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Record W3166737451 · doi:10.1177/03635465211016853

The Minimal Clinically Important Difference (MCID) for the WOMAC and Factors Related to Achievement of the MCID After Medial Opening Wedge High Tibial Osteotomy for Knee Osteoarthritis

2021· article· en· W3166737451 on OpenAlexaboutno aff
Man Soo Kim, In Jun Koh, Keun Young Choi, Yong Gyu Sung, Dong Chul Park, Hyo Jin Lee, Yong In

Bibliographic record

VenueThe American Journal of Sports Medicine · 2021
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsWOMACMinimal clinically important differenceMedicineOsteoarthritisHigh tibial osteotomyPhysical therapyKnee painSurgeryRandomized controlled trial

Abstract

fetched live from OpenAlex

Background: Many approaches have been used to determine the minimal clinically important difference (MCID) in patients undergoing total knee arthroplasty, but the MCID for outcome measures after medial opening wedge high tibial osteotomy (MOWHTO) for the treatment of medial compartment knee osteoarthritis (OA) has not been reported. Purpose: To define the MCID for the Western Ontario and McMaster Universities Arthritis Index (WOMAC) after MOWHTO and to identify risk factors for not achieving the MCID. Study Design: Case-control study; Level of evidence, 3. Methods: Among patients with medial compartment knee OA who underwent MOWHTO, 174 patients who were followed for 2 years were included in the study. The MCID and substantial clinical benefit (SCB) for the WOMAC were determined using the anchor-based method with a 15-item questionnaire. Preoperative OA severity was measured by the Kellgren-Lawrence (K-L) grading system, and the acceptable range of the postoperative weightbearing line ratio was 50% to 70%. Patients were divided into 2 groups based on whether the MCID and SCB were achieved, and then factors related to failure to achieve the MCID and SCB were analyzed using multivariate logistic regression analysis. Results: The MCID for the WOMAC was 4.2 points for the pain subscale, 1.9 points for the stiffness subscale, 10.1 points for the function subscale, and 16.1 points for the total. Additionally, the SCB for the WOMAC was 6.4 for pain, 2.6 for stiffness, 16.4 for function, and 25.3 for the total. Overall, 116 (66.7%), 99 (56.9%), 127 (73.0%), and 128 (73.6%) patients achieved the MCID for the WOMAC pain, stiffness, function, and total, respectively, after MOWHTO. The odds of not achieving the MCID for the WOMAC total were 1.09 times greater (95% CI, 1.05-1.13; P < .001) in patients with a low preoperative WOMAC total score (cutoff values: 10.5 for pain, 3.5 for stiffness, 34.5 for function, and 51.0 for the total), 11.77 times greater (95% CI, 3.68-37.70; P < .001) in patients with K-L grade 4 OA compared with K-L grades 2 or 3 OA, and 8.39 times greater (95% CI, 2.98-23.63; P < .001) in patients with undercorrection or overcorrection. A low preoperative WOMAC score, K-L grade 4 OA, and undercorrection or overcorrection were also associated with not achieving the SCB for the WOMAC total (all P < .05). Conclusion: Patients treated with a MOWHTO require a 16.1-point improvement in the WOMAC total score to achieve a MCID from the procedure. Low preoperative WOMAC scores, severe OA, and undercorrection or overcorrection were related to failure to achieve the MCID.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.003
Threshold uncertainty score0.016

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.018
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0010.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.278
Teacher spread0.267 · 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 source (direct Gemma or distilled Codex), 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

Citations76
Published2021
Admission routes1
Has abstractyes

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