Browsing by Author "Mpanya, Dineo"
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Item Predicting in-hospital mortality in heart failure patients using machine learning(2024) Mpanya, DineoThe age of onset and causes of heart failure differ between high-income and low-and-middle-income countries (LMIC). Heart failure patients in LMIC also experience a higher mortality rate. Innovative ways that can risk stratify heart failure patients in this region are needed. The aim of this study was to demonstrate the utility of machine learning in predicting all-cause mortality in heart failure patients hospitalised in a tertiary academic centre. Six supervised machine learning algorithms were trained to predict in-hospital all-cause mortality using data from 500 consecutive heart failure patients with a left ventricular ejection fraction (LVEF) less than 50%. The mean age was 55.2 ± 16.8 years. There were 271 (54.2%) males, and the mean LVEF was 29 ± 9.2%. The median duration of hospitalisation was 7 days (interquartile range: 4–11), and it did not differ between patients discharged alive and those who died. After a prediction window of 4 years (interquartile range: 2–6), 84 (16.8%) patients died before discharge from the hospital. The area under the receiver operating characteristic curve was 0.82, 0.78, 0.77, 0.76, 0.75, and 0.62 for random forest, logistic regression, support vector machines (SVM), extreme gradient boosting, multilayer perceptron (MLP), and decision trees, and the accuracy during the test phase was 88, 87, 86, 82, 78, and 76% for random forest, MLP, SVM, extreme gradient boosting, decision trees, and logistic regression. The support vector machines were the best performing algorithm, and furosemide, beta-blockers, spironolactone, early diastolic murmur, and a parasternal heave had a positive coefficient with the target feature, whereas coronary artery disease, potassium, oedema grade, ischaemic cardiomyopathy, and right bundle branch block on electrocardiogram had negative coefficients. Despite a small sample size, supervised machine learning algorithms successfully predicted all-cause mortality with modest accuracy. The SVM model will be externally validated using data from multiple cardiology centres in South Africa before developing a uniquely African risk prediction tool that can potentially transform heart failure managementItem The prevalence of myocardial viability as detected by 18F-Fluorodeoxyglucose positron emission tomography(2017) Mpanya, DineoBackground: Positron Emission Tomography (PET) is an imaging modality that guides the revascularization management of patients with left ventricular systolic dysfunction secondary to coronary artery disease. Segments of the myocardium demonstrating reduced perfusion and increased or preserved 18FFluorodeoxyglucose (18F-FDG) uptake are considered to be viable and thus suitable for revascularization. The aim of our study was to determine the prevalence of myocardial viability as determined by FDG-PET in our local cohort and to compare our prevalence of myocardial viability to data published elsewhere. Methods: We retrospectively reviewed 240 consecutive 99mTc-sestamibi myocardial perfusion Gated Single Photon Emission Tomography (SPECT) and 18FFDG PET reports of patients referred for evaluation of myocardial viability between January 2009 and June 2015. Results: 236 patients met the inclusion criteria. There were 194 (82.2%) males. The mean age was 59.1 (SD 11.0) years. A total of 4012 segments of the left ventricle were analyzed on the gated SPECT and reduced perfusion was noted in 1862 (46.4%) segments. Perfusion-metabolism mismatch (viable myocardium) was observed in 586 (31.5%) out of 1862 perfusion defects. The prevalence of myocardial viability in the study population was 61.4%. On the multivariate logistic regression model, aspirin intake [OR:0.37; CI:0.16-0.83; p=0.016] and hypertension [OR:0.26; CI:0.12-0.58; p=0.001] were associated with the presence of viable myocardium. Smoking was associated with the likelihood of having non-viable myocardium [OR:2.31; CI:1.01-5.29; p=0.048] Conclusion: The prevalence of myocardial viability as detected by 18F FDG PET in our local cohort is similar to prevalence rates reported in the developed world.