Machine learning for diagnosis of myocardial infarction using cardiac troponin concentrations - Nature Medicine

within 6 h or in an assumption of linearity, as an absolute change of 6 ng lwithin 3 h. Patients were contacted 3 and 12 months after discharge by telephone calls or in written form. Information regarding death during follow-up was furthermore obtained from the patient’s hospital notes, the family physician’s records and the national registry on mortality.IMPACT was an intervention trial on adult patients in the emergency department with potential acute coronary syndrome .

Risk stratification occurred per the IMPACT protocol. Initial troponin and electrocardiographic testing was performed on presentation. High-risk patients were treated according to the 2006 National Heart Foundation/Cardiac Society of Australia and New Zealand guidelines. Low- and intermediate-risk patients were assessed using an accelerated investigation strategy, with repeat troponin testing 2 h after the first test.

EDACS was a pragmatic randomized, controlled trial of adults with suspected acute myocardial infarction. The primary outcome was the proportion of patients discharged to outpatient care within 6 h of attendance without a subsequent major adverse cardiac event within 30 days. There were 558 patients recruited, 279 in each arm. From 558 patients presenting to a single center , 529 were included in the validation cohort.

For SPACE, patients presenting to Christchurch Hospital with the primary complaint of chest pain of less than 4 h in duration were offered recruitment into our prospective, observational study . Patients with the primary complaint of acute chest, epigastric, neck, jaw or arm pain suspicious of acute coronary syndrome without obvious noncardiac origin lasting ≥20 min were enrolled in accordance with guideline definitions.

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