title: A new risk scoring model for prediction of poor coronary collateral circulation in acute non-ST-elevation myocardial infarction.
abstract: BACKGROUND
  We aimed to investigate the clinical features associated with development of coronary collateral circulation (CCC) in patients with acute non-ST-elevation myocardial infarction (NSTEMI) and to develop a scoring model for predicting poor collateralization at hospital admission.
  
  
  METHODS
  The study enrolled 224 consecutive patients with NSTEMI admitted to our coronary care unit. Patients were divided into poor (grade 0 and 1) and good (grade 2 and 3) CCC groups.
  
  
  RESULTS
  In logistic regression analysis, presence of diabetes mellitus, total white blood cell (WBC) and neutrophil counts and neutrophil to lymphocyte ratio (NLR) were found as independent positive predictors of poor CCC, whereas older age (≥ 70 years) emerged as a negative indicator. The final scoring model was based on 5 variables which were significant at p < 0.05 level following multivariate analysis. Presence of diabetes mellitus, and elevated total WBC (≥ 7.85 × 103/μL) and neutrophil counts (≥ 6.25 × 103/μL) were assigned with 2 points; high NLR (≥ 4.5) with 1 point and older age (≥ 70 years old) with -1 point. Among 30 patients with risk score ≤ 1, 29 had good CCC (with a 97% negative predictive value). On the other hand, 139 patients had risk score ≥ 4; out of whom, 130 (with a 93.5% positive predictive value) had poor collateralization. Sensitivity and specificity of the model in predicting poor collateralization in patients with scores ≤ 1 and ≥ 4 were 99.2% (130/131) and +76.3 (29/38), respectively.
  
  
  CONCLUSIONS
  This study represents the first prediction model for degree of coronary collateralization in patients with acute NSTEMI.
authors.affiliation: Department of Cardiology, Ankara Numune Education and R esearch Hospital, Ankara, Turkey. maraspoli2020@gmail.com.
authors.forename: Mehmet
authors.initials: M
authors.lastname: İleri
authors.forename: Ümit
authors.initials: Ü
authors.lastname: Güray
authors.forename: Ertan
authors.initials: E
authors.lastname: Yetkin
authors.forename: Havva Tuğba
authors.initials: HT
authors.lastname: Gürsoy
authors.forename: Pınar Türker
authors.initials: PT
authors.lastname: Bayır
authors.forename: Deniz
authors.initials: D
authors.lastname: Şahin
authors.forename: Özgül Uçar
authors.initials: ÖU
authors.lastname: Elalmış
authors.forename: Yahya
authors.initials: Y
authors.lastname: Büyükaşık
mesh_terms: D000367:Age Factors; D000368:Aged; D016009:Chi-Square Distribution; D003097:Collateral Circulation; D003326:Coronary Circulation; D003661:Decision Support Techniques; D003920:Diabetes Mellitus / Q000175:diagnosis; D005260:Female; D006801:Humans; D016015:Logistic Models; D018655:Lymphocyte Count; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009203:Myocardial Infarction / Q000097:blood / Q000175:diagnosis / Q000503:physiopathology; D009504:Neutrophils; D010343:Patient Admission; D011237:Predictive Value of Tests; D011379:Prognosis; D011446:Prospective Studies; D018570:Risk Assessment; D012307:Risk Factors
keywords: coronary collateral circulation; non-ST-elevation myocardial infarction; risk scoring