Incorporating the STOP-BANG questionnaire improves prediction of cardiovascular events during hospitalization after myocardial infarction.

Journal: Scientific reports
Published Date:

Abstract

Obstructive sleep apnea (OSA) may impact outcomes in acute coronary syndrome (ACS) patients. The Global Registry of Acute Coronary Events (GRACE) score assesses cardiovascular risk post-ACS. This study evaluated whether incorporating the STOP-BANG score (a surrogate for OSA) enhances GRACE's predictive ability. A total of 227 myocardial infarction (MI) patients were included, with 66 (29.07%) experiencing in-hospital cardiovascular events. Patients with events were older, predominantly male, and had worse clinical markers, including lower hemoglobin and ejection fraction and higher RDW, creatinine, CRP, and GRACE scores (p < 0.001). While STOP-BANG was higher in event patients, risk group classification was non-significant (p = 0.3). Three models were trained: (1) all selected features, (2) GRACE alone, and (3) GRACE + STOP-BANG. The Extra Trees Classifier performed best (ROC-AUC = 0.82). Adding STOP-BANG improved the F1-score, accuracy, and precision but had a non-significant effect on ROC-AUC. The decision curve analysis showed an increased net benefit when STOP-BANG was incorporated. Feature importance analysis ranked STOP-BANG highest in models, reinforcing its relevance. While this study showed that STOP-BANG improved risk stratification, further multicenter validation is needed to confirm its clinical utility in ACS risk models.

Authors

  • Bahram Shahri
    Department of Cardiology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Ali Tajik
    Student Research Committee, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran.
  • Mohsen Moohebati
    Cardiovascular Research Center, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad 917791-8564, Iran.
  • Vahid Mahdavizadeh
    Department of Cardiology, Faculty of Medicine, Mashhad University of Medical Sciences, Mashhad, Iran. mahdavizadev@yahoo.com.