Evidence map›Paper›PMID 42638700›Full record

SynthesisFrontiers in medicine2026

Identification of cognitive impairment in patients with hypertension: a systematic review and critical appraisal of existing models.

Yueliang Sun, Jiankang Wang, Fengling Sun, Mingpeng Shi, Xinxin Tian, Hang Shang, Wenxuan Wang, Tianying Chang, Jiajun Zhao, Yongsheng Huang and 2 more

Abstract readSystematic Review
In one paragraph

Synthesis in Frontiers in medicine, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

0numbers the graph read from it
0cells of the map it votes in
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

12 authors.

Yueliang Sun *College of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, China.
Jiankang Wang *Department of Cardiology, Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, China.
Fengling SunOrthopedic Center, Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, China.
Mingpeng ShiCollege of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, China.
Xinxin TianCollege of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, China.
Hang ShangDepartment of Geriatrics, Affiliated Hospital of Changchun University of Chinese Medicine, Changchun, China.
Wenxuan WangCollege of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, China.
Tianying ChangChangchun University of Chinese Medicine Affiliated Hospital, Changchun, China.
Jiajun ZhaoCollege of Traditional Chinese Medicine, Changchun University of Chinese Medicine, Changchun, China.
Yongsheng HuangChangchun University of Chinese Medicine Affiliated Hospital, Changchun, China.
Yingzi CuiChangchun University of Chinese Medicine Affiliated Hospital, Changchun, China.
Jiajuan GuoAcademic Affairs Office, Changchun University of Chinese Medicine, Changchun, China.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Background: Hypertension is strongly associated with cognitive impairment. Existing tools include models designed to identify prevalent cognitive impairment and a smaller number developed to predict future risk. However, their methodological quality, validation status, and reproducibility have not been systematically assessed. We conducted a systematic review and critical appraisal of existing models designed to identify cognitive impairment in patients with hypertension. Methods: Chinese and English databases were searched from inception to December 23, 2025. Studies that developed, updated, or validated a multivariable model, nomogram, score, or machine-learning tool for cognitive impairment, mild cognitive impairment, cognitive decline, subjective cognitive decline, or dementia among adults with hypertension were included. Data were extracted using CHARMS, and risk of bias was assessed with PROBAST. The synthesis emphasized model purpose, temporality, outcome definition, discrimination, calibration, validation, risk of bias, and reproducibility. Reported c-statistics were summarized descriptively because of substantial heterogeneity in study design, outcome definitions, cognitive assessment tools, and repeated model estimates from the same datasets. Results: Seventeen studies reporting 25 models were included. Most models were developed in China using cross-sectional data, with cognitive outcomes assessed using varied instruments. Reported AUCs ranged from 0.344 to 0.938; most multivariable models exceeded 0.70. Internal validation was reported in 15 studies, whereas only four conducted external validation and 11 assessed calibration. Sixteen studies were judged at high risk of bias. Reproducibility was limited: four studies provided sufficient information for independent calculation, eight were partially reproducible, and five were insufficiently reported. Common predictors included older age, lower education, depression, obesity, longer hypertension duration, greater hypertension severity, and adverse metabolic indicators. Discussion: Existing models show some ability to distinguish hypertensive patients with and without cognitive impairment, while evidence supporting future-risk prediction remains limited. Future work should prioritize prospective cohorts, standardized outcome definitions, external validation, calibration, and transparent reporting of equations, intercepts, scoring rules, code, and model objects. Systematic review registration: https://www.crd.york.ac.uk/PROSPERO/view/CRD420251157136, identifier CRD420251157136.

Indexed as

cognitive impairmentcritical appraisalhypertensionrisk predictionsystematic review

Identifiers

PMID42638700
PMCPMC13500545

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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.