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Record W3067008661 · doi:10.7759/cureus.9837

Paradoxical Stress Fracture in a Patient With Multiple Myeloma and Bisphosphonate Use

2020· article· en· W3067008661 on OpenAlexaff
Edwin Chiu, Michael Cabanero, Gurinder Sidhu

Bibliographic record

VenueCureus · 2020
Typearticle
Languageen
FieldMedicine
TopicBone health and treatments
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineInsufficiency fractureStress fracturesBisphosphonateMultiple myelomaOsteoporosisAdverse effectSurgeryBone painBone diseaseAnemiaInternal medicine

Abstract

fetched live from OpenAlex

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.

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)0.000
metaresearch head score (Gemma)0.000
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 score0.012
Threshold uncertainty score0.286

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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)0.0000.000

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 head0.021
GPT teacher head0.260
Teacher spread0.239 · 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

Citations6
Published2020
Admission routes1
Has abstractyes

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