Development and verification of a nomogram for the prediction of coronary heart disease in the Chinese Guangxi Zhuang population

Objective: The purpose of this study was to explore the independent risk factors involved in coronary heart disease (CHD), and to develop and verify a fibrinogen-based nomogram to predict its risk in the Chinese Zhuang population in Guangxi Province. Methods: Patients who underwent coronary angiography at the First Affiliated Hospital of Guangxi Medical University from January 2018 to November 2019 were included, and randomly divided into a training set and a validation set at a ratio of 7:3. After multivariate logistic regression analysis, the nomogram for the prediction of CHD was constructed. Receiver operating characteristic (ROC) curves, calibration curves and decision curve analyses (DCA) were used to evaluate the discriminatory ability of the model, and its calibration and its use as a model. Results: Multivariate logistic regression showed that males (OR = 2.22, 95% CI (1.37-3.58); P = 0.001), smoking (OR = 1.71, 95% CI (1.11-2.62); P = 0.014), hypertension (OR = 9.79, 95% CI (5.67-16.86); P < 0.001), diabetes (OR=6.32, 95%CI (2.98-13.41)); P<0.001), fibrinogen (OR = 1.74, 95% CI (1.39-2.18); P < 0.001) and triglycerides (OR = 1.43, 95% CI (1.10-1.86); P = 0.007) were independent predictors of CHD. We then use these seven risk factors to construct and predict the nomogram. Our patients’ population was 480 with 205 patients randomly assigned to the training set and verification set respectively. The AUC of the nomogram in the training and validation sets were 0.837 and 0.889. The sensitivity and specificity in the validation set were 87.7% and 80.4%. However, the training set was 79.9% and 77.7%, respectively. These results indicate that the model predicts very well the presence of CHD. In addition, the calibration curve from the validation set shows a strong consistent performance from the nomogram model, and at the same time, DCA also showed excellent results from the nomogram. Conclusions: This study found that gender (men), age, smoking, hypertension, diabetes, fibrinogen, and triglycerides were all independent risk factors for CHD. Moreover, a novel method based on a fibrinogen nomogram was developed and validated to predict the risk of CHD in the Guangxi Zhuang population. These findings help medics to assess the risk of CHD, and can be easily used for its early diagnosis and improved screening in patients at high risk of CHD