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Pathologic Fractures of the Proximal Femur Secondary to Benign Bone Tumors

2001· article· en· W1974799722 on OpenAlexaffabout
Eugene K. Wai, Aileen M. Davis, Anthony M. Griffin, Robert S. Bell, Jay S. Wunder

Bibliographic record

VenueClinical Orthopaedics and Related Research · 2001
Typearticle
Languageen
FieldMedicine
TopicBone Tumor Diagnosis and Treatments
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsMedicineFemurPathologySurgery

Abstract

fetched live from OpenAlex

Pathologic fractures of the proximal femur secondary to benign bone tumors often are difficult to treat because of specific anatomic features of this region and the aggressiveness of the tumors. Between 1986 and 1996, 11 patients presented with a pathologic fracture of the proximal femur secondary to a benign bone tumor. All were treated with a uniform approach consisting of biopsy, intralesional curettage, high-speed burring, and reconstruction using morselized allograft, autograft, and a fixed-angle implant. The average followup was 4 years 3 months (range, 24-114 months). One patient was lost to followup. All fractures healed, and there were no local recurrences and no cases of avascular necrosis. Functional evaluation revealed generally good results. Patients scored a mean of 32.6 on the original Musculoskeletal Tumor Society scale and 95.8 on the revised version. The average Toronto Extremity Salvage Score was 91.3. With the numbers available, there were no significant differences between the study group and population norms in the Short Form-36. These results suggest that a uniform approach based on preservation of the femoral head can be applied successfully to the treatment of these lesions with good local tumor control, fracture healing, and acceptable functional outcomes.

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)0.003
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.768

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0000.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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 head0.079
GPT teacher head0.430
Teacher spread0.351 · 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

Citations57
Published2001
Admission routes2
Has abstractyes

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