How to Identify White Coat Hypertension at The First Diagnosis: Establishment of A Scoring Model for The Differential Diagnosis of White Coat Hypertension and Sustained Hypertension

Abstract

Background: To establish a scoring model for the differential diagnosis of white coat hypertension (WCH) and sustained hypertension (SHT). Methods: 553 adults with elevated office blood pressure, normal renal function and no antihypertensive drugs were included in this study. 17 parameters, such as gender and age, were obtained by questionnaire investigation and biochemical index detection. WCH and SHT were distinguished by 24-hour ambulatory blood pressure monitoring. Participants were randomly divided into a training set (445 cases) and a verification set (108 cases). In the training set, the above parameters were screened by LASSO regression and univariate logistic regression analysis, then, the scoring model was constructed through multivariate logistic regression analysis. ROC curve and calibration curve were used to discuss the discrimination and calibration of this scoring model respectivelyResults: 6 parameters were finally selected, namely isolated systolic hypertension, systolic blood pressure, diastolic blood pressure, triglyceride, serum creatinine, and cardiovascular and cerebrovascular diseases. Multivariate logistic regression was used to establish the scoring model. The R2 and AUC of the scoring model in the training set were 0.163 and 0.705, respectively. In the verification set, the R2 of the scoring model was 0.206, and AUC was 0.718. The calibration test results showed that the scoring model had good stability in both training set and verification set (MSE=0. 001, MAE=0. 014; MSE=0. 001, MAE=0. 025, respectively).Conclusion: A stable scoring model for distinguishing WCH can be established, which can assist clinical medical workers to identify WCH at the first diagnosis.