ArticleBMJ open2021
Development and validation of a risk prediction model for in-hospital major cardiovascular events in patients hospitalised for acute myocardial infarction.
Article in BMJ open, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.
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Who cites it
7 citing papers in PubMed.
- Article
- Risk prediction in people with acute myocardial infarction in England: a cohort study using data from 1521 general practices.BMJ open · 2025Article
- Development and validation of a risk score for predicting 30-day mortality in patients with ST elevation myocardial infarction.Scientific reports · 2025Article
- A Prediction Model Based on Systemic Immune-Inflammatory Index Combined with Other Predictors for Major Adverse Cardiovascular Events in Acute Myocardial Infarction Patients.Journal of inflammation research · 2024Article
- In-hospital major adverse cardiovascular events after primary percutaneous coronary intervention in patients with acute ST-segment elevation myocardial infarction: a retrospective study under the China chest pain center (standard center) treatment system.BMC cardiovascular disorders · 2023Article
- Prediction models for major adverse cardiovascular events after percutaneous coronary intervention: a systematic review.Frontiers in cardiovascular medicine · 2023Review
- Effects of Danhong injection combined with tirofiban on cardiac function, myocardial enzyme spectrum and lipoprotein-associated phospholipase A2 level in patients with acute myocardial infarction.American journal of translational research · 2022Article
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Authors and funding
11 authors.
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Abstract
objectivesPatients admitted to hospital with acute myocardial infarction (AMI) have considerable variability in in-hospital risks, resulting in higher demands on healthcare resources. Simple risk-assessment tools are important for the identification of patients with higher risk to inform clinical decisions. However, few risk assessment tools have been built that are suitable for populations with AMI in China. We aim to develop and validate a risk prediction model, and further build a risk scoring system.
designData from a nationally representative retrospective study was used to develop the model. Patients from a prospective study and another nationally representative retrospective study were both used for external validation.
setting161 nationally representative hospitals, and 53 and 157 other hospitals were involved in the above three studies, respectively.
participants8010 patients hospitalised for AMI were included as development sample, and 4485 and 11 223 other patients were included as validation samples in their corresponding studies. PRIMARY AND SECONDARY OUTCOME MEASURES: The in-hospital major adverse cardiovascular events (MACE) was defined as death from any cause, recurrent AMI, or ischaemic stroke.
resultsThe proportion of in-hospital MACE was 11.7%, 8.8% and 11.4% among the development sample and two external-validation samples, respectively. Nine predictors (ie, age, sex, left ventricular ejection fraction, Killip class, systolic blood pressure, creatinine, white blood cell count, heart rate and blood glucose) were independently associated with in-hospital MACE. The model performed well on both discrimination and calibration capability, with areas under the Receiver Operating Characteristic Curve (ROC) curve of 0.85, 0.74 and 0.80, and calibration slopes of 0.98, 0.84 and 0.97 in the development sample and two external validation samples, respectively. A point-based risk scoring system was built with good discrimination and reclassification ability.
conclusionsA prediction model using readily available clinical parameters was developed and externally validated to estimate risks of in-hospital MACE among patients with AMI, thereby better informing decision-making in improving clinical care.
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