Evidence map›Paper›PMID 37240994›Full record

ArticleJournal of personalized medicine2023

Digital Rehabilitation after Knee Arthroplasty: A Multi-Center Prospective Longitudinal Cohort Study.

Julien Lebleu, Andries Pauwels, Philippe Anract, Sébastien Parratte, Philippe Van Overschelde, Stefaan Van Onsem

Abstract read
In one paragraph

Article in Journal of personalized medicine, 2023. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 10 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
10citing papers in PubMed, 1 pooled it
–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

10 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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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

6 authors.

Julien LebleumoveUP, Cantersteen 47, 1000 Brussels, Belgium.ORCID 0000-0001-6737-4830
Andries PauwelsmoveUP, Cantersteen 47, 1000 Brussels, Belgium.
Philippe AnractService de Chirurgie Orthopédique, Hopital Cochin, 75679 Paris, France.
Sébastien ParratteInternational Knee and Joint Centre, Abu Dhabi 46705, United Arab Emirates.
Philippe Van OverscheldeHip and Knee Clinic, 9830 Gent, Belgium.
Stefaan Van OnsemOrthopaedics Department, AZ Alma Eeklo, Ringlaan 15, 9900 Eeklo, Belgium.

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

Rehabilitation for total knee replacement (TKA) often involves in-person therapy sessions, which can be time consuming and costly. Digital rehabilitation has the potential to address these limitations, but most of these systems offer standardized protocols without considering the patient's pain, participation, and speed of recovery. Furthermore, most digital systems lack human support in case of need. The aim of this study was to investigate the engagement, safety, and clinical effectiveness of a personalized and adaptative app-based human-supported digital monitoring and rehabilitation program. In this prospective multi-center longitudinal cohort study, 127 patients were included. Undesired events were managed through a smart alert system. Doctors were triggered when there was a suspicion of problems. The drop-out rate, complications and readmissions, PROMS, and satisfaction were collected through the app. There was only 2% readmission. Doctor actions through the platform potentially avoided 57 consultations (85% of alerts). The adherence to the program was 77%, and 89% of the patients would recommend the use of the program. Personalized human-backed-up digital solutions can help to improve the rehabilitation journey of patients after TKA, lower healthcare-related costs by lowering the complication and readmission rate, and improve patient reported outcomes.

Indexed as

digital rehabilitationindividualizedkneemhealthtelerehabilitationtotal knee arthroplasty

Identifiers

PMID37240994
PMCPMC10224554

What OpenQuestion holds

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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.