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Coronary Progenitor Cells and Soluble Biomarkers in Cardiovascular Prognosis after Coronary Angioplasty
Published on: January 28, 2020
A new risk scoring model for prediction of poor coronary collateral circulation in acute non-ST-elevation myocardial
Mehmet İleri1, Ümit Güray, Ertan Yetkin
1Department of Cardiology, Ankara Numune Education and R esearch Hospital, Ankara, Turkey. maraspoli2020@gmail.com.
Insights
This study developed a scoring model to predict poor coronary collateral circulation (CCC) in NSTEMI patients. The model uses diabetes, white blood cell counts, and neutrophil-to-lymphocyte ratio to identify patients needing closer monitoring.
Area of Science:
- Cardiology
- Internal Medicine
- Biomedical Engineering
Background:
- Coronary collateral circulation (CCC) is crucial in acute non-ST-elevation myocardial infarction (NSTEMI).
- Predicting poor collateralization at hospital admission is clinically significant for NSTEMI management.
Purpose of the Study:
- To investigate clinical features associated with CCC development in NSTEMI patients.
- To create a predictive scoring model for poor collateralization upon hospital admission.
Main Methods:
- Enrolled 224 consecutive NSTEMI patients.
- Classified patients into poor (grades 0-1) and good (grades 2-3) CCC groups.
- Utilized logistic regression and multivariate analysis to identify predictors.
Main Results:
- Diabetes mellitus, elevated white blood cell (WBC) and neutrophil counts, and high neutrophil-to-lymphocyte ratio (NLR) predicted poor CCC.
- Older age (≥ 70 years) was a negative predictor.
- The developed scoring model demonstrated high positive (93.5%) and negative (97%) predictive values for poor collateralization.
Conclusions:
- This study presents the first predictive model for coronary collateralization degree in acute NSTEMI.
- The model aids in identifying NSTEMI patients at risk of poor collateralization.
- Clinical application of this model can guide timely therapeutic interventions.
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.
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