Prediction of no-reflow in patients with acute coronary syndromes undergoing percutaneous coronary intervention.

Abstract

Background: Suboptimal coronary reperfusion (no-reflow) is common in acute coronary syndrome (ACS) percutaneous coronary intervention (PCI) and is associated with poor outcomes. We aimed to develop and externally validate an easy-to-use clinical risk score for no-reflow for use following angiography and prior to PCI to assist in guiding preventative strategies. Methods: We developed and externally validated a logistic regression model for prediction of no-reflow among adult patients undergoing PCI for ACS using data from the Melbourne Interventional Group (MIG) PCI registry (2005-2015; development cohort) and the British Cardiovascular Intervention Society (BCIS) PCI registry (2006-2020; external validation cohort). A subset of candidate variables was selected based on previous literature and an adaptive least absolute shrinkage and selection operator (LASSO) regression approach used for final variable selection. Results: 30,561 patients (mean age 64.1 years, 24% women) were included in the MIG development cohort and 440,256 patients (mean age 64.9 years, 27% women) in the BCIS external validation cohort. The primary outcome (no-reflow) occurred in 4.1% (1,249 patients). From 33 variables, 6 were included in the score (cardiogenic shock, STEMI with delayed symptom-to-balloon time, estimated stent length, vessel diameter, pre-PCI TIMI flow, and lesion location). Model discrimination was very good in both development (C-statistic 0.81) and external validation (C-statistic 0.74) cohorts with excellent calibration. Conclusions: We developed a simple count-based scoring system based on parameters available prior to PCI to predict risk of no-reflow. This score could be useful in guiding patient selection in future preventative treatment trials.