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Record W2570955682 · doi:10.1177/1602400305

Outcome in Total Knee Arthroplasty with a Medial-Lateral Balanced versus Unbalanced Gap

2016· article· en· W2570955682 on OpenAlexaboutno aff
Ahmed Jawhar, Karolin Hutter, Hanns‐Peter Scharf

Bibliographic record

VenueJournal of orthopaedic surgery · 2016
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineWOMACOsteoarthritisProsthesisTotal knee arthroplastyPatellaOrthodonticsSignificant differenceSurgeryInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: To evaluate the clinical outcome in 108 total knee arthroplasty (TKA) patients with a medial-lateral balanced versus unbalanced gap after a mean follow-up of 34 months. METHODS: 64 women and 44 men (mean age, 69.5 years) underwent computer-assisted TKA for osteoarthritis using a cemented fixed-bearing cruciate-retaining prosthesis. The medial-lateral gap difference (measured with the prosthesis in situ and the patella reduced) was balanced (≤2 mm) in 81 patients and unbalanced (>2 mm) in 27 patients. After a mean follow-up of 34 months, patients were assessed using the Western Ontario and McMaster Universities Arthritis Index (WOMAC) questionnaire for pain, stiffness, and physical function. Scores were normalised to 0% (worst) to 100% (best). RESULTS: The balanced and unbalanced gap groups were comparable in terms of age, severity of osteoarthritis, and proportion of pre- and post-operative mechanical alignment. Compared with the balanced gap group, the unbalanced gap group had a larger medial-lateral extension gap difference (0.75±0.57 vs. 2.02±1.15 mm, p=0.001) and medial-lateral flexion gap difference (0.79±0.63 vs. 2.98±2.13 mm, p=0.001) and lower normalised total WOMAC score (84.9±18 vs. 74.8±20.8, p=0.017). CONCLUSION: WOMAC score is better in TKAs with a medial-lateral balanced (<2 mm) gap.

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 score0.024
Threshold uncertainty score0.807

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
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 head0.028
GPT teacher head0.271
Teacher spread0.242 · 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

Citations31
Published2016
Admission routes1
Has abstractyes

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