ArticleThe Lancet regional health. Western Pacific2022
Biomarker-based risk model to predict cardiovascular events in patients with acute coronary syndromes - Results from BIPass registry.
Article in The Lancet regional health. Western Pacific, 2022. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers.
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Who cites it
10 citing papers in PubMed, 18 citations in OpenAlex.
- Association of the Uric Acid-to-Magnesium Ratio and Frontal QRS-T Angle with Angiographic Coronary Disease Severity in Acute Coronary Syndrome.Journal of clinical medicine · 2026Article
- A Novel Risk Score Based on Lipid-Related Biomarkers for Acute Coronary Syndromes: A Multicenter Machine Learning Study.Reviews in cardiovascular medicine · 2026Article
- Predicting the rapid progression of coronary artery lesions in patients with acute coronary syndrome based on machine learning.Frontiers in cardiovascular medicine · 2025Article
- Plasma metabolomics reveals the shared and distinct metabolic disturbances associated with cardiovascular events in coronary artery disease.Nature communications · 2024Article
- Development and evaluation of a chronic kidney disease risk prediction model using random forest.Frontiers in genetics · 2024Article
- Article
- Prehospital Targeting of 1-Year Mortality in Acute Chest Pain by Cardiac Biomarkers.Diagnostics (Basel, Switzerland) · 2023Article
- GDF-15 at admission predicts cardiovascular death, heart failure, and bleeding outcomes in patients with CAD.ESC heart failure · 2023Article
- Risk Prediction Models for Ischemic Cardiovascular Outcomes in Patients with Acute Coronary Syndrome.Reviews in cardiovascular medicine · 2023Review
- Relationship Between International Normalized Ratio to Albumin Ratio and Mortality in Critically Ill Patients With Myocardial Infarction.Clinical and applied thrombosis/hemostasis : official journal of the International Academy of Clinical and Applied Thrombosis/HemostasisArticle
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Authors and funding
15 authors at 7 institutions in 2 countries.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Background: Risk models integrating new biomarkers to predict cardiovascular events in acute coronary syndromes (ACS) are lacking. Therefore, we evaluated the prognostic value of biomarkers in addition to clinical predictors and developed a biomarker-based risk model for major adverse cardiovascular events (MACE) within 12 months after hospital admission with ACS. Methods: Patients ( Findings: Over 12 months, 196 patients experienced MACE (5.1%/year). Among twelve candidate biomarkers, N-terminal pro-B-type natriuretic peptide (NT-proBNP) measured at baseline showed the most prognostic capability independent of clinical predictors. The developed BIPass risk model included age, hypertension, previous myocardial infarction, stroke, Killip class, heart rate, and NT-proBNP. It displayed improved discrimination (C-statistic 0.79, 95% CI 0.73-0.85), calibration (GOF = 9.82, Interpretation: The BIPass risk model, integrating clinical variables and NT-proBNP, is useful for predicting 12-month MACE in ACS. It effectively identifies a gradient risk of cardiovascular events to aid personalized care. Funding: National Key R&D Program of China (2017YFC0908700, 2020YFC0846600), National S&T Fundamental Resources Investigation Project (2018FY100600, 2018FY100602), Taishan Pandeng Scholar Program of Shandong Province (tspd20181220), Taishan Young Scholar Program of Shandong Province (tsqn20161065, tsqn201812129), Youth Top-Talent Project of National Ten Thousand Talents Plan and Qilu Young Scholar Program.
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