Paradoxical Stress Fracture in a Patient With Multiple Myeloma and Bisphosphonate Use
Bibliographic record
Abstract
Multiple myeloma (MM) is a plasma cell disorder with related organ dysfunction, including hypercalcemia, renal insufficiency, anemia, and bone disease. Osteolytic bone lesions that result in pain and pathologic fractures are a major source of morbidity and the use of bisphosphonates is generally safe and effective treatment in reducing myeloma-related skeletal fractures and associated morbidity. We present a 73-year-old African American woman with MM in remission and on intravenous (IV) bisphosphonate therapy in the past five years who reported gradually worsening bilateral thigh pain of six months duration. A bone survey showed no neoplastic focus, and bilateral hip X-rays showed incomplete insufficiency stress fractures with characteristic features suspicious for bisphosphonate-related atypical femoral fracture (AFF). Increasingly reported in the literature, bilateral AFF is a unique and serious adverse effect for patients on bisphosphonates. Our case illustrates the distinct challenges in managing a patient with MM on long-term bisphosphonate therapy who suffered bilateral atypical femoral fractures, an uncommon presentation of a relatively rare phenomenon. It is important to balance the established benefits of bisphosphonate therapy with potential fracture risk and be particularly vigilant about adverse effect monitoring and timely intervention.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
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".