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Record W4327740845 · doi:10.1177/21514593221145884

Atypical Vancouver B1 Periprosthetic Fractures: The Unsolved Problem

2023· article· en· W4327740845 on OpenAlexaboutno aff
Giovanni Vicenti, Giuseppe Solarino, Guglielmo Ottaviani, M Carrozzo, F Simone, Giacomo Zavattini, Domenico Zaccari, Claudio Buono, Davide Bizzoca, Giuseppe Maccagnano, Biagio Moretti

Bibliographic record

VenueGeriatric Orthopaedic Surgery & Rehabilitation · 2023
Typearticle
Languageen
FieldMedicine
TopicOrthopaedic implants and arthroplasty
Canadian institutionsnot available
Fundersnot available
KeywordsPeriprostheticMedicineSurgeryOsteoporosisStress fracturesFirst lineGeneral surgeryArthroplastyInternal medicine

Abstract

fetched live from OpenAlex

Atypical femoral fractures (AFF) are stress or insufficiency fractures induced by low energy trauma or no trauma, frequently correlated with prolonged bisphosphonate therapy. The diagnosis follows major and minor criteria, originally described by the Task Force of the American Society for Bone and Mineral Research in 2010 and updated in 2014. However, the definition of AFFs in the report excluded periprosthetic fractures. When atypical fractures occur close to a prosthetic implant the situation become critical, the surgical treatment is often demolitive and supported by medical treatment. Moreover, acute ORIF as a first line treatment is frequently burdened by a high failure rate , and often a stem revision is required as second line treatment. The healing process is long and difficult with poor functional results and impairing outcomes. We present a case treated at our institution of a 78 year old woman with a history of a femoral atypical periprosthetic fracture, complicated by multiple surgical revisions. Its arduous management reflects all the difficulties that these type of fractures could present to the surgeon, while its good final result may teach us how to approach them in a correct way.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.385
Threshold uncertainty score0.967

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.002
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.011
GPT teacher head0.257
Teacher spread0.246 · 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

Citations2
Published2023
Admission routes1
Has abstractyes

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