Machine Learning for Myocardial Infarction Compared With Guideline-Recommended Diagnostic Pathways - Boeddinghaus, J.; Doudesis, D.; Lopez-Ayala, P.; Lee, K. K.; Koechlin, L.; Wildi, K.; Nestelberger, T.; Borer, R.; Miro, O.; Martin-Sanchez, F. J.; Strebel, I.; Rubini Gimenez, M.; et al. (Circulation, 2024)
BACKGROUND: Collaboration for the Diagnosis and Evaluation of Acute Coronary Syndrome (CoDE-ACS) is a validated clinical decision support tool that uses machine learning with or without serial cardiac troponin measurements at a flexible time point to calculate the probability of myocardial infarction (MI). How CoDE-ACS performs at different time points for serial measurement and compares with guideline-recommended diagnostic pathways that rely on fixed thresholds and time points is uncertain. METHODS: Patients with possible MI without ST-segment-elevation were enrolled at 12 sites in 5 countries and underwent serial high-sensitivity cardiac troponin I concentration measurement at 0, 1, and 2 hours. Diagnostic performance of the CoDE-ACS model at each time point was determined for index type 1 MI and the effectiveness of previously validated low- and high-probability scores compared with guideline-recommended European Society of Cardiology (ESC) 0/1-hour, ESC 0/2-hour, and High-STEACS (High-Sensitivity Troponin in the Evaluation of Patients With Suspected Acute Coronary Syndrome) pathways. RESULTS: In total, 4105 patients (mean age, 61 years [interquartile range, 50-74]; 32% women) were included, among whom 575 (14%) had type 1 MI. At presentation, CoDE-ACS identified 56% of patients as low probability, with a negative predictive value and sensitivity of 99.7% (95% CI, 99.5%-99.9%) and 99.0% (98.6%-99.2%), ruling out more patients than the ESC 0-hour and High-STEACS (25% and 35%) pathways. Incorporating a second cardiac troponin measurement, CoDE-ACS identified 65% or 68% of patients as low probability at 1 or 2 hours, for an identical negative predictive value of 99.7% (99.5%-99.9%); 19% or 18% as high probability, with a positive predictive value of 64.9% (63.5%-66.4%) and 68.8% (67.3%-70.1%); and 16% or 14% as intermediate probability. In comparison, after serial measurements, the ESC 0/1-hour, ESC 0/2-hour, and High-STEACS pathways identified 49%, 53%, and 71% of patients as low risk, with a negative predictive value of 100% (99.9%-100%), 100% (99.9%-100%), and 99.7% (99.5%-99.8%); and 20%, 19%, or 29% as high risk, with a positive predictive value of 61.5% (60.0%-63.0%), 65.8% (64.3%-67.2%), and 48.3% (46.8%-49.8%), resulting in 31%, 28%, or 0%, who require further observation in the emergency department, respectively. CONCLUSIONS: CoDE-ACS performs consistently irrespective of the timing of serial cardiac troponin measurement, identifying more patients as low probability with comparable performance to guideline-recommended pathways for MI. Whether care guided by probabilities can improve the early diagnosis of MI requires prospective evaluation. REGISTRATION: URL: https://www.clinicaltrials.gov; Unique identifier: NCT00470587.
Keywords: journalArticle; *Acute Coronary Syndrome/diagnosis; *Myocardial Infarction/diagnosis; Abbott Diagnostics, outside the submitted work. Dr Koechlin received a research; Biomarkers; Boeddinghaus, Doudesis, Lee, Bularga, Ferry, Tuck, Anand, and Gray are employees; Boehringer Ingelheim, Bayer, BMS, Idorsia, Novartis, Osler, Roche, and Sanofi,; Coulter, Bayer, Ortho Clinical Diagnostics, and Orion Pharma, outside the; Diagnostics, Ortho Clinical Diagnostics, Quidel Corporation, and Beckman Coulter,; Diagnostics, Siemens Healthineers, and Abbott Diagnostics, outside the submitted; Diagnostics, Siemens Healthineers, and LumiraDx. Dr Mueller has received research; Diagnostics, which had no role in the study design, data analysis, manuscript; Dr Nestelberger has received research support from the Swiss National Science; Edinburgh and honoraria or consultancy from Abbott Diagnostics, Roche; Female; Foundation (grant P400PM_191037/1), the Prof Dr Max Cloetta Foundation, the; Freiwillige Akademische Gesellschaft, as well as speaker honoraria from Roche; Hospital Basel, as well as speaker or consulting honoraria from Siemens, Beckman; Humans; Machine Learning; Male; Margarete und Walter Lichtenstein-Stiftung (grant 3MS1038), and the University; Middle Aged; Ortho Clinical Diagnostics, Quidel, Roche, Siemens, Singulex, and Sphingotec, as; Troponin; Troponin T; algorithm. The other authors have reported no relationships relevant to the; and travel support from Medtronic, all outside the submitted work. Dr Lopez-Ayala; contents of this article to disclose; grant from the University of Basel, the Swiss Heart Foundation, the SAMW, and the; has received speaker honoraria or consultancy from Quidel, paid to the; institution, outside the submitted work. Dr Lee has received honoraria from; myocardial infarction; of the University of Edinburgh, which has filed for a patent on the CoDE-ACS; outside of the submitted work. The cardiac troponin assay was donated by Abbott; preparation, or the decision to submit the manuscript for publication. Drs Mills,; submitted work. Dr Mills has received research grants to the University of; support from Abbott Diagnostics, Beckman Coulter, bioMerieux, Idorsia, Novartis,; the University of Queensland, Brisbane, Australia, and the University of Basel; troponin; well as speaker honoraria or consulting honoraria from Acon, Amgen, Astra Zeneca,; work. Dr Wildi has received research support from the Wesley Research Institute,