Clinical Practice Guidelines and Diagnostic Uncertainty in the Management of Early Rheumatoid Arthritis
Bibliographic record
Abstract
Clinical practice guidelines (CPG) are “systematically developed statements to assist practitioner and patient decisions about healthcare for specific clinical circumstances,” and are intended to improve the quality of care for individuals with a specific diagnosis by encouraging physicians to adopt more evidence-based practice1. Over the past decade, several sets of CPG for the management of rheumatoid arthritis (RA) have been developed and disseminated2–4. Many studies have demonstrated substantial gaps between disseminated CPG and clinical practice, including some in RA5,6. However, requisite to drawing meaningful conclusions about physician adherence to CPG is a more detailed understanding of the circumstances leading to perceived suboptimal healthcare practices. In an effort to explore reasons for potential nonadherence to CPG in RA, in this issue of The Journal , Benhamou and colleagues examined physician prescribing patterns for early RA7 prior to publication of 2 sets of CPG addressing prescription of first-line disease-modifying antirheumatic drugs (DMARD)2,3. Utilizing ESPOIR (French acronym for “Study and Followup of Undifferentiated Early Arthritis”), a French multicenter observational cohort study that included 813 patients with early RA between 2002 and 2005, the authors found a 58% physician adherence rate with the French Society of Rheumatologists’ STPR (French acronym for “Therapeutic strategies in RA”) working group guidelines, and a 54% adherence with … Address reprint requests to Dr. Hersh. E-mail: hersha{at}peds.ucsf.edu
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.041 | 0.367 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.007 | 0.009 |
| Insufficient payload (model declined to judge) | 0.003 | 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".