Evidence map›Paper›PMID 40617621›Full record

ArticleBMJ open2025

Early warning and stratification of the elderly cardiopulmonary dysfunction-related diseases: multicentre prospective study protocol.

Xiuxiu Zhou, Qianxi Jin, Yi Xia, Yu Guan, Ziwei Zhang, Zhiping Guo, Zaiyi Liu, Chuanchang Li, Yongping Bai, Yang Hou and 6 more

Abstract readClinical Trial Protocol
PubMed Full text at PMC Publisher
In one paragraph

Article in BMJ open, 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

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

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. Review
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

16 authors.

Xiuxiu ZhouDepartment of Radiology, The Second Affiliated Hospital of the Naval Medical University of the Chinese People's Liberation Army, Shanghai, Shanghai, China.
Qianxi JinDepartment of Radiology, The Second Affiliated Hospital of the Naval Medical University of the Chinese People's Liberation Army, Shanghai, Shanghai, China.ORCID http://orcid.org/0009-0006-3312-2196
Yi XiaDepartment of Radiology, The Second Affiliated Hospital of the Naval Medical University of the Chinese People's Liberation Army, Shanghai, Shanghai, China.
Yu GuanDepartment of Radiology, The Second Affiliated Hospital of the Naval Medical University of the Chinese People's Liberation Army, Shanghai, Shanghai, China.
Ziwei ZhangDepartment of Radiology, The Second Affiliated Hospital of the Naval Medical University of the Chinese People's Liberation Army, Shanghai, Shanghai, China.
Zhiping GuoFuwai Central China Cardiovascular Hospital, Zhengzhou, China.
Zaiyi LiuGuangdong Provincial People's Hospital, Guangdong, China.
Chuanchang LiDepartment of Geriatric Medicine, Xiangya Hospital Central South University, Changsha, Hunan, China.ORCID http://orcid.org/0000-0003-3453-8928
Yongping BaiXiangya Hospital Central South University, Changsha, Hunan, China.
Yang HouShengjing Hospital of China Medical University, Shenyang, China.
Min ZhouDepartment of Respiration, Shanghai Rui Jin Hospital; Shanghai Jiao Tong University School of Medicine; Shanghai, China, Shanghai, Shanghai, China.ORCID http://orcid.org/0000-0002-8718-8506
Wei-Hua LiaoXiangya Hospital Central South University, Changsha, China.ORCID http://orcid.org/0000-0002-1926-3527
Hongyu LinQingdao Central Hospital, Qingdao, China.
Ping WangHangzhou Smart Intelligent Tech Co Ltd, Hangzhou, China.
Shiyuan LiuDepartment of Radiology, The Second Affiliated Hospital of the Naval Medical University of the Chinese People's Liberation Army, Shanghai, Shanghai, China.
Li FanDepartment of Radiology, The Second Affiliated Hospital of the Naval Medical University of the Chinese People's Liberation Army, Shanghai, Shanghai, China fanli0930@163.com.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

introductionIn China, there is a lack of standardised clinical imaging databases for multidimensional evaluation of cardiopulmonary diseases. To address this gap, this study protocol launched a project to build a clinical imaging technology integration and a multicentre database for early warning and stratification of cardiopulmonary dysfunction in the elderly. METHODS AND ANALYSIS: This study employs a cross-sectional design, enrolling over 6000 elderly participants from five regions across China to evaluate cardiopulmonary function and related diseases. Based on clinical criteria, participants are categorized into three groups: a healthy cardiopulmonary function group, a functional decrease group and an established cardiopulmonary diseases group. All subjects will undergo comprehensive assessments including chest CT scans, echocardiography, and laboratory examinations. Additionally, at least 50 subjects will undergo cardiopulmonary exercise testing (CPET). By leveraging artificial intelligence technology, multimodal data will be integrated to establish reference ranges for cardiopulmonary function in the elderly population, as well as to develop early-warning models and severity grading standard models. ETHICS AND DISSEMINATION: The study has been approved by the local ethics committee of Shanghai Changzheng Hospital (approval number: 2022SL069A). All the participants will sign the informed consent. The results will be disseminated through peer-reviewed publications and conferences.

Indexed as

Early Warning ScoreLung DiseasesAgedAged, 80 and overChinaCross-Sectional StudiesEchocardiographyExercise TestFemaleHumansMaleMulticenter Studies as TopicProspective StudiesTomography, X-Ray ComputedArtificial IntelligenceCardiovascular imagingComputed tomographyPulmonary Disease, Chronic Obstructive

Identifiers

PMID40617621
PMCPMC12228462

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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.