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Record W2161661784 · doi:10.1302/0301-620x.95b8.31832

Internal fixation of radiation-induced pathological fractures of the femur has a high rate of failure

2013· article· en· W2161661784 on OpenAlexaff
Amir Sternheim, Kevan Saidi, Jasjit Lochab, Patrick W. O’Donnell, Anthony M. Griffin, Jay S. Wunder, Peter C. Ferguson

Bibliographic record

VenueThe Bone & Joint Journal · 2013
Typearticle
Languageen
FieldMedicine
TopicManagement of metastatic bone disease
Canadian institutionsNOSM UniversityMount Sinai Hospital
Fundersnot available
KeywordsNonunionInternal fixationMedicineSurgeryFemurBone healingSoft tissueSarcomaFixation (population genetics)Radiation therapyPathologyPopulation

Abstract

fetched live from OpenAlex

We investigated the clinical outcome of internal fixation for pathological fracture of the femur after primary excision of a soft-tissue sarcoma that had been treated with adjuvant radiotherapy. A review of our database identified 22 radiation-induced fractures of the femur in 22 patients (seven men, 15 women). We noted the mechanism of injury, fracture pattern and any complications after internal fixation, including nonunion, hardware failure, secondary fracture or deep infection. The mean age of the patients at primary excision of the tumour was 58.3 years (39 to 86). The mean time from primary excision to fracture was 73.2 months (2 to 195). The mean follow-up after fracture fixation was 65.9 months (12 to 205). Complications occurred in 19 patients (86%). Nonunion developed in 18 patients (82%), of whom 11 had a radiological nonunion at 12 months, five a nonunion and hardware failure and two an infected nonunion. One patient developed a second radiation-associated fracture of the femur after internal fixation and union of the initial fracture. A total of 13 patients (59%) underwent 24 revision operations. Internal fixation of a pathological fracture of the femur after radiotherapy for a soft-tissue sarcoma has an extremely high rate of complication and requires specialist attention.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.915
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
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)0.0010.000

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 head0.028
GPT teacher head0.263
Teacher spread0.235 · 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

Citations41
Published2013
Admission routes1
Has abstractyes

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