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Record W2040045839 · doi:10.1002/jor.21248

Comparison of joint mechanics of both lower limbs of tha patients with healthy participants during stair ascent and descent

2010· article· en· W2040045839 on OpenAlexafffund
Mario Lamontagne, Mélanie L. Beaulieu, Paul E. Beaulé

Bibliographic record

VenueJournal of Orthopaedic Research® · 2010
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsUniversity of Ottawa
FundersOttawa Hospital Research InstituteCanadian Institutes of Health ResearchUniversity of Ottawa
KeywordsAnkleMedicinePhysical medicine and rehabilitationPhysical therapyOsteoarthritisRehabilitationKinematicsProsthesisSurgery

Abstract

fetched live from OpenAlex

Total hip arthroplasty (THA) is a common surgical procedure for patients suffering from osteoarthritis to relieve their pain and to attempt to restore their normal locomotion patterns. Although this procedure does not restore normal mobility during activities of daily living, it remains unclear how it affects the joint mechanics of both lower limbs during stair negotiation tasks. Hence, we compared the 3D joint mechanics of both lower limbs of THA patients with matched healthy controls during stair ascent and stair descent. 3D kinematics and kinetics of both lower limbs were recorded for 20 patients having undergone unilateral THA and 20 healthy, age and body mass index matched control participants. The THA patients generated limited power at the operated hip joint, and thus compensated with larger power generation at the contralateral ankle to lift the body weight to the next step. This stair ambulation strategy, as well as others, adopted by the THA patients implied decreased activation of the lower limb musculature, which may be indicative of a muscle strength deficiency or a post-operatively adopted protective mechanism to unload the prosthesis. These asymmetric power production patterns should be addressed in rehabilitation programs pre- and post-operatively.

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)0.002
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.477

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
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 head0.074
GPT teacher head0.377
Teacher spread0.303 · 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

Citations48
Published2010
Admission routes2
Has abstractyes

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