Case report: A severe case of zoledronate-associated diffuse orbital inflammation and uveitis in a patient with metastatic breast cancer
Bibliographic record
Abstract
Introduction: Zoledronate is a commonly prescribed medication to maintain bone health; however, a rare side effect includes ocular inflammation. We report a case of simultaneous anterior uveitis and orbital inflammation associated with zoledronate infusion in a patient with metastatic breast cancer. We also performed a literature search to provide an up-to-date summary of cases with zoledronate-associated ocular inflammation. Methods: This is a case report with literature review. Literature search (timeline 2010 to 2023) was performed using PubMed with the search team: (zoledronate) AND (uveitis OR scleritis OR orbital inflammation OR ocular inflammation). Results: A 48-year-old female presented with left eye pain, swelling, and decreased vision 2 days after receiving zoledronic acid infusion. An ophthalmic exam showed non-granulomatous anterior uveitis. CT orbits and ocular ultrasound showed signs of posterior scleritis and orbital inflammation. Ocular inflammation caused by an infection or metastatic cancer was ruled out. The patient was treated with both topical and systemic corticosteroids. Complete resolution of the inflammation occurred after 2.5 weeks. Conclusion: Orbital inflammation and uveitis are an uncommon side effect of zoledronate but needs to be promptly recognized and treated to prevent sight-threatening complications.
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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) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".