Subtrochanteric Fracture as First Sign of Metastatic Breast Cancer: Case Presentation
Bibliographic record
Abstract
Atraumatic subtrochanteric fractures represent a serious injury of the lower limb as they represent the clinical expression of a preexisting pathology. Atypical subtrochanteric femur fractures can result from long-term bisphosphonate therapy but a primary or metastatic tumor of the proximal femur should always be included in the differential diagnosis. We present the case of a young female patient without any previous pathological conditions that presented to the emergency room with a subtrochanteric fracture. She was admitted to our clinic and treated with a long cephalomedullary device (CMD). Tissue from the fracture zone was harvested and sent for a pathology analysis. While pathologic bone fractures are not a new entity by any mean in orthopedic practice, they seldom are the first sign of a metastatic disease. This presents a therapeutic challenge especially in young patients because of the reserved overall prognosis in the medium and long term. Better screening methods should be employed in a bid to eliminate this category of patients. We consider this case of a young woman with undetected breast cancer and one skeletal-related event (SRE) in the form of a pathological bone subtrochanteric fracture as an interesting development of the underlying pathology since as the literature shows these cases are quite rare and she did not present any of the usual symptoms associated with a bone metastasis. J Med Cases. 2015;6(8):367-372 doi: http://dx.doi.org/10.14740/jmc2216w
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.006 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".