Why the study?
Cardiac pathologies cause significant mortality worldwide, prompting an evaluation of associations between sex, age, heart weight, and causes of cardiac death in medico-legal autopsies.
Coronary artery pathologies are the leading cause of cardiac deaths in this Sri Lankan autopsy cohort, with heart weight varying significantly by sex and age but showing limited predictive value for specific causes of death.
Local autopsy data may inform forensic cardiac death patterns; leaves open causal links pending prospective studies.
Cardiac pathologies contribute to a significant number of deaths every year worldwide. This retrospective descriptive study was to determine the associations between the sex, age, weight of the heart and the cause of cardiac death of deceased individuals who were subjected to medico-legal autopsies in a local setting. Data was collected by scrutinizing the postmortem data records available at the Department of Forensic Medicine, Faculty of Medicine, University of Peradeniya, Sri Lanka, from 1st January 2017 to 31st December 2023. Using SPSS, descriptive analyses, ANOVA and binary logistic regression were employed to explore the associations between the variables. A total of 283 autopsy cases were considered, comprising 66.8% males. Among the subjects, 31.3% belonged to the age group of 70-79 years, followed by 29.3% from 60-69 years. Causes of cardiac deaths related to coronary artery pathologies contributed to 82.7% of the cases, with ischaemic heart disease (49.8%) and myocardial infarction (25.4%) being the most common. The ANOVA test showed a statistically significant difference between heart weight among the sexes (p<0.001), while heart weight showed a significant difference between the age groups of 50-59 and 80 and above (p=0.016). A binary logistic regression approach to exploring associations between age, sex, height, and heart weight with the causes of cardiac death (coronary vs. non-coronary) revealed a limited predictive power. Preventive measures and health education should be prioritized to minimize cardiac deaths, especially those due to coronary artery pathology. The importance of further research to improve the predictive modelling of causes of cardiac deaths is also highlighted.
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Ekanayake et al. (2025) studied this question.
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