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Incidence of Total Knee Arthroplasty After Arthroscopic Surgery for Knee Osteoarthritis

2024· article· en· W4394914047 on OpenAlexafffundabout
Trevor B. Birmingham, Codie A. Primeau, Salimah Z. Shariff, Jennifer Reid, Jacquelyn Marsh, Melody Lam, Stephanie N. Dixon, J. Robert Giffin, Kevin Willits, Robert Litchfield, Brian G. Feagan, Peter J. Fowler

Bibliographic record

VenueJAMA Network Open · 2024
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsLondon Health Sciences CentreLawson Health Research InstituteFowler Kennedy Sport Medicine ClinicWestern University
FundersLawson Health Research InstituteCanadian Institutes of Health ResearchConMedOntario Ministry of Health and Long-Term CareSchulich School of Medicine and DentistryAcademic Medical Organization of Southwestern Ontario
KeywordsMedicineOsteoarthritisOrthopedic surgerySurgeryRandomized controlled trialArthroplastyIncidence (geometry)Knee surgeryClinical trialPhysical therapyInternal medicine

Abstract

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Importance: It is unclear whether arthroscopic resection of degenerative knee tissues among patients with osteoarthritis (OA) of the knee delays or hastens total knee arthroplasty (TKA); opposite findings have been reported. Objective: To compare the long-term incidence of TKA in patients with OA of the knee after nonoperative management with or without additional arthroscopic surgery. Design, Setting, and Participants: In this ad hoc secondary analysis of a single-center, assessor-blinded randomized clinical trial performed from January 1, 1999, to August 31, 2007, 178 patients were followed up through March 31, 2019. Participants included adults diagnosed with OA of the knee referred for potential arthroscopic surgery in a tertiary care center specializing in orthopedics in London, Ontario, Canada. All participants from the original randomized clinical trial were included. Data were analyzed from June 1, 2021, to October 20, 2022. Exposures: Arthroscopic surgery (resection or debridement of degenerative tears of the menisci, fragments of articular cartilage, or chondral flaps and osteophytes that prevented full extension) plus nonoperative management (physical therapy plus medications as required) compared with nonoperative management only (control). Main Outcomes and Measures: Total knee arthroplasty was identified by linking the randomized trial data with prospectively collected Canadian health administrative datasets where participants were followed up for a maximum of 20 years. Multivariable Cox proportional hazards regression models were used to compare the incidence of TKA between intervention groups. Results: A total of 178 of 277 eligible patients (64.3%; 112 [62.9%] female; mean [SD] age, 59.0 [10.0] years) were included. The mean (SD) body mass index was 31.0 (6.5). With a median follow-up of 13.8 (IQR, 8.4-16.8) years, 31 of 92 patients (33.7%) in the arthroscopic surgery group vs 36 of 86 (41.9%) in the control group underwent TKA (adjusted hazard ratio [HR], 0.85 [95% CI, 0.52-1.40]). Results were similar when accounting for crossovers to arthroscopic surgery (13 of 86 [15.1%]) during follow-up (HR, 0.88 [95% CI, 0.53-1.44]). Within 5 years, the cumulative incidence was 10.2% vs 9.3% in the arthroscopic surgery group and control group, respectively (time-stratified HR for 0-5 years, 1.06 [95% CI, 0.41-2.75]); within 10 years, the cumulative incidence was 23.3% vs 21.4%, respectively (time-stratified HR for 5-10 years, 1.06 [95% CI, 0.45-2.51]). Sensitivity analyses yielded consistent results. Conclusions and Relevance: In this secondary analysis of a randomized clinical trial of arthroscopic surgery for patients with OA of the knee, a statistically significant association with delaying or hastening TKA was not identified. Approximately 80% of patients did not undergo TKA within 10 years of nonoperative management with or without additional knee arthroscopic surgery. Trial Registration: ClinicalTrials.gov Identifier: NCT00158431.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.435
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
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 head0.015
GPT teacher head0.276
Teacher spread0.261 · 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.

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

Citations11
Published2024
Admission routes3
Has abstractyes

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