An unusual case of gout in the wrist: the importance of monitoring medication dosage and interaction. A case report
Bibliographic record
Abstract
BACKGROUND: Gouty arthritis of the wrist is uncommon although gout itself is the most common inflammatory arthritis in older patients. Some known risk factors for the development of gout include trauma, alcohol use, obesity, hyperuricaemia, hypertension and diabetes mellitus. As well, certain medications have been shown to promote the development of gout. These include thiazide diuretics, low dose salicylates and cyclosporine. We present a case of gouty wrist pain possibly precipitated by a medication dosage increase as well as medication interactions. CASE PRESENTATION: A 77 year old male presented with right wrist pain. Redness and swelling was present at the dorsal aspect of his wrist and range of motion was full with pain at end range upon examination. One week prior, his anti-hypertensive medication dosage had been increased. The patient's situation continued to worsen. Radiographic examination revealed changes consistent with gouty arthritis. CONCLUSION: It is important for clinicians treating joint conditions to be aware of patients' comorbidities, medication usage and changes in dosages. Education of patients with gout is of prime importance. Clinicians should educate patients that gout may occur at any joint in the body not only the lower limb. Patients should be aware of the signs and symptoms of an acute gouty attack and be made aware that changes in certain medication dosages may precipitate an attack. Awareness of radiographic changes associated with gout is still of importance although these changes are not seen as frequently as they have been in the past due to better control of the disease.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.005 | 0.004 |
| Meta-epidemiology (broad) | 0.003 | 0.003 |
| Bibliometrics | 0.008 | 0.005 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.003 | 0.004 |
| Research integrity | 0.015 | 0.009 |
| Insufficient payload (model declined to judge) | 0.004 | 0.003 |
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".