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Development of a Nomogram for Predicting Asymptomatic Coronary Artery Disease in Patients with Ischemic Stroke
Jie Yang1,2, Xinguang Yang1,2, Jun Wen3
1Department of Neurology, The Second Affiliated Hospital of GuangZhou Medical University, 250# Changgang East Road, GuangZhou, 510260, Guangdong Province, China.
Insights
This study developed a nomogram to predict asymptomatic coronary artery stenosis (CAS) in ischemic stroke patients. The tool, using clinical factors, aids in identifying high-risk individuals for better vascular event management.
Area of Science:
- Cardiology
- Neurology
- Vascular Medicine
Background:
- Coronary artery stenosis (CAS) ≥50% frequently coexists with ischemic stroke.
- This comorbidity significantly elevates the risk of major vascular events post-stroke.
Purpose of the Study:
- To develop and validate a predictive nomogram for asymptomatic coronary artery stenosis (≥50%) in ischemic stroke patients.
Main Methods:
- A cohort of 275 non-cardioembolic ischemic stroke patients was analyzed.
- Two predictive models were constructed using best subset and stepwise regression.
- A nomogram was established and assessed for discrimination and calibration.
Main Results:
- Model 1, comprising eight clinical variables, demonstrated strong predictive performance (concordance index 0.716).
- The developed nomogram showed good calibration and significant clinical utility.
- Key predictors included age, sex, NIHSS score, hypertension, glucose, HDL, LDL, and cervicocephalic artery stenosis.
Conclusions:
- A nomogram incorporating specific clinical variables can predict asymptomatic coronary artery disease (CAD) in ischemic stroke patients.
- This tool aids in identifying patients at risk for significant coronary artery stenosis.
- Further external validation is recommended to confirm the nomogram's effectiveness across diverse populations.
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.
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