Evidence map›Paper›PMID 41947127›Full record

Trial reportBiomedical engineering online2026

A randomised controlled study of the efficacy of Internet of Things-based telerespiratory rehabilitation for chronic respiratory diseases.

Mengmeng Wu, Wenjuan Xu, Xin Zhao, Ningning Fang, Kaishu Li

Abstract readRandomized Controlled Trial
In one paragraph

Trial report in Biomedical engineering online, 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
–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

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.

Mengmeng WuDepartment of Respiratory and Critical Care Medicine, Binzhou People's Hospital Affiliated to Shandong First Medical University, No. 515, Huanghe 7th Road, Binzhou, 256610, China.
Wenjuan XuDepartment of Respiratory and Critical Care Medicine, Binzhou People's Hospital Affiliated to Shandong First Medical University, No. 515, Huanghe 7th Road, Binzhou, 256610, China. 122396592@qq.com.
Xin ZhaoDepartment of Cardiovascular Medicine, Binzhou People's Hospital Affiliated to Shandong First Medical University, Binzhou, 256610, China.
Ningning FangDay Ward, Binzhou People's Hospital Affiliated to Shandong First Medical University, Binzhou, 256610, China.
Kaishu LiDepartment of Respiratory and Critical Care Medicine, Binzhou People's Hospital Affiliated to Shandong First Medical University, No. 515, Huanghe 7th Road, Binzhou, 256610, China. 15954318626@163.com.

Funding

Institute-level project XJ2023011303
6 · The paper itself

Abstract

objectiveTo explore IoT-based remote respiratory rehabilitation for chronic respiratory disease patients at home.

designThis was a randomised controlled trial.

settingThe study took place in patients' homes (post-discharge) and the Department of Respiratory and Critical Care Medicine of Binzhou People's Hospital, Shandong First Medical University (inpatient period).

participants123 patients (mean age 68.85 ± 10.72 years, 55% male) with chronic respiratory diseases.

interventionsPatients were randomly assigned to either a 6-month Internet of Things (IoT)-based remote respiratory rehabilitation programme after hospital discharge (study group, n = 60) or usual care with conventional respiratory rehabilitation (control group, n = 63).

main outcome measuresThe primary outcomes were the 6-min walking test (6MWT) and lung function (forced vital capacity [FVC], forced expiratory volume in 1 s [FEV1] and peak expiratory flow [PEF]). The secondary outcomes included the modified Medical Research Council (mMRC) dyspnoea index, diaphragm thickness and rehospitalisation rate. Outcomes were assessed at baseline (during hospitalisation, approximately 4 weeks before the intervention started) and after 6 months.

resultsThe study group showed significantly greater improvements in 6MWT (mean difference 63.74 m, 95% CI 45.21-82.27), FVC (0.54 L, 95% CI 0.43-0.65), FEV1 (0.68 L, 95% CI 0.54-0.82), PEF (73.16 L/min, 95% CI 46.22-100) and diaphragm thickness (6.79 mm, 95% CI 4.68-8.90) than the control group (all p < 0.001). The between-group difference in 6MWT (63.74 m) exceeded the minimal clinically important difference (30 m) for chronic respiratory diseases.

conclusionA 6-month IoT-based remote respiratory rehabilitation programme significantly improved exercise capacity, lung function, dyspnoea index and respiratory muscle strength and reduced rehospitalisations when compared with conventional rehabilitation in patients with chronic respiratory diseases.

Indexed as

Internet of ThingsAgedChronic DiseaseFemaleHumansMaleMiddle AgedTreatment OutcomeChronic respiratory diseasesInternet of ThingsRehabilitation outcomesRemote rehabilitationTelerespiratory rehabilitation

Identifiers

PMID41947127
PMCPMC13214317

What Socratic holds

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LicenceCC BY-NC-ND
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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 Socratic graph.