Evidence map›Paper›PMID 42175423›Full record

ArticleMedicine2026

Applying digital technologies for remote care in the real life context: A 3-year experimentation with postoperative lung cancer patients.

Dongfang Tang, Jing Wang, Wentao Fu, Fuzhi Yang, Nianping Mo, Saitian Li, Yuxu Niu, Yingting Wu, Huibiao Zhang, Xiaoyong Shen and 1 more

Abstract read
In one paragraph

Article 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
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0citing papers in PubMed
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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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0 citing papers in PubMed.

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4 · The record

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5 · Who and what money

Authors and funding

11 authors.

Dongfang TangDepartment of Thoracic Surgery, Shanghai Huadong Hospital, Fudan University School of Medicine, Shanghai City, China.
Jing Wang
Wentao Fu
Fuzhi Yang
Nianping Mo
Saitian Li
Yuxu Niu
Yingting Wu
Huibiao Zhang
Xiaoyong Shen

Funding

National Key R&D Program for Intergovernmental International Science and Technology Innovation Cooperation Key Project 2019YFE0105600
6 · The paper itself

Abstract

Surgery remains the main curative treatment for lung cancer patients. However, operation has resulted in some-degree reduction in postoperative pulmonary function. The decreased pulmonary function could be rehabilitated to the preoperative level through restoring exercise, which is related to the ways and exercise time of rehabilitating. The Dignio platform is 1 digital telemedicine system and has been used maturely in Norway, however, it has not yet been widely promoted in China. In the present study, we adopted the telemedicine system, according to the formulated rehabilitation exercise program, to design a good way to recover pulmonary function for postoperative lung cancer patients, promoting early and quick recovery, and reducing the long-term postoperative complications and outpatient visits. This retrospective controlled study enrolled 250 postoperative lung cancer patients using a remote digital care platform and 250 matched controls receiving standard instructions. In the postoperative 1-week follow-up, we found that the forced expiratory volume in 1 second (FEV1), forced vital capacity (FVC), forced expiratory volume in 6 seconds, FVC25-75, peak expiratory flow had an obvious upward trend, although there were no significant differences in the measurements on postoperative day 7 compared with day 1. From the long-term data at 1 month/3 months/6 months post-operation, we found that the recovery was better to varying degrees in the experiment group using the remote care digital platform, compared with that of the control, especially the FEV1 at 3 (P = .065) and 6 months post-operation (P = .037), and forced Expiratory Flow between 25% and 75% of forced vital capacity at 3 months post-operation (P = .084). However, most pulmonary values, such as the FEV1/FVC, FVC and peak expiratory flow have no significant difference (all P > .05) in the recovery at 1 month post-operation between the experimental group and control, the second time at 3 months and the third time at 6 months after surgery. Especially in the experimental group, 2 patients with sudden pneumothorax were timely detected after discharge through the Digino platform, the patient returned to the hospital in time, and both patients were out of danger ultimately. The Digino remote care indeed has some benefit in the pulmonary function recovery in the long-term follow up, and reduces postoperative complications obviously.

Indexed as

Lung NeoplasmsPostoperative ComplicationsAgedChinaDigital HealthFemaleForced Expiratory VolumeHumansMaleMiddle AgedPostoperative CarePostoperative PeriodRemote Patient MonitoringRespiratory Function TestsRetrospective StudiesTelemedicinedigital technologylung cancerpulmonary functionremote care

Identifiers

PMID42175423
PMCPMC13200953

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LicenceCC BY
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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.