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Record W4411330402 · doi:10.2196/71022

Recovery of Patient-Reported Outcome Measures vs Gait Parameters Obtained by Instrumented Insoles After Tibial and Malleolar Fractures: Prospective Longitudinal Observational Study

2025· article· en· W4411330402 on OpenAlexvenueno aff
Elke Warmerdam, Marianne Huebner, Angela K. Lange, Bergita Ganse

Bibliographic record

VenueJMIR mhealth and uhealth · 2025
Typearticle
Languageen
FieldEngineering
TopicLower Extremity Biomechanics and Pathologies
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePhysical therapyObservational studyPhysical medicine and rehabilitationGaitRehabilitationmHealthProspective cohort studySurgeryPsychological intervention

Abstract

fetched live from OpenAlex

BACKGROUND: New technologies from the field of mobile health (mHealth) are increasingly used to improve patient monitoring during rehabilitation. While in recent years, mobile phones, health apps, personal digital assistants, and smartwatches opened up new diagnostic and monitoring opportunities for patients, the development of innovative sensor devices, such as instrumented insoles, has now reached a sufficient level of usability with promising opportunities for clinical practice. According to research on the best method for monitoring recovery after musculoskeletal injury or surgery, the Patient-Reported Outcome Measurement Information System (PROMIS) and wearables such as instrumented insoles are among the most promising newer options. However, it is unknown how a patient's health perception and improvements in instrumented insole-derived gait parameters correlate after surgery for tibial or malleolar fractures. OBJECTIVE: This study aimed to compare the longitudinal trajectories in separate PROMIS (sub)scores with gait and further patient-specific parameters, as well as associations between PROMIS scores and gait parameters. It was also aimed to determine the influence of anthropometric parameters and comorbidities. METHODS: A total of 85 patients (39 women and 46 men; average age 50.8, SD 17.1 years) requiring surgery after tibial or malleolar fractures were included in this prospective longitudinal observational study. In the hospital and during follow-up visits, the patients completed the PROMIS Global Health and Pain Interference questionnaires. During the same visits, individually fitted instrumented insoles with 16 pressure sensors, an accelerometer, and a gyroscope each were used to assess the maximal force, pressure distribution, and angular velocity during walking with data being recorded at 100 Hz. Statistical analyses were conducted using linear mixed effect models, pairwise Spearman correlation coefficients, and generalized additive models. RESULTS: The gait parameters assessed via the instrumented insoles quickly improved during the first 3 months after surgery, followed by a slowing of further improvement. After surgery, the PROMIS scores increased or decreased to extrema that were reached after 6 weeks to 3 months, followed by a return to preinjury values. Between 3 and 6 months, no significant improvements in PROMIS scores were observed. Between 6 months and 1 year, the Physical Health and Mental Health scores still improved significantly (P=.003 in both cases). Men had better Physical Health and lower Pain Interference scores than women (P=.01 and P=.03, respectively). Hypertension had a negative effect on the Physical Health score (P=.03). The associations between the PROMIS score and gait parameters were strongest at approximately 3 months after surgery, predominantly between the Pain Interference score and gait parameters. CONCLUSIONS: The patients' perception improved later than the objective gait parameters obtained by instrumented insoles did. When the gait pattern improved, pain perception correlated with the gait parameters. TRIAL REGISTRATION: German Clinical Trials Registry DRKS00025108; https://drks.de/search/en/trial/DRKS00025108.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.012
Threshold uncertainty score0.849

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.062
GPT teacher head0.328
Teacher spread0.266 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
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

Citations3
Published2025
Admission routes1
Has abstractyes

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