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A new risk scoring model for prediction of poor coronary collateral circulation in acute non-ST-elevation myocardial infarction
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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
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
Keywords
coronary collateral circulation, non-ST-elevation myocardial infarction, risk scoring
About this articleTitle
A new risk scoring model for prediction of poor coronary collateral circulation in acute non-ST-elevation myocardial infarction
Journal
Issue
Pages
107-113
Published online
2015-09-23
Page views
2767
Article views/downloads
1485
DOI
10.5603/CJ.a2015.0064
Pubmed
Bibliographic record
Cardiol J 2016;23(1):107-113.
Keywords
coronary collateral circulation
non-ST-elevation myocardial infarction
risk scoring
Authors
Mehmet İleri
Ümit Güray
Ertan Yetkin
Havva Tuğba Gürsoy
Pınar Türker Bayır
Deniz Şahin
Özgül Uçar Elalmış
Yahya Büyükaşık
