BMC Cardiovascular Disorders (Apr 2023)

A nomogram based on endothelial function and conventional risk factors predicts coronary artery disease in hypertensives

  • Xiao-Dong Huang,
  • Ji-Yan Lin,
  • Xian-Wei Huang,
  • Ting-Ting Zhou,
  • Liang-Di Xie

DOI
https://doi.org/10.1186/s12872-023-03235-6
Journal volume & issue
Vol. 23, no. 1
pp. 1 – 8

Abstract

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Abstract 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: χ 2 = 0.55, P = 0.759; validation group: χ 2 = 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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