MétaCan
Menu
Back to cohort
Record W2196704454 · doi:10.2106/jbjs.l.01691

Risk of Total Knee Arthroplasty After Operatively Treated Tibial Plateau Fracture

2014· article· en· W2196704454 on OpenAlexaffabout
David Wasserstein, Patrick Henry, Michael J. Paterson, Hans J. Kreder, Richard Jenkinson

Bibliographic record

VenueJournal of Bone and Joint Surgery · 2014
Typearticle
Languageen
FieldMedicine
TopicBone fractures and treatments
Canadian institutionsHealth Sciences CentreInstitute for Clinical Evaluative SciencesSunnybrook Health Science Centre
Fundersnot available
KeywordsMedicineTibial plateau fractureArthroplastyCohortTotal knee arthroplastySurgeryPlateau (mathematics)ComorbidityPopulationOxford knee scoreOsteoarthritisPhysical therapyInternal fixationInternal medicine

Abstract

fetched live from OpenAlex

Background: The aims of operative treatment of displaced tibial plateau fractures are to stabilize the injured knee to restore optimal function and to minimize the risk of posttraumatic arthritis and the eventual need for total knee arthroplasty. The purpose of our study was to define the rate of subsequent total knee arthroplasty after tibial plateau fractures in a large cohort and to compare that rate with the rate in the general population. Methods: All patients sixteen years of age or older who had undergone surgical treatment of a tibial plateau fracture from 1996 to 2009 in the province of Ontario, Canada, were identified from administrative health databases with use of surgeon fee codes. Each member of the tibial plateau fracture cohort was matched to four individuals from the general population according to age, sex, income, and urban/rural residence. The rates of total knee arthroplasty at two, five, and ten years were compared by using time-to-event analysis. A separate Cox proportional hazards model was used to explore the influence of patient, provider, and surgical factors on the time to total knee arthroplasty. Results: We identified 8426 patients (48.5% female; median age, 48.9 years) who had undergone fixation of a tibial plateau fracture and matched them to 33,698 controls. The two, five, and ten-year rates of total knee arthroplasty in the plateau fracture and control cohorts were 0.32% versus 0.29%, 5.3% versus 0.82%, and 7.3% versus 1.8%, respectively (p < 0.0001). After adjustment for comorbidity, plateau fracture surgery was found to significantly increase the likelihood of total knee arthroplasty (hazard ratio [HR], 5.29 [95% confidence interval, 4.58, 6.11]; p < 0.0001). Higher rates of total knee arthroplasty were also associated with increasing age (HR, 1.03 [1.03, 1.04] per year over the age of forty-eight; p < 0.0001), bicondylar fracture (HR, 1.53 [1.26, 1.84]; p < 0.0001), and greater comorbidity (HR, 2.17 [1.70, 2.77]; p < 0.001). Conclusions: Ten years after tibial plateau fracture surgery, 7.3% of the patients had had a total knee arthroplasty. This corresponds to a 5.3 times increase in likelihood compared with a matched group from the general population. Older patients and those with more severe fractures are also more likely to need total knee arthroplasty after repair of a tibial plateau fracture. Level of Evidence: Prognostic Level II. See Instructions for Authors for a complete description of levels of evidence. Peer Review This article was reviewed by the Editor-in-Chief and one Deputy Editor, and it underwent blinded review by two or more outside experts. It was also reviewed by an expert in methodology and statistics. The Deputy Editor reviewed each revision of the article, and it underwent a final review by the Editor-in-Chief prior to publication. Final corrections and clarifications occurred during one or more exchanges between the author(s) and copyeditors.

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)0.000
metaresearch head score (Gemma)0.002
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 score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.002
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)0.0020.000

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 head0.010
GPT teacher head0.226
Teacher spread0.216 · 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

Citations253
Published2014
Admission routes2
Has abstractyes

Explore more

Same venueJournal of Bone and Joint SurgerySame topicBone fractures and treatmentsFrench-language works237,207