Adverse Events During Longterm Low-dose Glucocorticoid Treatment of Polymyalgia Rheumatica: A Retrospective Study
Bibliographic record
Abstract
OBJECTIVE: To assess the occurrence of adverse events in a cohort of patients with polymyalgia rheumatica (PMR), treated with low-dose glucocorticoids (GC). METHODS: This was a retrospective study by review of medical records. RESULTS: We identified 222 patients who had a mean duration of followup of 60 ± 22 months and a mean duration of GC therapy of 46 ± 22 months. We found that 95 patients (43%) had at least 1 adverse event after a mean duration of GC therapy of 31 ± 22 months and a mean cumulative dose of 3.4 ± 2.4 g. In particular, 55 developed osteoporosis, 31 had fragility fractures; 27 developed arterial hypertension; 11 diabetes mellitus; 9 acute myocardial infarction; 3 stroke; and 2 peripheral arterial disease. Univariate analysis showed that the duration of GC treatment was significantly associated with osteoporosis (p < 0.0001), fragility fractures (p < 0.0001), arterial hypertension (p < 0.005), and acute myocardial infarction (p < 0.05). Cumulative GC dose was significantly associated with osteoporosis (p < 0.0001), fragility fractures (p < 0.0001), and arterial hypertension (p < 0.01). The adverse events occurred more frequently after 2 years of treatment. Multivariate analysis showed that GC duration was significantly associated with osteoporosis (adjusted OR 1.02, 95% CI 1.02-1.05) and arterial hypertension (adjusted OR 1.03, 95% CI 1.01-1.06); GC cumulative dose was significantly associated with fragility fractures (adjusted OR 1.4, 95% CI 1.03-1.8). CONCLUSION: Longterm, low-dose GC treatment of PMR is associated with serious adverse events such as osteoporosis, fractures, and arterial hypertension; these adverse events occur mostly after 2 years of treatment.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".