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Record W7146436725

A scoping review of patient-reported outcomes for post-stroke patients with lower limb orthosis

2025· article· en· W7146436725 on OpenAlexaboutno aff
Nana Tanikawa

Bibliographic record

VenueInstitutional Repositories DataBase (IRDB) · 2025
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
FundersNiigata University of Health and Welfare
KeywordsObservational studyRehabilitationLower limbStroke (engine)Randomized controlled trialQuality of life (healthcare)OrthoticsMEDLINE
DOInot available

Abstract

fetched live from OpenAlex

Gait disturbances due to hemiplegia after stroke reduce healthy life expectancy. Rehabilitation treatment guidelines in various countries recommend the use of lower limb orthoses for hemiplegia patients. Although objective outcomes such as motor function have been used to evaluate orthosis effectiveness, subjective patient-reported outcomes from orthotic users are increasingly being studied. Although patient-reported outcomes directly reflect patient health status, and tools have recently been developed to measure orthotic satisfaction, evidence on orthotic effectiveness remains limited. We conducted a scoping review to clarify the usefulness of patient-reported outcomes in evaluating the effectiveness of lower limb orthotic therapy for post-stroke hemiplegia patients. The review showed that patient-reported outcome evaluation studies on lower limb orthoses after stroke are mainly conducted in Europe, the USA, and Asia. Randomized controlled trials are frequently conducted in the USA and Europe, whereas observational studies are more common in Asia. The Quebec User Evaluation of Satisfaction with Assistive Technology 2.0 is the most frequently used patient-reported outcome measure and was found to be useful for both primary and secondary outcomes. However, owing to the limited number of studies, comprehensive evidence on the usefulness of patient-reported outcome evaluations remains lacking. Future research should focus on the international standardization and multilingual adaptation of such evaluations.

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)0.021
metaresearch head score (Gemma)0.115
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Systematic review · Consensus signal: Systematic review
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.022
Threshold uncertainty score0.111

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.115
Meta-epidemiology (narrow)0.0020.001
Meta-epidemiology (broad)0.0070.009
Bibliometrics0.0220.024
Science and technology studies0.0010.001
Scholarly communication0.0040.003
Open science0.0020.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0070.001

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 head0.011
GPT teacher head0.297
Teacher spread0.286 · 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 designSystematic review
Domainnot available
GenreReview

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

Citations0
Published2025
Admission routes1
Has abstractyes

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