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Record W2100208010 · doi:10.2522/ptj.20100163

Volitional Muscle Strength in the Legs Predicts Changes in Walking Speed Following Locomotor Training in People With Chronic Spinal Cord Injury

2011· article· en· W2100208010 on OpenAlexafffund
Jaynie F. Yang, Jonathan Norton, Jennifer Nevett-Duchcherer, François D. Roy, Douglas P. Gross, Monica A. Gorassini

Bibliographic record

VenuePhysical Therapy · 2011
Typearticle
Languageen
FieldMedicine
TopicSpinal Cord Injury Research
Canadian institutionsUniversity of Alberta HospitalUniversity of Alberta
FundersCanadian Institutes of Health Research
KeywordsPhysical medicine and rehabilitationSpinal cord injurySpinal cordMedicineMuscle strengthPhysical therapyStrength trainingNeurosciencePsychology

Abstract

fetched live from OpenAlex

BACKGROUND: It is unclear which individuals with incomplete spinal cord injury best respond to body-weight-supported treadmill training. OBJECTIVE: The purpose of this study was to determine the factors that predict whether a person with motor incomplete spinal cord injury will respond to body-weight-supported treadmill training. DESIGN: This was a prognostic study with a one-group pretest-posttest design. METHODS: Demographic, clinical, and electrophysiological measurements taken prior to training were examined to determine which measures best predicted improvements in walking speed in 19 individuals with chronic (>7 months postinjury), motor-incomplete spinal cord injuries (ASIA Impairment Scale categories C and D, levels C1-L1). RESULTS: Two initial measures correlated significantly with improvements in walking speed: (1) the ability to volitionally contract a muscle, as measured by the lower-extremity manual muscle test (LE MMT) (r=.72), and (2) the peak locomotor electromyographic (EMG) amplitude in the legs (r=.56). None of the demographics (time since injury, age, body mass index) were significantly related to improvements in walking speed, nor was the clinical measure of balance (Berg Balance Scale). Further analysis of LE MMT scores showed 4 key muscle groups were significantly related to improvements in walking speed: knee extensors, knee flexors, ankle plantar flexors, and hip abductors (r=.82). Prediction using the summed MMT scores from those muscles and peak EMG amplitude in a multivariable regression indicated that peak locomotor EMG amplitude did not add significantly to the prediction provided by the LE MMT alone. Change in total LE MMT scores from the beginning to the end of training was not correlated with a change in walking speed over the same period. LIMITATIONS: The sample size was limited, so the results should be considered exploratory. CONCLUSIONS: The results suggest that preserved muscle strength in the legs after incomplete spinal cord injury, as measured by MMT, allows for improvements in walking speed induced by locomotor training.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.768
Threshold uncertainty score0.590

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.095
GPT teacher head0.374
Teacher spread0.280 · 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

Citations47
Published2011
Admission routes2
Has abstractyes

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