Risk of Incident Chronic Obstructive Pulmonary Disease in Rheumatoid Arthritis: A Population‐Based Cohort Study
Bibliographic record
Abstract
OBJECTIVE: Studies have demonstrated a link between chronic obstructive pulmonary disease (COPD) and inflammation, raising the question whether chronic inflammatory conditions, such as rheumatoid arthritis (RA), predispose to COPD. Our objective was to evaluate the risk of incident COPD hospitalization in RA compared to the general population. METHODS: We studied a population-based incident RA cohort with matched general population controls, using administrative health data. All incident RA cases in British Columbia who first met RA definition between January 1996 and December 2006 were selected using previously published criteria. General population controls were randomly selected, matched 1:1 to RA cases on birth year, sex, and index year. COPD outcome was defined as hospitalization with a primary COPD code. Incidence rates, 95% confidence intervals (95% CIs), and incidence rate ratios (IRRs) were calculated for RA and controls. Multivariable Cox proportional hazards models estimated the risk of COPD in RA compared to the general population after adjusting for potential confounders. Sensitivity analyses were performed to test the robustness of the results to the possible confounding effect of smoking, unavailable in administrative data, and to COPD outcome definitions. RESULTS: The cohorts included 24,625 RA individuals and 25,396 controls. The incidence of COPD hospitalization was greater in RA than controls (IRR 1.58, 95% CI 1.34-1.87). After adjusting for potential confounders, RA cases had a 47% greater risk of COPD hospitalization than controls. The increased risk remained significant after modeling for smoking and with varying COPD definitions. CONCLUSION: In our population-based cohort, individuals with RA had a 47% greater risk of COPD hospitalization compared to the general population.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".