Study on forensic diagnostic biomarker combination for acute ischemia heart disease based on postmortem biochemistry.

J Forensic Leg Med

Key Laboratory of Evidence Science (China University of Political Science and Law), Ministry of Education, 100088, Beijing, China; Collaborative Innovation Center of Judicial Civilization, 100088, Beijing, China. Electronic address:

Published: February 2025


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Article Abstract

Sudden cardiac death (SCD) caused by ischemia heart disease (IHD) has traditionally been identified through autopsy and microscopic examination. However, these methods are limited in diagnosing cases of acute ischemia heart disease (AIHD) without typical myocardial necrosis and excessive reliance on the subjective experience of experts. Postmortem biochemistry is crucial in the assisted diagnosis of SCD in forensic medicine. We evaluated the expression levels of six sensitive biomarkers of myocardial injury in the training-set comprising 78 cases of acute ischemia (AI), 23 cases of acute myocardial infarction (MI), and 37 cases who died of high falls. The results showed that CK-MB, cTnI, BNP, LDH, and HBDH may be of great significance in diagnosing sudden death of AIHD. Among these, BNP, LDH, and HBDH are particularly useful for distinguishing between AI and acute MI. Using receiver operating analysis, we identified that the combination of five biomarkers-BNP, cTnI, CK-MB, LDH, and HBDH-achieved a significantly higher diagnostic accuracy for AIHD, with an AUC of 0.910. This combination outperformed the traditional three-biomarker combination (CK-MB, cTnI, BNP), which was considered highly accurate but only had an AUC of 0.857. Additionally, a three-biomarker combination (BNP, HBDH, and LDH) demonstrated clear advantages in differentiating between AI and acute MI, with an AUC of 0.794. Validation-set results proved that the strategy of finding the unique combination based on postmortem biochemistry is effective. It can provide valuable information for the discrimination of AIHD and the identification of AI and acute MI.

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http://dx.doi.org/10.1016/j.jflm.2025.102825DOI Listing

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