The predictive value of laboratory parameters for no-reflow phenomenon in patients with ST-elevation myocardial infarction following primary percutaneous coronary intervention: A meta-analysis.

Abstract

To date, the predictive role of laboratory indicators for the phenomenon of no flow is unclear. Hence, our objective was to conduct a meta-analysis to investigate the association between laboratory parameters and the risk of the no-reflow phenomenon in patients with ST-elevation myocardial infarction (STEMI) following primary percutaneous coronary intervention (PCI). This, in turn, aims to offer valuable insights for early clinical prediction of no-reflow. We searched Pubmed, Embase, and Cochrane Library from the establishment of the database to October 2023. We included case-control or cohort study that patients with STEMI following primary PCI. We excluded repeated publication, research without full text, incomplete information or inability to conduct data extraction and animal experiments, reviews, and systematic reviews. STATA 15.1 was used to analyze the data. The pooled results indicated that elevated white blood cell (WBC) count (odds ratio [OR] = 1.061, 95% confidence interval [CI]: 1.013-1.112), neutrophil count (OR = 1.324, 95% CI: 1.128-1.553), platelet (PLT) (OR = 1.002, 95%CI: 1.000-1.005), blood glucose (OR = 1.005, 95%CI: 1.002-1.009), creatinine (OR = 1.290, 95%CI: 1.070-1.555), total cholesterol (TC) (OR = 1.022, 95%CI: 1.012-1.032),d-dimer (OR = 1.002, 95%CI: 1.001-1.004), and fibrinogen (OR = 1.010, 95%CI: 1.005-1.015) were significantly associated with increased risk of no-reflow. However, elevated hemoglobin was significantly associated with decreased risk of no-reflow. In conclusion, our comprehensive analysis highlights the predictive potential of various parameters in assessing the risk of no-reflow among STEMI patients undergoing PCI. Specifically, WBC count, neutrophil count, PLT, blood glucose, hemoglobin, creatinine, TC, d-dimer, and fibrinogen emerged as significant predictors. This refined risk prediction may guide clinical decision-making, allowing for more targeted and effective preventive measures to mitigate the occurrence of no-reflow in this patient population.