Trial reportThe Lancet. Digital health2022
Validation of the myocardial-ischaemic-injury-index machine learning algorithm to guide the diagnosis of myocardial infarction in a heterogenous population: a prespecified exploratory analysis.
Trial report in The Lancet. Digital health, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 22 papers, 1 of them a synthesis that pooled it.
What it found
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The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it, 37 citations in OpenAlex.
- Predictive Value of Machine Learning for Recurrence of Atrial Fibrillation after Catheter Ablation: A Systematic Review and Meta-Analysis.Reviews in cardiovascular medicine · 2023Pooled it
- Machine learning for diagnosing non-ST-segment elevation myocardial infarction: a derivation and validation study.EClinicalMedicine · 2026Article
- Clinical Gray Zones of Cardiac Troponin Interpretation in the Emergency Department: When Increased Concentrations Do Not Equal Acute Coronary Syndrome.Journal of clinical medicine · 2026Review
- Sex-Consistent Performance of an AI-Enabled ECG for Acute Myocardial Infarction: The ROMIAE Study.JACC. Advances · 2026Article
- The role of artificial intelligence in early detection and risk prediction of ischemic heart disease.Annals of medicine and surgery (2012) · 2026Review
- First-line risk stratification with machine learning models facilitates rapid triage for non-ST-elevation myocardial infarction.PLOS digital health · 2026Article
- AI-guided refinement of coronary revascularization need in patients suspected of acute coronary syndrome.European heart journal. Digital health · 2025Article
- Harnessing Artificial Intelligence for Innovation in Interventional Cardiovascular Care.Journal of the Society for Cardiovascular Angiography & Interventions · 2025Review
- Addressing myocardial infarction in South-Asian populations: risk factors and machine learning approaches.NPJ cardiovascular health · 2025Review
- Machine Learning Applications in Acute Coronary Syndrome: Diagnosis, Outcomes and Management.Advances in therapy · 2025Review
- Article
- Review
- A Multimodal Omics Framework to Empower Target Discovery for Cardiovascular Regeneration.Cardiovascular drugs and therapy · 2024Review
- Adopting artificial intelligence in cardiovascular medicine: a scoping review.Hypertension research : official journal of the Japanese Society of Hypertension · 2024Article
- Clinical Biochemistry of Serum Troponin.Diagnostics (Basel, Switzerland) · 2024Review
- Personalized diagnosis in suspected myocardial infarction.Clinical research in cardiology : official journal of the German Cardiac Society · 2023Article
- Machine learning for diagnosis of myocardial infarction using cardiac troponin concentrations.Nature medicine · 2023Article
- Deep Learning Analysis of Chest Radiographs to Triage Patients with Acute Chest Pain Syndrome.Radiology · 2023Article
- Risk stratification of patients who present with chest pain and have normal troponins using a machine learning model.World journal of cardiology · 2022Article
- Influence of Age on the Diagnosis of Myocardial Infarction.Circulation · 2022Article
Corrections and comments
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Authors and funding
11 authors at 5 institutions in 2 countries.
Funding
Abstract
backgroundDiagnostic pathways for myocardial infarction rely on fixed troponin thresholds, which do not recognise that troponin varies by age, sex, and time within individuals. To overcome this limitation, we recently introduced a machine learning algorithm that predicts the likelihood of myocardial infarction. Our aim was to evaluate whether this algorithm performs well in routine clinical practice and predicts subsequent events.
methodsThe myocardial-ischaemic-injury-index (MI
findingsIn total, 20 761 patients (64 years [SD 16], 9597 [46%] women) enrolled between June 10, 2013, and March 3, 2016, were included from the High-STEACS trial cohort, of whom 3272 (15·8%) had myocardial infarction. MI
interpretationIn consecutive patients undergoing serial cardiac troponin measurement for suspected acute coronary syndrome, the MI
fundingMedical Research Council, British Heart Foundation, National Institute for Health Research, and NHSX.
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What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.