Evidence map›Paper›PMID 38580439›Full record

Observational studyBMJ open respiratory research2024

Whole-course management of chronic obstructive pulmonary disease in primary healthcare: an internet of things-enabled prospective cohort study in China.

Xingru Zhao, Haonan Kang, Yunxia An, Zhiwei Xu, Meihui Wei, Quncheng Zhang, Linqi Diao, Zhiping Guo, Xiaoju Zhang

Open access · goldAbstract readObservational Study
PubMed Full text at PMC Publisher
In one paragraph

Observational study in BMJ open respiratory research, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed
1.7field-weighted citation impact, top 16% of its field
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

4 citing papers in PubMed, 4 citations in OpenAlex.

  1. A Narrative Review of the Correlation Between Comorbidity and Acute Exacerbation of COPD Patients.International journal of chronic obstructive pulmonary disease · 2026
    Review
  2. Article
  3. Article
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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

9 authors at 3 institutions in 2 countries.

Xingru Zhao *Department of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital, Zhengzhou, Henan, China.ORCID http://orcid.org/0000-0002-9607-0227
Haonan Kang *Department of Statistics and Data Science, National University of Singapore, Singapore.
Yunxia AnDepartment of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital, Zhengzhou, Henan, China.
Zhiwei XuDepartment of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital, Zhengzhou, Henan, China.
Meihui WeiDepartment of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital, Zhengzhou, Henan, China.
Quncheng ZhangDepartment of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital, Zhengzhou, Henan, China.
Linqi DiaoDepartment of Disease Control and Prevention, Health Commission of Henan Province, Zhengzhou, Henan, China.
Zhiping GuoFuwai Central China Cardiovascular Hospital, Zhengzhou, Henan, China.
Xiaoju ZhangDepartment of Respiratory and Critical Care Medicine, Zhengzhou University People's Hospital, Zhengzhou, Henan, China zhangxiaoju@zzu.edu.cn.
Zhengzhou University · CNNational University of Singapore · SGZhengzhou Central Hospital · CN

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundDespite substantial progress in reducing the global burden of chronic obstructive pulmonary disease (COPD), traditional methods to promote understanding and management of COPD are insufficient. We developed an innovative model based on the internet of things (IoT) for screening and management of COPD in primary healthcare (PHC).

methodsElectronic questionnaire and IoT-based spirometer were used to screen residents. We defined individuals with a questionnaire score of 16 or higher as high-risk population, COPD was diagnosed according to 2021 Global Initiative for COPD (Global Initiative for Chronic Obstructive Lung Disease) criteria. High-risk individuals and COPD identified through the screening were included in the COPD PHC cohort study, which is a prospective, longitudinal observational study. We provide an overall description of the study's design framework and baseline data of participants.

resultsBetween November 2021 and March 2023, 162 263 individuals aged over 18 from 18 cities in China were screened, of those 43 279 high-risk individuals and 6902 patients with COPD were enrolled in the cohort study. In the high-risk population, the proportion of smokers was higher than that in the screened population (57.6% vs 31.4%), the proportion of males was higher than females (71.1% vs 28.9%) and in people underweight than normal weight (57.1% vs 32.0%). The number of high-risk individuals increased with age, particularly after 50 years old (χ

conclusionStrategy based on IoT model help improve the detection rate of COPD in PHC. This cohort study has established a large clinical database that encompasses a wide range of demographic and relevant data of COPD and will provide invaluable resources for future research.

Indexed as

Internet of ThingsPulmonary Disease, Chronic ObstructiveAdolescentAdultCohort StudiesDisease ProgressionFemaleHumansMaleMiddle AgedPrimary Health CareProspective StudiesPulmonary Disease, Chronic Obstructive

Identifiers

PMID38580439
PMCPMC11002421
OpenAlexW4393998431

What OpenQuestion holds

Textmetadata
LicenceCC BY-NC
Read underepoch 390

Registered trials

None linked

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.