Nomogram for Predicting the Severity of Coronary Artery Disease in Young Adults ≤45 Years of Age with Acute Coronary Syndrome
نویسندگان
چکیده
Background: A non-invasive predictive model has not been established to identify the severity of coronary lesions in young adults with acute syndrome (ACS). Methods: In this retrospective study, 1088 (≤45 years age) first diagnosed ACS who underwent angiography were enrolled and randomized 7:3 into training or testing datasets. To build nomogram, we determined optimal predictors lesion Least Absolute Shrinkage Selection Operator Random Forest algorithm. The accuracy nomogram was assessed calibration plots, performance receiver operating characteristic curve, decision curve analysis clinical impact curve. Results: Seven identified integrated nomogram: age, hypertension, diabetes, body mass index, low-density lipoprotein cholesterol, mean platelet volume C-reactive protein. Receiver analyses demonstrated nomogram’s good discriminatory predicting severe artery disease patients (area under 0.683, 95% confidence interval [0.645–0.721]) 0.670, [0.611–0.729]) also well-calibrated both (P=0.961) (P=0.302) Decision indicated model’s utility. Conclusion: simple practical for adults≤45 age validated.
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ژورنال
عنوان ژورنال: Cardiovascular innovations and applications
سال: 2022
ISSN: ['2009-8782', '2009-8618']
DOI: https://doi.org/10.15212/cvia.2022.0016