MétaCan
Menu
Back to cohort
Record W2167874889 · doi:10.1191/0269215506cr958oa

Gait analysis and WOMAC are complementary in assessing functional outcome in total hip replacement

2006· article· en· W2167874889 on OpenAlexfundaboutno aff
Ulrich Lindemann, Clemens Becker, R. Muche, Kamiar Aminian, H. Dejnabadi, Th. Nikolaus, W. Puhl, K. Huch, Karsten Dreinhöfer

Bibliographic record

VenueClinical Rehabilitation · 2006
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
FundersMcMaster University
KeywordsWOMACGaitPhysical therapyMedicineGait analysisOsteoarthritisPhysical medicine and rehabilitationHip replacementProspective cohort studyQuality of life (healthcare)Orthopedic surgerySurgery

Abstract

fetched live from OpenAlex

OBJECTIVE: To investigate the correlation between objective and subjective evaluation of patients with total hip replacement. DESIGN: Prospective preliminary trial comparing the Western Ontario and McMaster University questionnaire (WOMAC) and gait analysis preoperatively and three months postoperatively. SETTING: A German academic orthopaedic centre specializing in total hip replacement surgery. SUBJECTS: Seventeen patients (median age 70 years) with hip osteoarthritis. INTERVENTION: All patients had had a primary unilateral total hip replacement. MAIN MEASURES: WOMAC questionnaire to assess self-perceived health status and gait analysis to determine objective gait parameters. RESULTS: Performance of walking as well as subjective judgement of health status improved following surgery (gait speed P = 0.0222; stride length P = 0.038; stance phase ratio P = 0.0466; WOMAC P < 0.0001). However, the correlation between gait parameters and WOMAC was poor (r = -0.27 or less). Correlation between changes of walking parameters and WOMAC was bad to good (r = 0.01 to r = -0.72). CONCLUSION: The WOMAC questionnaire might not reflect walking performance. The addition of gait analysis is recommended to gain objective information about the quality of gait.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.509

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
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 head0.048
GPT teacher head0.389
Teacher spread0.341 · 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

Citations87
Published2006
Admission routes2
Has abstractyes

Explore more

Same venueClinical RehabilitationSame topicTotal Knee Arthroplasty OutcomesFrench-language works237,207