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Record W2769831445 · doi:10.1177/0008417416668370

Functional electrical stimulation therapy for severe hemiplegia: Randomized control trial revisited

2017· article· en· W2769831445 on OpenAlexvenueno aff
César Márquez-Chin, Shaghayegh Bagher, Vera Zivanovic, Miloš R. Popović

Bibliographic record

VenueCanadian Journal of Occupational Therapy · 2017
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsnot available
FundersMinisterul Cercetării, Inovării şi Digitalizării
KeywordsFunctional Independence MeasureFunctional electrical stimulationStroke (engine)Physical medicine and rehabilitationMedicineRandomized controlled trialUpper limbPhysical therapyPopulationActivities of daily livingStimulationSurgeryInternal medicine

Abstract

fetched live from OpenAlex

BACKGROUND: Stroke is the leading cause of long-term disability. Stroke survivors seldom improve their upper-limb function when their deficit is severe, despite recently developed therapies. PURPOSE: This study aims to assess the efficacy of functional electrical stimulation therapy in improving voluntary reaching and grasping after severe hemiplegia. METHOD: A post hoc analysis of a previously completed randomized control trial ( clinicaltrials.gov , No. NCT00221078) was carried out involving 21 participants with severe upper-limb hemiplegia (i.e., Fugl-Meyer Assessment-Upper Extremity [FMA-UE] ≤ 15) resulting from stroke. FINDINGS: Functional Independence Measure Self-Care subscores increased 22.8 (±6.7) points in the intervention group and 9 (±6.5) in the control group, following 40 hr of equal-intensity therapy. FMA-UE score changes were 27.2 (±13.5) and 5.3 (±11.0) for the intervention and control groups, respectively. IMPLICATIONS: The results may represent the largest upper-limb function improvements in any stroke population to date, especially in those with severe upper-limb deficit.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation 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 score0.206
Threshold uncertainty score0.717

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
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)0.0010.000

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 head0.087
GPT teacher head0.371
Teacher spread0.284 · 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 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

Citations25
Published2017
Admission routes1
Has abstractyes

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