In search of a diagnostic test for polymyalgia rheumatica: is positron emission tomography the answer?
Bibliographic record
Abstract
This editorial refers to Use of 18F-fluorodeoxyglucose positron emission tomography in the diagnosis of polymyalgia rheumatica–A prospective study of 99 patients by Liesbet Henckaerts et al., on pages 1908–16. PMR remains a disease with no definitive diagnostic test. Its diagnosis, relying predominantly on the physician’s clinical impression and supported by a rapid response to low-medium dose prednisone is, by nature, tentative. Quick response to prednisone is not unique to PMR, however. A polymyalgic presentation may herald numerous other diseases, including GCA or other vasculitides, elderly-onset RA, crystal arthropathy, malignancy or infection [1]. Given that treatment consists of months of prednisone, with all its attendant risks, improving diagnostic certainty is a top priority in PMR. To this end, in this issue of Rheumatology, Henckaerts et al. [2] present the results of their prospective study evaluating PET in patients with suspected PMR, yielding new insights and further questions into the role that imaging should play in routine care.
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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 | 0.002 | 0.022 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.007 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.041 | 0.034 |
| Insufficient payload (model declined to judge) | 0.006 | 0.006 |
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".