Healthcare utilization among patients with rheumatoid arthritis, with and without herpes zoster, a retrospective administrative data linked cohort study
Bibliographic record
Abstract
BACKGROUND: Herpes zoster (HZ) infection is a significant concern among seniors and immunosuppressed patients including those with rheumatoid arthritis (RA). We aimed to compare healthcare utilization (HCU) and mortality in RA patients with and without HZ. METHODS: Patients from the Ontario Best Practices Research Initiative (OBRI) a clinical cohort (2008-2020) were linked to the Institute for Clinical Evaluative Sciences (ICES), a population health database. Each HZ patient was matched to four non-HZ patients based on sex, age, and HZ diagnosis date. The incidence of primary (HCU including hospitalization, Emergency Department (ED) visits, physician visits) and secondary (mortality and chronic clinical conditions) outcomes was calculated for each cohort, along with the impact of disease activity, patient-reported outcomes, and RA medication on these outcomes. RESULTS: The study included 269 RA patients with and 1072 without HZ. At index date (HZ diagnosis) patients with HZ were less likely to have private health insurance (45.7% vs. 56.5%) and more prone to use biologics (30.9% vs. 26.8%) and JAK inhibitors (3.7% vs. 2.6%). Hospitalization/ED visits and mortality were higher in HZ patients, but these differences were not statistically significant after adjusting for other factors. HZ patients had significantly more physician visits (adj IRR: 1.17; 95% CI: 1.03-1.33). Female sex and lower CDAI were associated with fewer physician visits. JAK inhibitor use was associated with increased mortality (adj HR: 4.73, 95% CI: 1.68, 13.4). CONCLUSION: HCU was higher in RA patients with HZ, particularly in physician visits. Disease activity, patient reported outcomes and RA medication used did not have an impact on HCU and mortality.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".