Evidence map›Paper›PMID 39113937›Full record

ArticleFrontiers in physiology2024

Prediction of non-dipper blood pressure pattern in Chinese patients with hypertension using a nomogram model.

Dandan Sun, Zhihua Li, Guomei Xu, Jing Xue, Wenqing Wang, Ping Yin, Meijuan Wang, Miaomiao Shang, Li Guo, Qian Cui and 4 more

Abstract read
In one paragraph

Article in Frontiers in physiology, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

14 authors.

Dandan SunDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.
Zhihua LiDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.
Guomei XuDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.
Jing XueDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.
Wenqing WangDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.
Ping YinDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.
Meijuan WangDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.
Miaomiao ShangDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.
Li GuoDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.
Qian CuiDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.
Yuchuan DaiDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.
Ran ZhangDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.
Xueting WangDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.
Dongmei SongDepartment of Cardiology, Affiliated Hospital of Jining Medical University, Jining, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

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/1.73 m

Indexed as

blood pressure patterndipperhypertensionnomogramnon-dipper

Identifiers

PMID39113937
PMCPMC11303159

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