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Predicting the no-reflow phenomenon in ST-elevation myocardial infarction patients undergoing primary percutaneous coronary intervention: a systematic review of clinical prediction models

医学 传统PCI 经皮冠状动脉介入治疗 心肌梗塞 蒂米 内科学 批判性评价 数据提取 检查表 血运重建 心脏病学 急诊医学 重症监护医学 梅德林 病理 替代医学 法学 心理学 认知心理学 政治学
作者
Reza Ebrahimi,Maryam Rahmani,Parisa Fallahtafti,Amirhossein Ghaseminejad‐Raeini,Alireza Azarboo,Arash Jalali,Mehdi Mehrani
出处
期刊:Therapeutic Advances in Cardiovascular Disease [SAGE]
卷期号:18
标识
DOI:10.1177/17539447241290438
摘要

Background: The 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. Objectives: In this study, we aim to investigate the clinical prediction models developed to predict NRF in STEMI patients undergoing primary PCI. Design: Systematic review. Data sources and methods: Preferred 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. Results: The 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. Conclusion: Clinical 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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