High-sensitive cardiac troponin hs-TnT levels in sudden deaths related to atherosclerotic coronary artery disease

Postmortem biochemistry in deaths from ischemic heart disease

Ischemic heart disease (IHD) is one of the leading causes of morbidity and sudden cardiac death worldwide and is an important public health problem. The presence of ischemia in clinical applications can be detected by ECG, biochemical markers, and radiological methods. Myocardial infarction is also frequently encountered in forensic autopsies. Postmortem diagnosis is determined as a result of histopathological examinations and additional exclusionary examinations (toxicology, microbiology, etc.). However, routine histopathological examinations are insufficient, especially when death occurs in the early period of ischemia. It creates a problem for forensic pathologists and forensic medicine specialists in such cases of sudden cardiac death. Postmortem biochemistry is one of the important and promising disciplines in which forensic applications work in order to diagnose these cases correctly. The issue of whether biomarkers used in the diagnosis of myocardial infarction in clinical studies can be used reliably in postmortem cases has been discussed by forensic medicine researchers for some time. This manuscript aims to review and summarize biomarkers belonging to various categories that have been studied in IHD-related deaths, in biological fluids taken at autopsy, or in animal experiments. Our study shows that the postmortem use of biochemical markers in the diagnosis of IHD yields promising results. However, it should not be forgotten that postmortem biochemistry is different from clinical applications due to its dynamics and that the body causes unpredictable changes in markers in the postmortem process. Therefore, comprehensive studies are needed to evaluate the postmortem stability of these markers in different biological fluids, their significance among various causes of death, and whether they are affected by any variable (Cardiopulmonary resuscitation, Postmortem interval, medications, etc.) before they are routinely applied. It is suggested by the authors that the cut-off values of biomarkers whose significance has been proven by these studies should be determined and that they should be used in this way in routine applications.

Exploring the Potential of Proteome Analysis as a Promising Tool for Evaluation of Sudden Cardiac Death (SCD) in Forensic Settings: A Literature Review

Sudden cardiac death (SCD) represents a global emergency, with a high number of cases affecting all age groups every year. The prevention of these fatal events requires an accurate knowledge of etiology and pathogenesis, which can vary. Autopsy is an indispensable tool in cases of SCD for diagnostic purposes, as well as for judicial and preventive purposes for family members. Despite the completion of all routine post-mortem investigations, it is often complicated for the forensic pathologist to define the triggering cause of these events. The study of the proteome is proving to be extremely promising in the field of human cardiovascular disease. This paper aims to offer a literature review on the study of the proteome in post-mortem cadaveric biological samples obtained from SCD cases. The aim of this work is to outline the state of the art of the scientific advances that protein analysis can offer in the diagnosis of SCD and the limits that various studies have traced up to now. In conclusion, the work defines the future perspectives of this field in SCD, suggesting strategies to overcome the reported limits and improve the diagnostics of these events.

Forensic identification of sudden cardiac death: a new approach combining metabolomics and machine learning

The determination of sudden cardiac death (SCD) is one of the difficult tasks in the forensic practice, especially in the absence of specific morphological changes in the autopsies and histological investigations. In this study, we combined the metabolic characteristics from corpse specimens of cardiac blood and cardiac muscle to predict SCD. Firstly, ultra-high performance liquid chromatography coupled with high-resolution mass spectrometry (UPLC-HRMS)-based untargeted metabolomics was applied to obtain the metabolomic profiles of the specimens, and 18 and 16 differential metabolites were identified in the cardiac blood and cardiac muscle from the corpses of those who died of SCD, respectively. Several possible metabolic pathways were proposed to explain these metabolic alterations, including the metabolism of energy, amino acids, and lipids. Then, we validated the capability of these combinations of differential metabolites to distinguish between SCD and non-SCD through multiple machine learning algorithms. The results showed that stacking model integrated differential metabolites featured from the specimens showed the best performance with 92.31% accuracy, 93.08% precision, 92.31% recall, 91.96% F1 score, and 0.92 AUC. Our results revealed that the SCD metabolic signature identified by metabolomics and ensemble learning in cardiac blood and cardiac muscle has potential in SCD post-mortem diagnosis and metabolic mechanism investigations.

Significance of postmortem biomarkers and multimarker strategy in sudden cardiac death

The most common cause in the etiology of sudden cardiac death (SCD) is ischemic heart disease due to atherosclerosis. Postmortem diagnosis can be made by histopathological examinations, but routine histopathological examinations are limited, especially in the early period of postmortem ischemia. For this reason, many methods are being investigated for the postmortem diagnosis of ischemia, and postmortem biochemical studies are promising. In our study, we evaluated the biochemical markers; hs-cTnT, NT-proBNP, H-FABP, pentraxin-3, copeptin, ischemic modified albumin (IMA), and PAPP-A in postmortem serums. In forensic pathology practice, it was investigated whether it would be useful to go to the diagnosis by measuring more than one marker in a single biological fluid in SCD cases. The study included 35 sudden cardiac death cases and 24 control cases and as a result of our study, hs-cTnT, NT-proBNP, and H-FABP values were found to be significantly higher in the SCD group than in the control group. Within the scope of the multi-marker strategy, models were tried to be developed in which the markers were used together, and it was concluded that the model consisting of the myocardial ischemia marker hs-cTnT, the myocardial stress marker NT-proBNP, and the inflammation marker pentraxin 3 was the most accurate combination by correctly classifying the cases at a rate of 94.9%. As a result, it was thought that it would be appropriate to use the multi-marker strategy which is widely used in clinical applications, also in forensic medicine applications.

Combined metabolomics and machine learning algorithms to explore metabolic biomarkers for diagnosis of acute myocardial ischemia

Acute myocardial ischemia (AMI) remains the leading cause of death worldwide, and the post-mortem diagnosis of AMI represents a current challenge for both clinical and forensic pathologists. In the present study, the untargeted metabolomics based on ultra-performance liquid chromatography combined with high-resolution mass spectrometry was applied to analyze serum metabolic signatures from AMI in a rat model (n = 10 per group). A total of 28 endogenous metabolites in serum were significantly altered in AMI group relative to control and sham groups. A set of machine learning algorithms, namely gradient tree boosting (GTB), support vector machine (SVM), random forest (RF), logistic regression (LR), and multilayer perceptron (MLP) models, was used to screen the more valuable metabolites from 28 metabolites to optimize the biomarker panel. The results showed that classification accuracy and performance of MLP model were better than other algorithms when the metabolites consisting of L-threonic acid, N-acetyl-L-cysteine, CMPF, glycocholic acid, L-tyrosine, cholic acid, and glycoursodeoxycholic acid. Finally, 17 blood samples from autopsy cases were applied to validate the classification model's value in human samples. The MLP model constructed based on rat dataset achieved accuracy of 88.23%, and ROC of 0.89 for predicting AMI type II in autopsy cases of sudden cardiac death. The results demonstrated that MLP model based on 7 molecular biomarkers had a good diagnostic performance for both AMI rats and autopsy-based blood samples. Thus, the combination of metabolomics and machine learning algorithms provides a novel strategy for AMI diagnosis.

Interpol review of toxicology 2016-2019

This review paper covers the forensic-relevant literature in toxicology from 2016 to 2019 as a part of the 19th Interpol International Forensic Science Managers Symposium. The review papers are also available at the Interpol website at: https://www.interpol.int/content/download/14458/file/Interpol%20Review%20.Papers%202019.pdf.

Diagnosis of myocardial infarction at autopsy: AECVP reappraisal in the light of the current clinical classification

Ischemic heart disease is one of the leading causes of morbidity and death worldwide. Consequently, myocardial infarctions are often encountered in clinical and forensic autopsies, and diagnosis can be challenging, especially in the absence of an acute coronary occlusion. Precise histopathological identification and timing of myocardial infarction in humans often remains uncertain while it can be of crucial importance, especially in a forensic setting when third person involvement or medical responsibilities are in question. A proper post-mortem diagnosis requires not only up-to-date knowledge of the ischemic coronary and myocardial pathology, but also a correct interpretation of such findings in relation to the clinical scenario of the deceased. For these reasons, it is important for pathologists to be familiar with the different clinically defined types of myocardial infarction and to discriminate myocardial infarction from other forms of myocardial injury. This article reviews present knowledge and post-mortem diagnostic methods, including post-mortem imaging, to reveal the different types of myocardial injury and the clinical-pathological correlations with currently defined types of myocardial infarction.

Diagnostic Roles of Postmortem cTn I and cTn T in Cardiac Death with Special Regard to Myocardial Infarction: A Systematic Literature Review and Meta-Analysis

Background: Cardiac troponin I (cTn I) and cardiac troponin T (cTn T) are currently widely used as diagnostic biomarkers for myocardial injury caused by ischemic heart diseases in clinical and forensic medicine. However, no previous meta-analysis has summarized the diagnostic roles of postmortem cTn I and cTn T. The aim of the present study was to meta-analyze the diagnostic roles of postmortem cTn I and cTn T for cardiac death in forensic medicine, present a systematic review of the previous literature, and determine the postmortem cut-off values of cTn I and cTn T. Methods: We searched multiple databases for the related literature, performed a meta-analysis to investigate the diagnostic roles of postmortem cardiac troponins, and analyzed the receiver operating characteristic (ROC) curve to determine their postmortem cut-off values. Results and Conclusions: The present meta-analysis demonstrated that postmortem cTn I and cTn T levels were increased in pericardial fluid and serum in cardiac death, especially in patients with acute myocardial infarction (AMI). We determined the postmortem cut-off value of cTn I in the pericardial fluid at 86.2 ng/mL, cTn I in serum at 9.5 ng/mL, and cTn T in serum at 8.025 ng/mL.

Postoperative high-sensitivity troponin T as a predictor of sudden cardiac arrest in patients undergoing cardiac surgery

BACKGROUND

The usefulness of high-sensitivity troponin T (hs-TnT) as a predictor of sudden cardiac arrest (SCA) in patients undergoing valve surgery is currently unknown.

METHODS

A prospective study was conducted on a group of 815 consecutive patients with significant valvular heart disease that underwent elective valve surgery. The primary end-point was postoperative SCA.

RESULTS

The postoperative SCA occurred in 26 patients. At multivariate analysis of hs-TnT measured immediately after surgery (hs-TnT I) and age remained independent predictors of the primary end-point.

CONCLUSIONS

Elevated postoperative hs-TnT was associated with a higher risk of postoperative SCA.

Biomarkers in acute myocardial infarction: current perspectives

PURPOSE

Acute myocardial infarction (AMI) is the most common cause of death in the world. Comprehensive risk assessment of patients presenting with chest pain and eliminating undesirable results should decrease morbidity and mortality rates, increase the quality of life of patients, and decrease health expenditure in many countries. In this study, the advantages and disadvantages of the enzymatic and nonenzymatic biomarkers used in the diagnosis of patients with AMI are given in historical sequence, and some candidate biomarkers - hFABP, GPBB, S100, PAPP-A, RP, TNF, IL6, IL18, CD40 ligand, MPO, MMP9, cell-adhesion molecules, oxidized LDL, glutathione, homocysteine, fibrinogen, and D-dimer procalcitonin - with a possible role in the diagnosis of AMI are discussed.

METHODS

The present study was carried out using meta-analyses, reviews of clinical trials, evidence-based medicine, and guidelines indexed in PubMed and Web of Science.

RESULTS

These numerous AMI biomarkers guide clinical applications (diagnostic methods, risk stratification, and treatment). Today, however, TnI remains the gold standard for the diagnosis of AMI. Details in the text will be given of many biomarkers for the diagnosis of AMI.

CONCLUSION

We evaluated the advantages and disadvantages of routine enzymatic and nonenzymatic biomarkers and the literature evidence of other candidate biomarkers in the diagnosis of AMI, and discuss challenges and constraints that limit translational use from bench to bedside.