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A nomogram based on endothelial function and conventional risk factors predicts coronary artery disease in
Xiao-Dong Huang1,2,3, Ji-Yan Lin1,3, Xian-Wei Huang1,3
1Department of Emergency, The First Affiliated Hospital of Xiamen University, Xiamen, 361003, China.
Insights
A new nomogram accurately predicts coronary artery disease (CAD) in patients with essential hypertension (EH). This tool uses flow-mediated dilation (FMD) and traditional risk factors to identify high-risk individuals.
Area of Science:
- Cardiology
- Vascular Medicine
- Clinical Prediction Modeling
Background:
- Essential hypertension (EH) patients lack precise tools for coronary artery disease (CAD) prediction.
- Existing models do not adequately incorporate vascular function markers like flow-mediated dilation (FMD).
Purpose of the Study:
- To develop and validate a clinical prediction model (nomogram) for CAD in EH patients.
- To integrate FMD measurements with traditional risk factors for improved CAD risk assessment.
Main Methods:
- Retrospective analysis of 1752 EH patients.
- Utilized high-resolution vascular ultrasound to measure FMD.
- Developed a nomogram using multivariable logistic regression and validated it on a separate cohort.
Main Results:
- The nomogram identified FMD, age, EH duration, waist circumference, and diabetes mellitus as independent predictors of CAD.
- The model demonstrated good predictive performance with AUC values of 0.799 (training) and 0.836 (validation).
- The nomogram showed excellent calibration and clinical applicability.
Conclusions:
- A nomogram incorporating FMD and traditional risk factors effectively predicts CAD in EH patients.
- This tool can aid in identifying high-risk individuals for targeted interventions.
- The model offers a precise and practical approach to CAD risk stratification in EH.
Background:
There is currently a lack of a precise, concise, and practical clinical prediction model for predicting coronary artery disease (CAD) in patients with essential hypertension (EH). This study aimed to construct a nomogram to predict CAD in patients with EH based on flow-mediated dilation (FMD) of brachial artery and traditional risk factors.
Methods:
Clinical data of 1752 patients with EH were retrospectively collected. High-resolution vascular ultrasound was used to detect FMD in all patients at the Fujian Hypertension Research Institute, China. Patients were divided into two groups, i.e. training group (n = 1204, from August 2000 to December 2013) and validation group (n = 548, from January 2014 to May 2016) according to the time of enrollment. Independent predictors of CAD were analyzed by multivariable logistic regression in the training group, and a nomogram was constructed accordingly. Finally, we evaluated the discrimination, calibration, and clinical applicability of the model using the area under curve (AUC) of receiver operating characteristic analysis, calibration curve combined with Hosmer-Lemeshow test, and decision curve, respectively.
Results:
There were 263 (21.8%) cases of EH combined with CAD in the training group. Multivariate logistic regression showed that FMD, age, duration of EH, waist circumference, and diabetes mellitus were independent influencing factors for CAD in EH patients. Smoking which was close to statistical significance (P = 0.062) was also included in the regression model to increase the accuracy. Ultimately, the nomogram for predicting CAD in EH patients was constructed according to above predictors after proper transformation. The AUC values of the training group and the validation group were 0.799 (95%CI 0.770-0.829) and 0.836 (95%CI 0.787-0.886), respectively. Calibration curve and Hosmer-Lemeshow test showed that the model had good calibration (training group: χ2 = 0.55, P = 0.759; validation group: χ2 = 1.62, P = 0.446). The decision curve also verified the clinical applicability of the nomogram.
Conclusion:
The nomogram based on FMD and traditional risk factors (age, duration of EH disease, smoking, waist circumference and diabetes mellitus) can predict CAD high-risk group among patients with EH.
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