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Record W7103979776 · doi:10.2196/78307

Digital Physiotherapeutic Ankle-Specific Training System for Patients With Chronic Ankle Instability Following Modified Brostrom Surgery: Noninferiority Randomized Controlled Trial at a Tertiary Grade A Trauma Center in China

2025· article· en· W7103979776 on OpenAlexvenueno aff

Bibliographic record

VenueJMIR mhealth and uhealth · 2025
Typearticle
Languageen
FieldMedicine
TopicFoot and Ankle Surgery
Canadian institutionsnot available
Fundersnot available
KeywordsRandomized controlled trialTraining systemRehabilitationAnkleTelemedicine

Abstract

fetched live from OpenAlex

Background: Functional rehabilitation is commonly used for patients with chronic ankle instability (CAI). Digital training (DT) systems have become increasingly popular in postoperative rehabilitation; however, their effectiveness for CAI patients after modified Brostrom surgery (MBS) is uncertain. Furthermore, specialized physiotherapy resources for CAI are limited in some regions, highlighting the need for effective digital home-based rehabilitation alternatives. Objective: This trial aimed to evaluate whether individually tailored physiotherapeutic ankle-specific training (PAST) delivered via a DT system is noninferior to conventional face-to-face physiotherapy in clinical outcomes and to compare their cost-effectiveness in CAI patients following MBS in China. Methods: We conducted a 2-arm, single-blinded (assessor), noninferiority randomized controlled trial at a tertiary hospital in Shanghai, China, from January 2022 to January 2024. A total of 84 postsurgery CAI patients were randomly assigned to a DT group (n=42), which received a 12-week individualized PAST program via a digital system, or a physiotherapy group (n=42), which received standard face-to-face physiotherapy for 12 weeks. Assessments were performed at baseline, 12 weeks, and 24 weeks postoperatively. The primary outcomes were 2 subscales of the Foot and Ankle Ability Measure, with a noninferiority margin of 8 points for Foot and Ankle Ability Measure-Activities of Daily Living (FAAM-ADL) and 9 points for Foot and Ankle Ability Measure-Sports (FAAM-S). Secondary outcomes included balance tests (time-in-balance, foot-lift, and star excursion balance), functional tests (ankle dorsiflexion range of motion, side-hop, and figure-8 hop), and quality of life (FAAM questionnaire). We also collected intervention costs to evaluate cost-effectiveness. Statistical analyses included between-group comparisons of outcomes and nonparametric bootstrapping to calculate incremental cost-effectiveness ratios. Results: Baseline characteristics were similar between groups (except for a difference in foot-lift test performance). By the 24-week follow-up, improvements in the primary outcomes were comparable between the DT and physiotherapy groups, with adjusted between-group differences of 0.36 (95% CI -1.01 to 1.72) for FAAM-ADL and 1.67 (95% CI -0.61 to 3.96) for FAAM-S. These differences fell within the predefined noninferiority margins, demonstrating noninferiority of the digital program. No significant between-group differences were observed in secondary outcomes (all P>.05). The average cost per patient was lower in the DT group (CNY 53,551; an exchange rate of US $1=CNY 7 was applied) than in the physiotherapy group (CNY 59,372), yielding an incremental cost of CNY -14,451 in favor of the digital intervention. The bootstrapped incremental cost-effectiveness ratios were CNY -16,396 for FAAM-ADL and CNY -114,131 for FAAM-S, indicating that DT was more cost-effective. Conclusions: Individually tailored PAST delivered via a DT system was found to be clinically noninferior to conventional face-to-face physiotherapy and more cost-effective, supporting its use as a viable rehabilitation alternative for CAI patients after MBS.

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)0.002
metaresearch head score (Gemma)0.001
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 score0.004
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0040.002
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.032
GPT teacher head0.315
Teacher spread0.283 · 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".

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Citations0
Published2025
Admission routes1
Has abstractyes

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