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Record W4372402908 · doi:10.7759/cureus.38614

Treatment of Vancouver B2 Femur Fractures With Open Reduction Internal Fixation Versus Revision Arthroplasty

2023· article· en· W4372402908 on OpenAlexaboutno aff
Michael Perry, John-Luke Rivera, Michael Wesolowski, Carlo Eikani, William D. Lack, Joseph Cohen, Nicholas M. Brown

Bibliographic record

VenueCureus · 2023
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsnot available
Fundersnot available
KeywordsMedicinePeriprostheticSurgeryInternal fixationBlood lossArthroplastyRetrospective cohort studyReduction (mathematics)CohortTrauma centerFemurInternal medicine

Abstract

fetched live from OpenAlex

Background Vancouver B2 periprosthetic femur fractures have traditionally been treated with revision arthroplasty. However, there is increasing evidence that open reduction and internal fixation (ORIF) may be a valid alternative treatment strategy. The purpose of this study was to compare the outcomes of ORIF versus revision arthroplasty for the treatment of Vancouver B2 fractures and evaluate the influence of the treating surgeon’s fellowship training on treatment selection. Methodology This was a retrospective cohort study of 31 patients treated for Vancouver B2 periprosthetic fractures (16 ORIF and 15 revision arthroplasty) at a single academic Level 1 trauma center. Outcome measures included one-year mortality, revision, reoperation, infection, and blood loss. Results There were no statistically significant differences in revision, reoperation, or infection at an average follow-up of 65 weeks. Median estimated blood loss was higher in the arthroplasty group (700 cc versus 400 cc; P = 0.04). There were five deaths in the ORIF group versus one in the revision group (P = 0.18). Cases treated by surgeons with fellowship training in arthroplasty were more likely to be treated with revision arthroplasty (10/11, 90.9%) than those treated by surgeons with fellowship training in trauma (5/15, 33.3%; P < 0.01). Conclusions There was no difference in outcomes between the two treatment strategies, but revision was associated with higher blood loss. The appropriate treatment method should be based on surgeon familiarity and patients' characteristics.

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)0.001
metaresearch head score (Gemma)0.003
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 score0.002
Threshold uncertainty score0.004

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
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 head0.035
GPT teacher head0.333
Teacher spread0.298 · 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

Citations8
Published2023
Admission routes1
Has abstractyes

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