Dandan Sun Zhihua Li Guomei Xu Jing Xue Wenqing Wang Ping Yin Meijuan Wang Miaomiao Shang Li Guo Qian Cui Yuchuan Dai Ran Zhang Xueting Wang Dongmei Song ^*

• Affiliated Hospital of Jining Medical University, Jining, China

Non-dipper blood pressure has been shown to affect cardiovascular outcomes and cognitive function in patients with hypertension. Although some studies have explored the influencing factors of non-dipper blood pressure, there is still relatively little research on constructing a prediction model. This study aimed to develop and validate a simple and practical nomogram prediction model and explore relevant elements that could affect the dipper blood pressure relationship in patients with hypertension. A convenient sampling method was used to select 356 inpatients with hypertension who visited the Affiliated Hospital of Jining Medical College from January 2022 to September 2022. All patients were randomly assigned to the training cohort (75%, n=267) and the validation cohort (25%, n=89). Univariate and multivariate logistic regression were utilized to identify influencing factors. The nomogram was developed and evaluated based on the receiver operating characteristic (ROC) curve, the area under the ROC curve (AUC), and decision curve analyses. The optimal cutoff values for the prevalence of dipper blood pressure were estimated. The nomogram was established using six variables, including age, sex, hemoglobin (Hb), estimated glomerular filtration rate (eGFR), ejection fraction (EF), and heart rate. The AUC was 0.860 in the training cohort. The cutoff values for optimally predicting the prevalence of dipper blood pressure were 41.50 years, 151.00 g/L, 117.53 mL/min/1.73m 2 , 64.50%, and 75 beats per minute for age, Hb, eGFR, ejection fraction, and heart rate, respectively. In summary, our nomogram can be used as a simple, plausible, affordable, and widely implementable tool to predict the blood pressure pattern of Chinese patients with hypertension.