Contribution of the Polymyalgia Rheumatica Activity Score to Glucocorticoid Dosage Adjustment in Everyday Practice
Bibliographic record
Abstract
OBJECTIVE: To evaluate the usefulness of the polymyalgia rheumatica (PMR) activity score (PMR-AS) in guiding adjustment of glucocorticoid (GC) dosage. METHODS: Rheumatologists prospectively included patients receiving GC therapy for PMR. At each visit, they assessed disease activity using a visual analog scale for physician's global assessment (VASph) and recorded whether a flare was diagnosed and/or the GC dosage was changed. In each patient, the PMR-AS was calculated using the formula of Leeb and Bird: C-reactive protein (mg/dl) + VAS pain score (0 to 10) + VASph (0 to 10) + (morning stiffness in min × 0.1) + elevation of upper limbs (0-3). We evaluated the correlation between PMR-AS and GC dosage changes in the group already treated with GC. RESULTS: We included 89 patients (mean age 74.6 ± 6.2 yrs; disease duration 1.6 ± 2.2 yrs), who had a total of 149 visits. PMR-AS was available for 137 visits. Of those, 124 involved patients already treated with GC, and 13 patients who started GC treatment. The Spearman correlation coefficient between PMR-AS values and GC dosage change was 0.58 (p < 0.001). In the group already treated with GC, when the PMR-AS was higher than 20, GC dosages were never decreased. When the PMR-AS was between 10 and 20, GC dosages were decreased in 4 patients, unchanged in 4, and increased by < 5 mg in 4 patients. When PMR-AS was < 10, GC dosages were generally decreased. CONCLUSION: The PMR-AS is helpful for diagnosing flares of PMR and may also assist in everyday practice to decide how to change the GC dosage.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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) | 0.000 | 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 teacher head, 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".