Diagnostic and Prognostic Value of History-taking and Physical Examination in Undifferentiated Peripheral Inflammatory Arthritis: A Systematic Review
Bibliographic record
Abstract
OBJECTIVE: To review the diagnostic and prognostic value of history/physical examination among patients with undifferentiated peripheral inflammatory arthritis (UPIA). METHODS: We conducted a systematic review evaluating the association between history/physical examination features and a diagnostic or prognostic outcome. RESULTS: Nineteen publications were included. Advanced age, female sex, and morning stiffness were predictive of a diagnosis of rheumatoid arthritis (RA) from UPIA. A higher number of tender and swollen joints, small/large joint involvement in the upper/lower extremities, and symmetrical involvement were associated with progression to RA. Similar features were associated with persistent disease and erosions, while disability at baseline and extraarticular features were predictive of future disability. CONCLUSION: History/physical examination features are heterogeneously reported. Several features predict progression from UPIA to RA or a poor prognosis. Continued measurements in the UPIA population are needed to determine if these features are valid and reliable predictors of outcomes, especially as new definitions for RA and disease states emerge.
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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 | 0.005 | 0.042 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.006 | 0.007 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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".