• Hong Meng, Liang Guo, Bin Kong, Wei Shuai, and He Huang.
• Department of Cardiology, Renmin Hospital of Wuhan University, Wuhan, Hubei, PR China.
• Medicine (Baltimore). 2022 Dec 9; 101 (49): e32144e32144.

AbstractPatients with masked hypertension (MH) and masked uncontrolled hypertension (MUCH) are easily overlooked, and both cause target organ damage. We propose a prediction model for MH and MUCH patients based on clinical features at a single outpatient visit. Data collection was planned before the index test and reference standard were after. Thus, we retrospectively collect analyzed 804 subjects who underwent ambulatory blood pressure monitoring (ABPM) at Renmin Hospital of Wuhan University. These patients were divided into normotension/controlled hypertension group (n = 121), MH/MUCH (n = 347), and sustained hypertension (SH)/sustained uncontrolled hypertension group (SUCH) (n = 302) for baseline characteristic analysis. Models were constructed by logistic regression, a nomogram was visualized, and internal validation by bootstrapping. All groups were performed according to the definition proposed by the Chinese Hypertension Association. Compared with normotension/controlled hypertension, patients with MH/MUCH had higher office blood pressure (BP) and were more likely to have poor liver and kidney function, metabolic disorder and myocardial damage. By analysis, [office systolic blood pressure (OSBP)] (P = .004) and [office diastolic blood pressure (ODBP)] (P = .007) were independent predictors of MH and MUCH. By logistic regression backward stepping method, office BP, body mass index (BMI), total cholesterol (Tch), high-density lipoprotein cholesterol (HDL-C), and left ventricular mass index are contained in this model [area under curve (AUC) = 0.755] and its mean absolute error is 0.015. Therefore, the prediction model established by the clinical characteristics or relevant data obtained from a single outpatient clinic can accurately predict MH and MUCH.Copyright © 2022 the Author(s). Published by Wolters Kluwer Health, Inc.

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