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Record W4294811888 · doi:10.1097/pep.0000000000000942

Maintenance of Functional Gains Following a Goal-Directed and FES-Assisted Cycling Program for Children With Cerebral Palsy

2022· article· en· W4294811888 on OpenAlexaboutno aff
Ellen Armstrong, Roslyn N. Boyd, Sean A. Horan, Megan Kentish, Robert S. Ware, Christopher P. Carty

Bibliographic record

VenuePediatric Physical Therapy · 2022
Typearticle
Languageen
FieldMedicine
TopicCerebral Palsy and Movement Disorders
Canadian institutionsnot available
Fundersnot available
KeywordsCerebral palsyPhysical therapyCyclingPhysical medicine and rehabilitationGross motor skillMedicineFunctional electrical stimulationPsychologyIntervention (counseling)Motor skillStimulationDevelopmental psychologyInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: This study investigated whether the functional improvements associated with functional electrical stimulation-assisted cycling, goal-directed training, and adapted cycling in children with cerebral palsy were maintained 8 weeks after the intervention ceased. METHODS: The intervention (2 × 1-hour supervised sessions and 1-hour home program/week) ran for 8 weeks. Primary outcomes were the Gross Motor Function Measure (GMFM-88) and the Canadian Occupational Performance Measure (COPM). Secondary outcomes included the GMFM-66 and goal scores, 5 times sit-to-stand test (FTSTS), Participation and Environment Measure-Children and Youth (PEM-CY), Pediatric Evaluation of Disability Inventory Computer Adaptive Test (PEDI-CAT), and cycling power output (PO). Outcomes were assessed at baseline, 8 and 16 weeks. RESULTS: Twenty children participated (mean age = 10 years 3 months; SD = 2 years 11 months; Gross Motor Function Classification System II = 5, III = 6, and IV = 9). Improvements were retained above baseline at 16 weeks on the GMFM and COPM. Improvements in cycling PO, PEDI-CAT scores, PEM-CY environmental barriers and FTSTS were also retained. CONCLUSION: Functional improvements in children with cerebral palsy were retained 8 weeks post-intervention.

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 score0.216
Threshold uncertainty score0.525

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 head0.021
GPT teacher head0.286
Teacher spread0.265 · 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

Citations7
Published2022
Admission routes1
Has abstractyes

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