School of Medicine, Tehran University of Medical Sciences, Tehran, Iran.
Tehran Heart Center, Cardiovascular Diseases Research Institute, Tehran University of Medical Sciences, Tehran, Iran.
Ther Adv Cardiovasc Dis. 2024 Jan-Dec;18:17539447241290438. doi: 10.1177/17539447241290438.
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.
In this study, we aim to investigate the clinical prediction models developed to predict NRF in STEMI patients undergoing primary PCI.
Systematic review.
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.
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.
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.
无复流(NRF)现象是介入治疗专家在 ST 段抬高型心肌梗死(STEMI)患者行经皮冠状动脉介入治疗(PCI)后的“阿喀琉斯之踵”。目前尚无针对 NRF 的明确治疗方法,预防策略对于改善发生 NRF 的患者的护理至关重要。
本研究旨在探讨用于预测行直接 PCI 的 STEMI 患者 NRF 的临床预测模型。
系统评价。
遵循系统评价和荟萃分析的首选报告项目(PRISMA)指南。纳入了针对直接 PCI 后 STEMI 患者 NRF 开发临床预测模型的研究。使用系统评价中预测模型风险偏倚评估工具(PROBAST)对纳入研究进行批判性评价。使用清单对关键评价和系统评价预测模型研究的数据提取(CHARMS)清单进行数据提取。
最常见的三个预测因子是年龄、总缺血时间和术前心肌梗死溶栓治疗血流分级。大多数纳入的研究通过各种方法(随机分割、自举法和交叉验证)对其开发的模型进行了内部验证。仅有 3 项研究(18%)对模型进行了外部验证。6 项研究(37%)报告了校准图和/或霍斯默-莱梅肖检验。报告的曲线下面积范围为 0.648 至 0.925。最常见的偏倚存在于统计学领域。
临床预测模型有助于对直接 PCI 后发生 NRF 的 STEMI 患者进行个体化治疗。在纳入的 16 项研究中,我们报告有 4 项研究的偏倚风险低,并且根据我们的研究问题,其可信度低,这些研究应在未来的研究中进行外部验证,或在验证时进行更新。