Clinical Characteristics and Predictors of the Recurrence of Organizing Pneumonia Associated With Rheumatoid Arthritis
Bibliographic record
Abstract
Objective To clarify the clinical characteristics of organizing pneumonia (OP) in rheumatoid arthritis (RA; RA-OP) and the association of OP development with RA exacerbation, and to identify OP recurrence predictors. Methods Data from 33 patients with RA-OP admitted to our hospital were retrospectively analyzed (2006-2016). Results RA onset preceded OP onset in 82% of patients, whereas OP onset preceded (OP-preceding) or co-occurred with RA in 9% of patients each. Median age at first OP onset was 64.0 years, and the period from RA onset to first OP onset was 5.5 years. At OP onset, 42% of events exhibited unilateral involvement and 76% had normal Krebs von den Lungen-6. RA disease control remained optimal in 52% of events and was exacerbated in 18% of events. Ten patients (30%) experienced OP recurrence with an interval of 13.0 months between events, and the first OP recurrence rate was 127/1000 person-years. Compared with nonrecurrent cases (n = 14), recurrent cases (n = 10) showed lower age at first OP onset (59.5 vs 67.1 yrs; P = 0.04) and a shorter period from RA onset to first OP onset (6.4 vs 14.2 yrs; P = 0.047); moreover, these cases included a higher number of OP-preceding patients (30% vs 0%; P = 0.03) and ever smokers (80% vs 36%; P = 0.03). OP-preceding patients showed shorter median recurrence-free survival time (15 vs 136 months; P = 0.01) and higher recurrence risk (hazard ratio 5.45; P = 0.02). Conclusion RA-OP showed a high recurrence rate and was not associated with RA exacerbation. Four RA-OP recurrence predictors were identified.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 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".