Nomogram for Predicting the Severity of Coronary Artery Disease in Young Adults ≤45 Years of Age with Acute Coronary Syndrome.
Background: A non-invasive predictive model has not been established to identify the severity of coronary lesions in young adults with acute coronary syndrome (ACS). Methods: In this retrospective study, 1088 young adults (≤45 years of age) first diagnosed with ACS who underwent coronary angiography...
| Publicado en: | Cardiovascular Innovations & Applications (CVIA) Vol. 7; no. 1; pp. 1 - 11 |
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| Autores principales: | , , , , , |
| Formato: | research tables/charts Journal Article |
| Publicado: |
Compuscript Ltd
2022
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| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=162533417&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 162533417 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 20098618 LW63 jtl: Cardiovascular Innovations & Applications (CVIA) issn: 20098618 maglogo: N pubinfo: dt: 2022 vid: 7 iid: 1 pid: 95705 pub: Compuscript Ltd artinfo: ui: 162533417 162533417 162533417 10.15212/CVIA.2022.0016 162533417 ppf: 1 ppct: 10 formats: tig: atl: Nomogram for Predicting the Severity of Coronary Artery Disease in Young Adults ≤45 Years of Age with Acute Coronary Syndrome. aug: au: Xulin Hong Duanbin Li Xinrui Yang Guosheng Fu Chenyang Jiang Wenbin Zhang affil: Department of Cardiology, Sir Run Run Shaw Hospital, School of Medicine, Zhejiang University, Hangzhou, Zhejiang, China sug: subj: Coronary Arteriosclerosis Diagnosis Severity of Illness Evaluation Noninvasive Procedures Prediction Models Evaluation Models, Statistical Evaluation Predictive Value of Tests Evaluation Human Male Female Adult Middle Age China Retrospective Design Record Review Validity ROC Curve Confidence Intervals Coronary Arteriosclerosis Risk Factors Descriptive Statistics Data Analysis Software Mann-Whitney U Test Chi Square Test Fisher's Exact Test Logistic Regression Adult: 19-44 years Middle Aged: 45-64 years Male Female ab: Background: A non-invasive predictive model has not been established to identify the severity of coronary lesions in young adults with acute coronary syndrome (ACS). Methods: In this retrospective study, 1088 young adults (≤45 years of age) first diagnosed with ACS who underwent coronary angiography were enrolled and randomized 7:3 into training or testing datasets. To build the nomogram, we determined optimal predictors of coronary lesion severity with the Least Absolute Shrinkage and Selection Operator and Random Forest algorithm. The predictive accuracy of the nomogram was assessed with calibration plots, and performance was assessed with the receiver operating characteristic curve, decision curve analysis and the clinical impact curve. Results: Seven predictors were identified and integrated into the nomogram: age, hypertension, diabetes, body mass index, low-density lipoprotein cholesterol, mean platelet volume and C-reactive protein. Receiver operating characteristic analyses demonstrated the nomogram's good discriminatory performance in predicting severe coronary artery disease in young patients with ACS in the training (area under the curve 0.683, 95% confidence interval [0.645-0.721]) and testing (area under the curve 0.670, 95% confidence interval [0.611-0.729]) datasets. The nomogram was also well-calibrated in both the training (P = 0.961) and testing (P = 0.302) datasets. Decision curve analysis and the clinical impact curve indicated the model's good clinical utility. Conclusion: A simple and practical nomogram for predicting coronary artery disease severity in young adults =45 years of age with ACS was established and validated. pubtype: Academic Journal doctype: research tables/charts Journal Article ougenre: Article language: English refInfo: holdings: @attributes: islocal: N |
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