SynthesisTherapeutic advances in cardiovascular disease
Predicting the no-reflow phenomenon in ST-elevation myocardial infarction patients undergoing primary percutaneous coronary intervention: a systematic review of clinical prediction models.
Synthesis in Therapeutic advances in cardiovascular disease. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
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Who cites it
3 citing papers in PubMed.
- Inflammation-Based C-Reactive Protein-to-Albumin Ratio for No-Reflow Prediction in STEMI.Biomedicines · 2026Article
- Article
- The predictive role of dyspnea in left main and/or three-vessel coronary artery involvement in patients with myocardial infarction: an analytical cross-sectional study.BMC cardiovascular disorders · 2025Article
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Authors and funding
7 authors.
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No grant is acknowledged in the PubMed record.
Abstract
backgroundThe no-reflow (NRF) phenomenon is the "Achilles heel" of interventionists after performing percutaneous coronary intervention (PCI) in patients with ST-segment elevation myocardial infarction (STEMI). No definitive treatment has been proposed for NRF, and preventive strategies are central to improving care for patients who develop NRF.
objectivesIn this study, we aim to investigate the clinical prediction models developed to predict NRF in STEMI patients undergoing primary PCI.
designSystematic review. DATA SOURCES AND
methodsPreferred Reporting Items for Systematic Reviews and Meta-Analyses (PRISMA) guidelines were observed. Studies that developed clinical prediction modeling for NRF after primary PCI in STEMI patients were included. Data extraction was performed using the Checklist for Critical Appraisal and Data Extraction for Systematic Reviews of Prediction Modeling Studies (CHARMS) checklist. The Prediction Model Risk of Bias Assessment Tool (PROBAST) tool was used for critical appraisal of the included studies.
resultsThe three most common predictors were age, total ischemic time, and preoperative thrombolysis in myocardial infarction flow grade. Most of the included studies internally validated their developed model via various methods: random split, bootstrapping, and cross-validation. Only three studies (18%) externally validated their model. Six studies (37%) reported a calibration plot with or without the Hosmer-Lemeshow test. The reported area under the curve ranged from 0.648 to 0.925. The most common biases were in the statistical domain.
conclusionClinical prediction models aid in individualizing care for STEMI patients with NRF after primary PCI. Of the 16 included studies, we report four to have a low risk of bias and low concern with regard to our research question, which should undergo external validation with or without updating in future studies.
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