Although guidelines recommend fixed cardiac troponin thresholds for the diagnosis of myocardial infarction, troponin concentrations are influenced by age, sex, comorbidities and time from symptom onset. To improve diagnosis, we developed machine learning models that integrate cardiac troponin concentrations at presentation or on serial testing with clinical features and compute the Collaboration for the Diagnosis and Evaluation of Acute Coronary Syndrome (CoDE-ACS) score (0–100) that corresponds to an individual’s probability of myocardial infarction. The models were trained on data from 10,038 patients (48% women), and their performance was externally validated using data from 10,286 patients (35% women) from seven cohorts. CoDE-ACS had excellent discrimination for myocardial infarction (area under curve, 0.953; 95% confidence interval, 0.947–0.958), performed well across subgroups and identified more patients at presentation as low probability of having myocardial infarction than fixed cardiac troponin thresholds (61 versus 27%) with a similar negative predictive value and fewer as high probability of having myocardial infarction (10 versus 16%) with a greater positive predictive value. Patients identified as having a low probability of myocardial infarction had a lower rate of cardiac death than those with intermediate or high probability 30 days (0.1 versus 0.5 and 1.8%) and 1 year (0.3 versus 2.8 and 4.2%; P < 0.001 for both) from patient presentation. CoDE-ACS used as a clinical decision support system has the potential to reduce hospital admissions and have major benefits for patients and health care providers.

尽管指南建议使用固定的心肌肌钙蛋白阈值来诊断心肌梗死，但肌钙蛋白浓度受年龄、性别、合并症和症状发作时间的影响。为了改进诊断，我们开发了机器学习模型，将出现时或连续测试时的心肌肌钙蛋白浓度与临床特征相结合，并计算对应于一个人患心肌梗塞的概率。这些模型根据来自 10,038 名患者（48% 为女性）的数据进行训练，并使用来自七个队列的 10,286 名患者（35% 为女性）的数据对它们的性能进行了外部验证。CoDE-ACS 对心肌梗死具有出色的鉴别能力（曲线下面积，0.953；95% 置信区间，0.947–0. 958)，在各个亚组中表现良好，并且在就诊时发现更多的患者比固定的心肌肌钙蛋白阈值具有较低的心肌梗死概率（61 对 27%），具有相似的阴性预测值，而较少的患者具有心肌梗塞的高概率（10 对 16 %) 具有更大的阳性预测值。30 天（0.1 对 0.5 和 1.8%）和 1 年（0.3 对 2.8 和 4.2%；跨亚组表现良好，并确定更多的患者在就诊时患心肌梗死的可能性低于固定的心肌肌钙蛋白阈值（61% 对 27%），具有相似的阴性预测值，而较少的患者患心肌梗塞的可能性高（10% 对 16%）更大的阳性预测值。30 天（0.1 对 0.5 和 1.8%）和 1 年（0.3 对 2.8 和 4.2%；跨亚组表现良好，并确定更多的患者在就诊时患心肌梗死的可能性低于固定的心肌肌钙蛋白阈值（61% 对 27%），具有相似的阴性预测值，而较少的患者患心肌梗塞的可能性高（10% 对 16%）更大的阳性预测值。30 天（0.1 对 0.5 和 1.8%）和 1 年（0.3 对 2.8 和 4.2%； 两者P < 0.001）来自患者介绍。用作临床决策支持系统的 CoDE-ACS 有可能减少住院人数，并为患者和医疗保健提供者带来重大好处。