![]() ![]() ML improves death prediction by identifying separate characteristics in older Asian populations. In a multi-ethnic population, DL outperformed the TIMI risk score in classifying elderly STEMI patients. All ML feature selection algorithms identify age, fasting blood glucose, heart rate, Killip class, oral hypoglycemic agent, systolic blood pressure, and total cholesterol as common predictors of mortality in the elderly. TIMI predicts 18.4% higher mortality than the DL algorithm (44.7%). The TIMI score underestimates mortality in the elderly. DL built from ML features (AUC ranging from 0.93 to 0.95) outscored DL built from all features (AUC 0.93). The DL and ML model constructed using ML feature selection outperforms the conventional risk scoring score, TIMI (AUC 0.75). The main performance metric was the area under the receiver operating characteristic curve (AUC). The TIMI score was used to predict mortality using DL and feature selection methods from ML algorithms. 50 variables helped in establishing the in-hospital death prediction model. Malaysia's National Cardiovascular Disease Registry comprises an ethnically diverse Asian elderly population (3991 patients). We used DL and ML to predict in-hospital mortality in Asian elderly STEMI patients and compared it to a conventional risk score for myocardial infraction outcomes. ![]() Mean RR and SDNN show a perfect linear relationship (r = 0.657, p < 0.001).Ĭonclusion: It was observed that depressed heart rate variability and increased 24-hours mean heart rate correlates with high TIMI risk score after acute ST-elevation myocardial infarction.Limited research has been conducted in Asian elderly patients (aged 65 years and above) for in-hospital mortality prediction after an ST-segment elevation myocardial infarction (STEMI) using Deep Learning (DL) and Machine Learning (ML). High TIMI risk score also showed a negative correlation with mean RR interval (r=-574, p<0.001). There was a significant correlation between depressed SDNN and high TIMI risk score (r=.893, p=.001). Among the TIMI risk groups SDNN values were 120.0 ± 19, 871.0 ± 20.5 and 40.9 ± 6.4 msec in mild, moderate and high risk group respectively(p=<0.001). % between 0 – 2 and 24% 8 or more than 8.SDNN and RR interval stratified by TIMI risk score demonstrates that both the variables decreases significantly with the increase of TIMI risk score. Stratification of subjects by TIMI risk score shows that nearly 60% had risk score in the range of 3 – 7, 17. Results : Ninety one patients (mean age 53.9 ± 10.8 years), 86.7% were males and 14( mean age 59.8 ± 8.8 years), 13.3% were female. SDNN for HRV and mean RR interval for mean heart rate were recorded. ![]() TIMI risk score were calculated and each patient under went 24hour Holter monitoring. Total 105 STEMI patients were included in the study. Methods: This study was conducted in NICVD (National Institute of Cardiovascular Diseases), Dhaka, from July 2008 to June 2009. Correlation among these factors has not been studied thoroughly. TIMI risk score, Heart rate variability, STEMI Abstractīackground: Thrombolysis In Myocardial Infarction (TIMI) risk score, heart rate variability (HRV) and 24hour mean heart rate all are important predictor of prognosis after ST segment elevation myocardial infarction(STEMI). ![]()
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