Evidence map›Paper›PMID 41742927›Full record

ArticleMissouri medicine

Trends and Determinants of Blood Pressure Control in US Hypertensive Patients: Insights from NHANES 1999-2021.

Yiming Shi, Ke Xie, Zhichen Xu, Jingyi Zhang, Lei Liu

Abstract read
In one paragraph

Article in Missouri medicine. 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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0citing papers in PubMed
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1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

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Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

0 citing papers in PubMed.

No citing paper in PubMed yet.

4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

5 authors.

Yiming ShiCenter for Biostatistics and Data Science, Washington University School of Medicine, St. Louis, Missouri, USA.
Ke XieCenter for Biostatistics and Data Science, Washington University School of Medicine, St. Louis, Missouri, USA.
Zhichen XuDepartment of Statistics and Data Science, Washington University, St. Louis, Missouri, USA.
Jingyi ZhangDepartment of Neurology, Washington University School of Medicine, St. Louis, Missouri, USA.
Lei LiuCenter for Biostatistics and Data Science, Washington University School of Medicine, St. Louis, Missouri, USA.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

This study analyzes trends and determinants of blood pressure control among hypertensive patients in the United States (US) using National Health and Nutrition Examination Survey NHANES data from 1999 to 2021. Blood pressure control rates improved through 2013 but declined thereafter. Applying machine learning methods such as XGBoost, we identify hypertension awareness and antihypertensive medication use as the strongest predictors of successful control. In contrast, resistant hypertension, chronic kidney disease, and elevated low-density lipoprotein (LDL) levels are associated with poorer control. The shift from JNC7 to JNC8 hypertension guidelines reclassified some individuals from uncontrolled to controlled, influencing observed trends. Additionally, a reduction in antihypertensive medication use among female patients may have contributed to the recent decline. These findings highlight the critical role of medication adherence and patient awareness in maintaining blood pressure control.

Indexed as

Blood Pressure ControlHypertensionMachine LearningTime Trend Analysis

Identifiers

PMID41742927
PMCPMC12931589

What OpenQuestion holds

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.