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Record W1996978118 · doi:10.4137/cmamd.s10859

Clinical and Economic Burden of Revision Knee Arthroplasty

2012· article· en· W1996978118 on OpenAlexaff
Mohit Bhandari, Jon Smith, Larry E. Miller, Jon E. Block

Bibliographic record

VenueClinical Medicine Insights Arthritis and Musculoskeletal Disorders · 2012
Typearticle
Languageen
FieldMedicine
TopicTotal Knee Arthroplasty Outcomes
Canadian institutionsMcMaster University
Fundersnot available
KeywordsMedicineUnicompartmental knee arthroplastyPeriprostheticHigh tibial osteotomyOsteoarthritisArthroplastySurgeryOsteotomyPhysical therapyAlternative medicine

Abstract

fetched live from OpenAlex

Surgery is indicated for symptomatic knee osteoarthritis (OA) when conservative measures are unsuccessful. High tibial osteotomy (HTO), unicompartmental knee arthroplasty (UKA), and total knee arthroplasty (TKA) are surgical options intended to relieve knee OA pain and dysfunction. The choice of surgical intervention is dependent on several factors such as disease location, patient age, comorbidities, and activity levels. Regardless of surgical treatment, complications such as infection, loosening or lysis, periprosthetic fracture, and postoperative pain are known risks and are indications for revision surgery. The clinical and economic implications for revision surgery are underappreciated. Over 55,000 revision surgeries were performed in 2010 in the US, with 48% of these revisions in patients under 65 years. Total costs associated with each revision TKA surgery have been estimated to be in excess of $49,000. The current annual economic burden of revision knee OA surgery is $2.7 billion for hospital charges alone. By 2030, assuming a 5-fold increase in the number of revision procedures, this economic burden will exceed $13 billion annually. It is appealing to envision a therapy that could delay or obviate the need for arthroplasty. From an actuarial standpoint, this would have the theoretical downstream effect of substantially reducing the number of revision procedures. Although no known therapies currently meet these criteria, such a breakthrough would have a tremendous impact in lessening the clinical and economic burden of knee OA revision surgery.

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)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.603
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0020.000
Bibliometrics0.0000.000
Science and technology studies0.0000.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.021
GPT teacher head0.338
Teacher spread0.316 · 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

Citations234
Published2012
Admission routes1
Has abstractyes

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