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Task-Oriented Intervention in Chronic Stroke

2006· article· en· W2063531936 on OpenAlexaff
Alain Leroux, H l ne Pinet, Sylvie Nadeau

Bibliographic record

VenueAmerican Journal of Physical Medicine & Rehabilitation · 2006
Typearticle
Languageen
FieldMedicine
TopicStroke Rehabilitation and Recovery
Canadian institutionsConcordia University
Fundersnot available
KeywordsBerg Balance ScalePhysical medicine and rehabilitationMedicineStroke (engine)Physical therapyBalance (ability)Center of pressure (fluid mechanics)Chronic strokeIntervention (counseling)Rehabilitation

Abstract

fetched live from OpenAlex

OBJECTIVE: The objective of this study was to evaluate whether, after a task-oriented exercise program, the changes in clinical measures of balance and mobility were paralleled by changes in biomechanical parameters in subjects with chronic stroke. DESIGN: Ten stroke subjects took part in an 8-wk exercise program aimed at improving balance and mobility through various functional tasks. Subjects were evaluated before and after the exercise intervention. Clinical measures included the Berg Balance Scale and the Timed-Up-and-Go and laboratory measures included ground reaction forces and center of pressure displacement during four functional tasks. RESULTS: Stroke subjects showed significant improvements (P < 0.05) in the clinical measures after completing the exercise program. Significant improvements (P < 0.05) were also found in postural steadiness during tandem stance and stool touch and in force production through the paretic lower limb during sit-to-stand. This last result was strongly correlated (r = -0.93) with the improvements on the Timed-Up-and-Go after exercise intervention. In contrast, the increase in postural steadiness was poorly correlated with the improvements on the Berg Balance Scale. CONCLUSIONS: A task-oriented exercise program might improve both clinical and laboratory measures of balance and mobility in stroke subjects. However, several correlations between the changes in clinical and laboratory measures after exercise intervention were generally weak, indicating that these outcome measures assessed different components of improvements.

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)0.001
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 score0.838
Threshold uncertainty score0.479

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0000.001
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 head0.004
GPT teacher head0.292
Teacher spread0.288 · 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

Citations104
Published2006
Admission routes1
Has abstractyes

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