ArticleInflammation research : official journal of the European Histamine Research Society ... [et al.]2023
Multimodal data-driven prognostic model for predicting new-onset ST-elevation myocardial infarction following emergency percutaneous coronary intervention.
Article in Inflammation research : official journal of the European Histamine Research Society ... [et al.], 2023. 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.
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Who cites it
22 citing papers in PubMed, 1 synthesis or guideline pooled it.
- Accuracy of Machine Learning Models for Early Prediction of Major Cardiovascular Events Post Myocardial Infarction: A Systematic Review and Meta-Analysis.Reviews in cardiovascular medicine · 2025Pooled it
- The combined effect of arterial hypertension and coronary microvascular dysfunction in the prognosis of patients with ST-segment elevation myocardial infarction: a real-world study.BMC cardiovascular disorders · 2026Article
- Risk assessment of acute heart failure after endovascular therapy in acute ischemic stroke: a nomogram-based study.Frontiers in cardiovascular medicine · 2026Article
- Risk prediction for long-term cardiovascular events in patients with concurrent hypertension, HFpEF, and unstable angina: a multicenter machine learning-assisted cohort study.Frontiers in endocrinology · 2026Article
- A composite model incorporating systemic inflammatory burden and GRACE score for enhanced identification of elevated myocardial stress in acute myocardial infarction: an exploratory analysis.Frontiers in cardiovascular medicine · 2026Article
- Machine learning-selected inflammation biomarkers for stable coronary artery disease with intermediate coronary lesions: potential for long-term prognosis in a multicenter cohort study.Frontiers in physiology · 2026Article
- Machine learning-enhanced prediction model for atrial fibrillation development in patients with concurrent type 2 diabetes and obstructive sleep apnea syndrome: a comorbidity perspective.Nutrition & metabolism · 2025Article
- Multimodal Data-Driven Explainable Prognostic Model for Major Adverse Cardiovascular Events Prediction in Patients With Unstable Angina and Heart Failure With Preserved Ejection Fraction: Multicenter, Cross-Regional Cohort Study.Journal of medical Internet research · 2025Article
- Integrated metabolic-inflammatory risk assessment: HbA1c/HDL-c and hsCRP-to-albumin ratios synergistically predict major adverse cardiovascular events in post-PCI STEMI patients.Lipids in health and disease · 2025Article
- Inflammatory markers guide early risk stratification and prognosis in elderly patients with acute myocardial infarction.Scientific reports · 2025Article
- Association between glucose-to-albumin ratio and ischemic stroke risk in patients with coronary heart disease: a machine learning-based predictive model analysis.BMC cardiovascular disorders · 2025Article
- Construction and Clinical Relevance of a Predictive Model of Coronary Microcirculatory Dysfunction in Patients With Acute Myocardial Infarction Following Percutaneous Coronary Intervention.Reviews in cardiovascular medicine · 2025Article
- Multimodal Visualization and Explainable Machine Learning-Driven Markers Enable Early Identification and Prognosis Prediction for Symptomatic Aortic Stenosis and Heart Failure With Preserved Ejection Fraction After Transcatheter Aortic Valve Replacement: Multicenter Cohort Study.Journal of medical Internet research · 2025Article
- Novel insights into myocardial fibrosis in patients with new onset ST-elevation myocardial infarction following percutaneous coronary intervention through enhanced cardiac magnetic resonance imaging: a prospective cohort study.BMC cardiovascular disorders · 2025Article
- Multimodal data-driven prognostic model for predicting long-term outcomes in older adult patients with sarcopenia: a retrospective cohort study.Frontiers in public health · 2025Article
- Developing a novel diagnostic model for identifying high-risk plaques in new onset unstable angina pectoris using coronary CT angiography.Frontiers in endocrinology · 2025Article
- Associations of Gla-rich protein and interleukin-1β with coronary artery calcification risk in patients with suspected coronary artery disease.Frontiers in endocrinology · 2025Article
- Multimodal Data-Driven Prognostic Model for Predicting Long-Term Prognosis in Patients With Ischemic Cardiomyopathy and Heart Failure With Preserved Ejection Fraction After Coronary Artery Bypass Grafting: A Multicenter Cohort Study.Journal of the American Heart Association · 2024Article
- Incorporating Inflammation Biomarker-Driven Multivariate Predictive Model for Coronary Microcirculatory Dysfunction in Acute Myocardial Infarction Following Emergency Percutaneous Coronary Intervention.Clinical cardiology · 2024Article
- Multimodal Data Integration Enhance Longitudinal Prediction of New-Onset Systemic Arterial Hypertension Patients with Suspected Obstructive Sleep Apnea.Reviews in cardiovascular medicine · 2024Article
Corrections and comments
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Authors and funding
7 authors.
Funding
Abstract
objectivesWe developed a nomogram model derived from inflammatory indices, clinical data, and imaging data to predict in-hospital major adverse cardiac and cerebrovascular events (MACCEs) following emergency percutaneous coronary intervention (PCI) in patients with new-onset ST-elevation myocardial infarction (STEMI).
methodsPatients with new-onset STEMI admitted between June 2020 and November 2022 were retrospectively reviewed. Data pertaining to coronary angiograms, clinical data, biochemical indices, and in-hospital clinical outcomes were derived from electronic medical records. Lasso regression model was employed to screen risk factors and construct a prediction model.
resultsOverall, 547 patients with new-onset STEMI who underwent PCI were included and assigned to the training cohort (n = 384) and independent verification cohort (n = 163). Six clinical features (age, diabetes mellitus, current smoking, hyperuricemia, neutrophil-to-lymphocyte ratio, and Gensini score) were selected by LASSO regression to construct a nomogram to predict the risk of in-hospital MACCEs. The area-under-the-curve (AUC) values for in-hospital MACCEs risk in the training and independent verification cohorts were 0.921 (95% CI 0.881-0.961) and 0.898 (95% CI 0.821-0.976), respectively. It was adequately calibrated in both training cohort and independent verification cohorts, and predictions were correlated with actual outcomes. Decision curve analysis demonstrated that the nomogram was capable of predicting in-hospital MACCEs with good clinical benefit.
conclusionsOur prediction nomogram based on multi-modal data (inflammatory indices, clinical and imaging data) reliably predicted in-hospital MACCEs in new-onset STEMI patients with emergency PCI. This prediction nomogram can enable individualized treatment strategies.
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37644338What 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.