59
.05 .10 .25 median .75 .90 .95
43.20 46.00 54.00 64.00 78.00 83.20 84.80
range sd vcoef mad IQR skew kurt
58.00 14.32 0.22 16.31 24.00 -0.01 -1.01
lowest : 35.0, 40.0, 43.0, 44.0, 46.0 (3)
highest: 82.0, 84.0 (2), 85.0, 86.0, 93.0
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3 - Sex (factor - dichotomous) :
Sex
length n NAs unique
45 45 0 2
100.0% 0.0%
freq perc lci.95 uci.95'
F 18 40.0% 27.0% 54.5%
M 27 60.0% 45.5% 73.0%
' 95%-CI Wilson
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4 - Culprit vessel (factor) :
Culprit vessel
length n NAs unique levels dupes
45 43 2 3 3 y
95.6% 4.4%
level freq perc cumfreq cumperc
1 LAD 17 39.5% 17 39.5%
2 RCA 17 39.5% 34 79.1%
3 LCX 9 20.9% 43 100.0%
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5 - GLS-2d (numeric) :
GLS-2d
length n NAs unique 0s mean meanCI
45 45 0 36 0 -11.31 -12.21
100.0% 0.0% 0.0% -10.41
.05 .10 .25 median .75 .90 .95
-16.00 -15.44 -13.60 -11.00 -9.40 -7.88 -7.12
range sd vcoef mad IQR skew kurt
11.90 3.00 -0.26 3.11 4.20 0.07 -0.79
lowest : -16.80, -16.10, -16.0 (2), -15.60, -15.20
highest: -7.80, -7.60, -7.0, -5.0, -4.90
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6 - GWI (numeric) :
Global myocardial work index
length n NAs unique 0s mean meanCI
45 45 0 44 0 1'099.04 1'005.32
100.0% 0.0% 0.0% 1'192.77
.05 .10 .25 median .75 .90 .95
693.40 807.40 925.00 1'036.00 1'182.00 1'560.80 1'617.00
range sd vcoef mad IQR skew kurt
1'501.00 311.96 0.28 210.53 257.00 0.59 0.15
lowest : 401.0, 628.0, 686.0, 723.0, 807.0
highest: 1'612.0, 1'613.0, 1'618.0, 1'824.0, 1'902.0
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7 - Rehospitalization (factor - dichotomous) :
Rehospitalization
length n NAs unique
45 45 0 2
100.0% 0.0%
freq perc lci.95 uci.95'
yes 8 17.8% 9.3% 31.3%
no 37 82.2% 68.7% 90.7%
' 95%-CI Wilson
Variable | Details | Total |
N= | 45 | |
Diagnosis | STEMI | 31 (68.9%) |
NSTEMI | 14 (31.1%) | |
Age (years) | M (min:max) | 64 (35:93) |
μ ±SD | 64.29 ±14.3 | |
Sex | F | 18 (40.0%) |
M | 27 (60.0%) | |
Culprit vessel | LAD | 17 (39.5%) |
RCA | 17 (39.5%) | |
LCX | 9 (20.9%) | |
GLS-2d | M (min:max) | -11 (-16.8:-4.9) |
μ ±SD | -11.31 ±3.0 | |
Global myocardial work index | M (min:max) | 1036 (401:1902) |
μ ±SD | 1099.04 ±312.0 | |
Rehospitalization | 8 (17.8%) | |
μ ±SD = Mean (standard deviation); M (min:max) = Median (min:max); | ||
Figure 1: Age distribution, at admission, colored by sex. (| mean, ¦ median).
Figure 2: Sex and Rehospitalization.
Figure 3: Diagnosis and Culprit vessel.
Variable | Details | yes | no | Total | Statistics |
Rehospitalization | 8 (17.8%) | 37 (82.2%) | 45 | ||
Diagnosis | STEMI | 5 (62.5%) | 26 (70.3%) | 31 (68.9%) | OR=0.71 [0.14, 3.48] (p=0.689) |
NSTEMI | 3 (37.5%) | 11 (29.7%) | 14 (31.1%) | ||
Age (years) | M (min:max) | 64.5 (35:93) | 64 (40:86) | 64 (35:93) | T-test: p=0.972 |
μ ±SD | 64.12 ±18.0 | 64.32 ±13.7 | 64.29 ±14.3 | ||
Sex | F | 2 (25.0%) | 16 (43.2%) | 18 (40.0%) | OR=0.44 [0.08, 2.46] (p=0.445) |
M | 6 (75.0%) | 21 (56.8%) | 27 (60.0%) | ||
Culprit vessel | LAD | 4 (50.0%) | 13 (37.1%) | 17 (39.5%) | V=0.12 (p=0.735) |
RCA | 3 (37.5%) | 14 (40.0%) | 17 (39.5%) | ||
LCX | 1 (12.5%) | 8 (22.9%) | 9 (20.9%) | ||
GLS-2d | M (min:max) | -10.3 (-13:-5) | -11.4 (-16.8:-4.9) | -11 (-16.8:-4.9) | T-test: p=0.252 |
μ ±SD | -10.20 ±2.75 | -11.55 ±3.03 | -11.31 ±3.0 | ||
Global myocardial work index | M (min:max) | 841 (401:1028) | 1117 (628:1902) | 1036 (401:1902) | T-test: p=0.002 |
μ ±SD | 801.25 ±198.8 | 1163.43 ±295.5 | 1099.04 ±312.0 | ||
OR = odds-ratio [95% CI] and p value from Fisher test); | |||||
4.1 GLS-2d & GWI
Figure 4: GLS-2d and GWI distributions. (| mean, ¦ median).
Figure 5: (◆ mean, — median).
5 CONCLUSIONS
6 References
- R Core Team (2019). R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. URL https://www.R-project.org/.