Bilateral Avascular Necrosis of the Hips in a Patient With Sickle Cell Trait and Chronic Alcohol Use
Bibliographic record
Abstract
Sickle cell trait (SCT) is generally considered a benign carrier state, unlike sickle cell disease (SCD), which is frequently associated with complications such as avascular necrosis (AVN). While AVN affects approximately 30% of patients with SCD, it is rarely reported in individuals with SCT and is not well understood. A 29-year-old African American male with SCT presented with progressively worsening hip pain. He reported chronic heavy alcohol use but denied steroid use, trauma or previous sickle cell crises. Physical exam demonstrated severely limited hip range of motion and antalgic gait. Laboratory studies were unremarkable aside from elevated C-reactive protein. Radiographs revealed bilateral femoral head AVN greater than stage II, with partial collapse on the left. He was managed conservatively with nonsteroidal anti-inflammatory drugs (NSAIDs), physical therapy, and counseling on alcohol reduction, and was referred to orthopedics for long-term management. Although rare, AVN can occur in individuals with SCT, particularly when compounded by modifiable risk factors such as chronic alcohol use, which can impair bone remodeling, promote fat embolism, and exacerbate microvascular compromise from intermittent sickling. It highlights the importance of early recognition and intervention in patients with unexplained joint pain, and that clinicians should maintain a high index of suspicion for AVN in SCT patients, especially in the presence of other comorbidities and risk factors.
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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 | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".