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Record W2278924316 · doi:10.1016/j.carj.2015.09.014

Audit of Atypical Femoral Fractures and a Description of Some of Their Features

2016· article· en· W2278924316 on OpenAlexaffabout
Kevin Lian, Jacques Trollip, Supna Sandhu, Mandana Moosavi, Amninder Gill, David L. Kendler, Larry Dian, Brian C. Lentle

Bibliographic record

VenueCanadian Association of Radiologists Journal · 2016
Typearticle
Languageen
FieldMedicine
TopicBone health and osteoporosis research
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsMedicineRadiographyOsteoporosisRadiologySurgeryInternal medicine

Abstract

fetched live from OpenAlex

PURPOSE: Atypical femoral fractures (AFF) are recently described events related to osteoporosis and, potentially, a rare result of antiresorptive treatment. METHODS: We set out to audit the diagnosis of AFF in an acute hospital. Charts and radiographs were reviewed retrospectively from patients diagnosed with subtrochanteric femoral fractures according to hospital discharge coding at Vancouver General Hospital (VGH), Canada, from January 2005 to March 2013. RESULTS: A total of 3084 patients were discharged from the hospital with a diagnosis of hip fracture between 2005 and 2013. Of these, 204 were coded as having had subtrochanteric fractures; 178 of the patients thus coded had radiographic evidence of other fracture types-usually intertrochanteric fractures. Eleven patients did not have available radiographs. Of the remaining 193 patients whose radiographs were reviewed, 24 (12.4%) fulfilled the published criteria for AFF. OUR OBSERVATIONS WERE: 1) laterality: 13 of 24 AFF (54.2%) were right-sided; 2) there was only one incomplete AFF in this series: a completed fracture was an inclusion criterion, but 1 patient with an AFF had both that fracture and an incomplete fracture and further foci of periosteal or endosteal foci of new bone (PENB) involving the contralateral femur; 3) radiologists had only diagnosed AFF in only 1 of the 24 patients with characteristic radiographic signs of AFF; 4) all but 1 patient had a focus of periosteal and/or endosteal new bone (PENB) through which the fracture line invariably passed, and in the 1 exception the radiography was too poor to be sure of this but there was a symmetrical contralateral focus of PENB; 5) in 19 of 24 patients there was an adequate image of part of the contralateral femur and of these 12 (63%) had a contralateral focus of PENB situated ±2.5 cm from the index lesion site when measured from the upper aspect of the greater trochanter, and in another patient a prior fracture of the contralateral femur had been treated surgically and it was at a symmetrical contralateral location from the index fracture.; 6) in 3 of the 19 patients multiple foci of PENB were detected on the lateral aspect of the contralateral femur even though the examination was of limited extent; and 7) AFFs were associated with bisphosphonate medication in 75% of the patients studied. CONCLUSIONS: Hospital discharge coding misclassified a great majority of femoral fractures as subtrochanteric. As an essential criteria for diagnosing AFF is their subtrochanteric location, this misclassification impaired our ability to retrospectively search for AFF patients. Radiologists tended not to report AFF when typical radiographic characteristics were present. Bilateral and multifocal disease is of interest in pointing to the diagnosis and in suggesting that the mechanism of injury in respect of these unusual fractures is more complex than simple low-energy trauma.

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)0.005
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 score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0010.000
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 head0.024
GPT teacher head0.297
Teacher spread0.273 · 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".

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Citations10
Published2016
Admission routes2
Has abstractyes

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