Evidence mapPaperPMID 40146413Full record

ArticleAging clinical and experimental research2025

Further insights into influence factors of hypertension in older patients with obstructive sleep apnea syndrome: a model based on multiple centers.

Libo Zhao, Xin Xue, Yinghui Gao, Weihao Xu, Zhe Zhao, Weimeng Cai, Dong Rui, Xiaoshun Qian, Lin Liu, Li Fan

Abstract readMulticenter Study
In one paragraph

Article in Aging clinical and experimental research, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing papers in PubMed
field-weighted citation impact
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

1 citing paper in PubMed.

  1. Article
4 · The record

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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

10 authors.

Libo Zhao *Cardiology Department of the Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
Xin Xue *Department of Respiratory and Critical Care Medicine, Affiliated Hospital of Yan'an University, Yan'an, 716000, China.
Yinghui Gao *Sleep Center, Peking University International Hospital, Beijing, 102206, China.
Weihao XuCardiology Department of Guangdong Provincial People's Hospital, Guangzhou, 510080, China.
Zhe ZhaoCardiology Department of the Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China.
Weimeng CaiGraduate School, Medical School of Chinese PLA, Beijing, 100853, China.
Dong RuiGraduate School, Medical School of Chinese PLA, Beijing, 100853, China.
Xiaoshun QianDepartment of Respiratory and Critical Care Medicine of the Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China. qianxs@yahoo.com.
Lin LiuDepartment of Respiratory and Critical Care Medicine of the Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China. liulin715@qq.com.
Li FanCardiology Department of the Second Medical Center & National Clinical Research Center for Geriatric Diseases, Chinese PLA General Hospital, Beijing, 100853, China. fl6698@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

objectiveTo construct a novel model or a scoring system to predict hypertension comorbidity in older patients with obstructive sleep apnea syndrome (OSAS).

methodsA total of 1290 older patients with OSAS from six tertiary hospitals in China were enrolled. The sample was randomly divided into a modeling set (80%) and validation set (20%) using a bootstrap method. Binary logistic regression analysis was used to identify influencing factors. According to the regression coefficients, a vivid nomogram was drawn, and an intuitive score was determined. The model and score were evaluated for discrimination and calibration. The Z-test was utilized to compare the predictive ability between the model and scoring system.

resultsIn the multivariate analysis, age, body mass index (BMI), apnea-hypopnea index (AHI), total bilirubin (TB), high-density lipoprotein cholesterol (HDL-C), and fasting blood glucose (FBG) were significant predictors of hypertension. The area under the receiver operating characteristic curve of the model in the modeling and validation sets was 0.714 and 0.662, respectively. The scoring system had predictive ability equivalent to that of the model. Moreover, the calibration curve showed that the risk predicted by the model and the score was in good agreement with the actual hypertension risk.

conclusionsThis accessible and practical correlation model and diagram can reliably identify older patients with OSAS at high risk of developing hypertension and facilitate solutions on modifying this risk most effectively.

Indexed as

HypertensionSleep Apnea, ObstructiveAgedBody Mass IndexChinaFemaleHumansMaleMiddle AgedRisk FactorsROC CurveHypertensionModelNomogramOlderOSASScoring system

Identifiers

PMID40146413
PMCPMC11950130

What Socratic holds

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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 Socratic graph.