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Development of a Nomogram for Predicting Asymptomatic Coronary Artery Disease in Patients with Ischemic Stroke
BACKGROUND: Coronary artery stenosis (CAS) ≥50% often coexists in patients with ischemic stroke, which leads to a significant increase in the occurrence of major vascular events after stroke. This study aimed to develop a nomogram for diagnosing the presence of ≥50% asymptomatic CAS in patients with...
Autores principales: | , , , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Bentham Science Publishers
2022
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Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900699/ https://www.ncbi.nlm.nih.gov/pubmed/35570518 http://dx.doi.org/10.2174/1574887117666220513104303 |
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author | Yang, Jie Yang, Xinguang Wen, Jun Huang, Jiayi Jiang, Lihong Liao, Sha Lian, Chun Yao, Haiyan Huang, Li Long, Youming |
author_facet | Yang, Jie Yang, Xinguang Wen, Jun Huang, Jiayi Jiang, Lihong Liao, Sha Lian, Chun Yao, Haiyan Huang, Li Long, Youming |
author_sort | Yang, Jie |
collection | PubMed |
description | BACKGROUND: Coronary artery stenosis (CAS) ≥50% often coexists in patients with ischemic stroke, which leads to a significant increase in the occurrence of major vascular events after stroke. This study aimed to develop a nomogram for diagnosing the presence of ≥50% asymptomatic CAS in patients with ischemic stroke. METHODS: A primary cohort was established that included 275 non-cardioembolic ischemic stroke patients who were admitted from January 2011 to April 2013 to a teaching hospital in southern China. The preoperative data were used to construct two models by the best subset regression and the forward stepwise regression methods, and a nomogram between these models was established. The assessment of the nomogram was carried out by discrimination and calibration in an internal cohort. RESULTS: Out of the two models, model 1 contained eight clinical-related variables and exhibited the lowest Akaike Information Criterion value (322.26) and highest concordance index 0.716 (95% CI, 0.654-0.778). The nomogram showed good calibration and significant clinical benefit according to calibration curves and the decision curve analysis. CONCLUSION: The nomogram, composed of age, sex, NIHSS score on admission, hypertension history, fast glucose level, HDL cholesterol level, LDL cholesterol level, and presence of ≥50% cervicocephalic artery stenosis, can be used for prediction of ≥50% asymptomatic coronary artery disease (CAD). Further studies are needed to validate the effectiveness of this nomogram in other populations. |
format | Online Article Text |
id | pubmed-9900699 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2022 |
publisher | Bentham Science Publishers |
record_format | MEDLINE/PubMed |
spelling | pubmed-99006992023-02-16 Development of a Nomogram for Predicting Asymptomatic Coronary Artery Disease in Patients with Ischemic Stroke Yang, Jie Yang, Xinguang Wen, Jun Huang, Jiayi Jiang, Lihong Liao, Sha Lian, Chun Yao, Haiyan Huang, Li Long, Youming Curr Neurovasc Res Neurology BACKGROUND: Coronary artery stenosis (CAS) ≥50% often coexists in patients with ischemic stroke, which leads to a significant increase in the occurrence of major vascular events after stroke. This study aimed to develop a nomogram for diagnosing the presence of ≥50% asymptomatic CAS in patients with ischemic stroke. METHODS: A primary cohort was established that included 275 non-cardioembolic ischemic stroke patients who were admitted from January 2011 to April 2013 to a teaching hospital in southern China. The preoperative data were used to construct two models by the best subset regression and the forward stepwise regression methods, and a nomogram between these models was established. The assessment of the nomogram was carried out by discrimination and calibration in an internal cohort. RESULTS: Out of the two models, model 1 contained eight clinical-related variables and exhibited the lowest Akaike Information Criterion value (322.26) and highest concordance index 0.716 (95% CI, 0.654-0.778). The nomogram showed good calibration and significant clinical benefit according to calibration curves and the decision curve analysis. CONCLUSION: The nomogram, composed of age, sex, NIHSS score on admission, hypertension history, fast glucose level, HDL cholesterol level, LDL cholesterol level, and presence of ≥50% cervicocephalic artery stenosis, can be used for prediction of ≥50% asymptomatic coronary artery disease (CAD). Further studies are needed to validate the effectiveness of this nomogram in other populations. Bentham Science Publishers 2022-11-25 2022-11-25 /pmc/articles/PMC9900699/ /pubmed/35570518 http://dx.doi.org/10.2174/1574887117666220513104303 Text en https://creativecommons.org/licenses/by/4.0/This is an Open Access article published under CC BY 4.0 https://creativecommons.org/licenses/by/4.0/legalcode |
spellingShingle | Neurology Yang, Jie Yang, Xinguang Wen, Jun Huang, Jiayi Jiang, Lihong Liao, Sha Lian, Chun Yao, Haiyan Huang, Li Long, Youming Development of a Nomogram for Predicting Asymptomatic Coronary Artery Disease in Patients with Ischemic Stroke |
title | Development of a Nomogram for Predicting Asymptomatic Coronary Artery Disease in Patients with Ischemic Stroke |
title_full | Development of a Nomogram for Predicting Asymptomatic Coronary Artery Disease in Patients with Ischemic Stroke |
title_fullStr | Development of a Nomogram for Predicting Asymptomatic Coronary Artery Disease in Patients with Ischemic Stroke |
title_full_unstemmed | Development of a Nomogram for Predicting Asymptomatic Coronary Artery Disease in Patients with Ischemic Stroke |
title_short | Development of a Nomogram for Predicting Asymptomatic Coronary Artery Disease in Patients with Ischemic Stroke |
title_sort | development of a nomogram for predicting asymptomatic coronary artery disease in patients with ischemic stroke |
topic | Neurology |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9900699/ https://www.ncbi.nlm.nih.gov/pubmed/35570518 http://dx.doi.org/10.2174/1574887117666220513104303 |
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