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Record W4324129339 · doi:10.1186/s12891-023-06270-8

The effect of a digital-assisted group rehabilitation on clinical and functional outcomes after total hip and knee arthroplasty—a prospective randomized controlled pilot study

2023· article· en· W4324129339 on OpenAlexaboutno aff
Judith Osterloh, Franziska Knaack, Rainer Bader, Martin Behrens, Juliana Peschers, Lisa Nawrath, Philipp Bergschmidt, Martin Darowski

Bibliographic record

VenueBMC Musculoskeletal Disorders · 2023
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical therapyWOMACRehabilitationTimed Up and Go testRandomized controlled trialArthroplastyOsteoarthritisQuality of life (healthcare)Sports medicineOrthopedic surgeryKnee replacementPhysical medicine and rehabilitationSurgeryBalance (ability)

Abstract

fetched live from OpenAlex

BACKGROUND: The rising number of total hip and knee arthroplasties and the decreasing availability of physiotherapists require clinically and economically effective rehabilitation approaches. Therefore, the present pilot study investigated the effect of a novel digital-assisted individualized group rehabilitation program on clinical and functional outcomes after total hip and knee arthroplasty. METHODS: In this randomized controlled pilot study, 26 patients undergoing total knee or hip replacement were randomly assigned to either the intervention group (IG, novel digital-assisted group therapy) or the control group (CG, standard postoperative physiotherapy currently carried out in Germany). The IG received the novel digital-assisted group therapy twice per week for a six-months period, while the CG received individual outpatient therapy depending on the prescription of the supervising physician. The number of therapy sessions was recorded. Moreover, subjective outcomes (EuroQol-5Dimensions (EQ-5D) and Western Ontario and McMaster Universities Osteoarthritis Index (WOMAC)), functional outcome (30 s sit to stand test and timed up and go test (TUG)), as well as gait parameters were quantified preoperatively as well as at three and six months after surgery. Data were analyzed using an analysis of covariance with baseline-adjustment. RESULTS: No patient-reported falls, pain, and hospital readmissions were recorded. On average, the IG received more therapy sessions. The clinical and functional outcomes were mainly not significantly different between groups at three- and six-months follow-up, but medium to large effect sizes for the differences in quality of life (EQ-5D) as well as pain, stiffness, and physical function (WOMAC), and TUG performance were observed in favor of the IG. However, the IG showed a higher variability of gait velocity after total joint replacement. CONCLUSION: The digital-assisted rehabilitation had positive effects on quality of life, pain, stiffness, physical function, and TUG performance. Nevertheless, the therapy concept may be improved by adding exercises focusing on gait performance to reduce gait variability. The results indicate that the digital-assisted therapy concept is effective and safe. Therefore, a consecutive full-scaled randomized controlled clinical trial is recommended. TRIAL REGISTRATION: This study was retrospectively registered on 14/02/2022 in the German Clinical Trial Register (DRKS00027960).

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Randomized trial · Consensus signal: Randomized trial
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.023

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0010.001
Science and technology studies0.0010.002
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0050.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.012
GPT teacher head0.291
Teacher spread0.279 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designRandomized trial
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations11
Published2023
Admission routes1
Has abstractyes

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