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Record W4213062445 · doi:10.1503/cjs.002221

The rate of unnecessary interventions for the management of knee osteoarthritis: a population-based cohort study

2022· article· en· W4213062445 on OpenAlexaffvenueabout
Jacquelyn Marsh, Ryan M. Degen, Trevor B. Birmingham, J. Robert Giffin, Alan Getgood, Robert Litchfield, Kevin Willits, J. Andrew McClure, Blayne Welk

Bibliographic record

VenueCanadian Journal of Surgery · 2022
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsFowler Kennedy Sport Medicine ClinicWestern University
Fundersnot available
KeywordsMedicineInterquartile rangeOsteoarthritisRetrospective cohort studyArthroscopyCohortMagnetic resonance imagingPhysical therapyCohort studyTotal knee arthroplastyPopulationSurgeryInternal medicineRadiologyPathology

Abstract

fetched live from OpenAlex

<h3>Background:</h3> Several commonly used procedures for knee osteoarthritis (OA) are not supported by evidence-based guidelines. The objective of this study was to identify the proportion of patients who underwent knee arthroscopy or magnetic resonance imaging (MRI) and the timing of these procedures before total knee arthroplasty (TKA). <h3>Methods:</h3> We conducted a retrospective cohort study using administrative data sets from Ontario, Canada. We identified the proportion of patients who underwent knee arthroscopy in the previous 10 years or an MRI in the 3 years before their primary TKA. We also evaluated the rate of arthroscopies by diagnosis. We report the timing of each outcome in relation to the TKA, rates by geographical area, and differences in rates over time. <h3>Results:</h3> We included 142 275 patients, of whom 36 379 (25.57%) underwent knee arthroscopy (median time 2.8 [interquartile range (IQR) 1.1–6.0] years); 22% of those were within 1 year of TKA and 52% were within 3 years. The rates of arthroscopies for a diagnosis of osteoarthritis (OA) steadily decreased, while those for meniscal-related diagnoses increased over the study period (<i>p</i> &lt; 0.0001). There was significant variation by region. Of the cohort, 23.2% (<i>n</i> = 32 989) had an MRI before their TKA, with rates significantly increasing over time (<i>p</i> &lt; 0.0001). <h3>Conclusion:</h3> A substantial proportion of patients with knee OA received diagnostic and therapeutic interventions before TKA that are contrary to clinical practice guidelines.

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)0.000
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 score0.010
Threshold uncertainty score0.507

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
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 head0.033
GPT teacher head0.278
Teacher spread0.245 · 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

Citations14
Published2022
Admission routes3
Has abstractyes

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