International journal of cardiology · 2025
Prediction models for no-reflow phenomenon after PCI in acute coronary syndrome patients: A systematic review.
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Li Fang, Zhang Jin-Jiang, Ruan Gui-Ji, Zhan Yue-Yun, Qiu Ai-Hua, Ye Meng-Si, Xiang Qian-Wen, Fang Hong-Cheng
Аннотация
OBJECTIVE: To comprehensively evaluate existing prediction models for the no-reflow phenomenon (NRP) after percutaneous coronary intervention (PCI) in patients with acute coronary syndrome (ACS).
METHODS: A systematic search was conducted across PubMed, Web of Science, Embase, Cochrane Library, Scopus, China National Knowledge Infrastructure (CNKI), Wanfang Database, Weipu (VIP), and the Chinese Biomedical Literature Service System (Sinomed) up until May 28, 2024, to identify studies on prediction models for the NRP in ACS patients after PCI. A qualitative synthesis was performed to assess study characteristics and model features.
RESULTS: A total of 3738 studies were retrieved, and 21 studies involving 25 prediction models were finally included. The reported incidence of NRP ranged from 3.58 % to 33.3 %. Most models were developed using logistic regression, with area under the curve (AUC) ranged from 0.637 to 0.958. Frequently reported predictors across models included Killip classification, symptom-to-balloon time, total ischemic time, and pre-PCI TIMI thrombus grade, among others. All included studies were assessed as having a high risk of bias (ROB), mainly due to inappropriate data sources and methodological limitations in the analysis domain.
CONCLUSIONS: Current prediction models for NRP after PCI in ACS patients exhibit high ROB and have not been adequately validated. Currently, no suitable prediction models are recommended for clinical decision-making. Future research should adopt more rigorous methodologies and emphasize multicenter external validation to enhance model reliability and applicability.
METHODS: A systematic search was conducted across PubMed, Web of Science, Embase, Cochrane Library, Scopus, China National Knowledge Infrastructure (CNKI), Wanfang Database, Weipu (VIP), and the Chinese Biomedical Literature Service System (Sinomed) up until May 28, 2024, to identify studies on prediction models for the NRP in ACS patients after PCI. A qualitative synthesis was performed to assess study characteristics and model features.
RESULTS: A total of 3738 studies were retrieved, and 21 studies involving 25 prediction models were finally included. The reported incidence of NRP ranged from 3.58 % to 33.3 %. Most models were developed using logistic regression, with area under the curve (AUC) ranged from 0.637 to 0.958. Frequently reported predictors across models included Killip classification, symptom-to-balloon time, total ischemic time, and pre-PCI TIMI thrombus grade, among others. All included studies were assessed as having a high risk of bias (ROB), mainly due to inappropriate data sources and methodological limitations in the analysis domain.
CONCLUSIONS: Current prediction models for NRP after PCI in ACS patients exhibit high ROB and have not been adequately validated. Currently, no suitable prediction models are recommended for clinical decision-making. Future research should adopt more rigorous methodologies and emphasize multicenter external validation to enhance model reliability and applicability.