Evidence map›Paper›PMID 41256352›Full record

ArticleWorld journal of clinical cases2025

Digitally assisted

Maryam Salimi, Alireza Keshtkar, Seyedarad Mosalamiaghili, Arash Sharafatvaziri, Brian T Feeley

Abstract read
In one paragraph

Article in World journal of clinical cases, 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

5 authors.

Maryam SalimiDepartment of Orthopedic Surgery, University of Texas Health Sciences Center, McGovern Medical School, Houston, TX 77030, United States.
Alireza KeshtkarResearch Center for Noncommunicable Diseases, Jahrom University of Medical Sciences, Jahrom 7414846199, Iran.
Seyedarad MosalamiaghiliGolestan Rheumatology Research Center, Biomedical Research Institute, Golestan University of Medical Sciences, Gorgan 4918936316, Golestān, Iran.
Arash SharafatvaziriCenter for Orthopedic Trans-Disciplinary Applied Research, Tehran University of Medical Sciences, Tehran 1914953616, Iran.
Brian T FeeleyDepartment of Orthopaedic Surgery, Sports Medicine and Shoulder Surgery, University of California San Francisco, San Francisco, CA 94158, United States. brian.feeley@ucsf.edu.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundRotator cuff tears are a chief cause of shoulder pain and disability, and surgical repair is often required when conservative management fails. As digital health technologies have expanded, especially since the coronavirus disease 2019 pandemic, digitally augmented rehabilitation programs emerged as a potential alternative to conventional physical therapy.

aimTo determine if digitally assisted rehabilitation could be as practical, or even more effective, than the traditional methods most patients currently follow.

methodsSix electronic databases, including PubMed, Scopus, Cochrane Library, Google Scholar, EMBASE, and Web of Science, were searched to find articles that compare digital-based rehabilitation and conventional treatment. Outcomes of interest were Disabilities of the Arm, Shoulder and Hand (DASH) score and range of motion. The quality assessment of the included studies was performed using the risk-of-bias tool for randomized trials tool.

resultsThree randomized controlled trial studies were enrolled in this study, including 195 cases. We did not find any significant differences between the two groups in terms of DASH score, flexion range of motion, and external rotation range of motion. There was a significant difference between the two groups for abduction range of motion.

conclusionDigital home-based rehab seems to be a strong alternative to traditional methods, offering similar results for people recovering from rotator cuff surgery. This approach might also make rehab more accessible and engaging for patients. That said, further research is needed to fully understand the potential of digital rehabilitation and ensure it works effectively for everyone.

Indexed as

Arthroscopic rotator cuff repairDigital therapeuticHome-based rehabilitationShoulder rehabilitation

Identifiers

PMID41256352
PMCPMC12620810

What OpenQuestion holds

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LicenceCC BY-NC
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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.