Baseline Shoulder Ultrasonography Is Not a Predictive Marker of Response to Glucocorticoids in Patients with Polymyalgia Rheumatica: A 12-month Followup Study
Bibliographic record
Abstract
OBJECTIVE: In this study, we evaluated whether ultrasound (US) subdeltoid bursitis (SB) and/or biceps tenosynovitis (BT) presence at baseline could represent a predictive marker of response to standard therapy after 12 months of followup, and whether a positive US examination could highlight the need of higher maintenance dosage of glucocorticoids (GC) at 6 and 12 months in patients with polymyalgia rheumatica (PMR). METHODS: Sixty-six consecutive patients with PMR underwent bilateral shoulder US evaluations before starting therapy and after 12 months of followup. Absence of girdle pain and morning stiffness (clinical remission) and laboratory variables were evaluated. After diagnosis, all patients were treated with prednisone. RESULTS: At baseline, SB and/or BT were present in 46 patients (70%), of whom 33 (72%) became negative while 13 (28%) remained positive at the 12-month US evaluation. All patients rapidly achieved a clinical remission, and at 6 months 26 (39%) also achieved a laboratory variable normalization. According to US positivity at baseline, no difference was found in remission or relapse rate after 12 months. Thirty patients (46%) at 6 months and 7 (11%) at 12 months were still taking more than 5 mg/day of prednisone. According to the US pattern at baseline, no difference was found in the mean GC dose at 6 and 12 months. CONCLUSION: In patients with PMR, the presence of SB and/or BT on US at diagnosis is not a predictive marker of GC response or of a higher GC dosage to maintain remission in a 12-month prospective followup study.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".