Impact of the COVID-19 pandemic on juvenile idiopathic arthritis presentation and research recruitment: results from the CAPRI registry
Bibliographic record
Abstract
OBJECTIVE: The COVID-19 pandemic has disrupted healthcare delivery and clinical research worldwide, with data from areas most affected demonstrating an impact on rheumatology care. This study aimed to characterize the impact of the pandemic on the initial presentation of JIA and JIA-related research in Canada. METHODS: Data collected from the Canadian Alliance of Pediatric Rheumatology Investigators JIA Registry from the year pre-pandemic (11 March 2019 to 10 March 2020) was compared with data collected during the first year of the pandemic (11 March 2020 to 10 March 2021). Outcomes included time from symptom onset to first assessment, disease severity at presentation and registry recruitment. Proportions and medians were used to describe categorical and continuous variables, respectively. RESULTS: The median time from symptom onset to first assessment was 138 (IQR 64-365) days pre-pandemic vs 146 (IQR 83-359) days during the pandemic. The JIA category frequencies remained overall stable (44% oligoarticular JIA pre-pandemic, 46.8% pandemic), except for systemic JIA (12 cases pre-pandemic, 1 pandemic). Clinical features, disease activity (cJADAS10), disability (CHAQ) and quality of life (JAQQ) scores were similar between the two cohorts. Pre-pandemic, 225 patients were enrolled, compared with 111 in the pandemic year, with the greatest decrease from March to June 2020. CONCLUSIONS: We did not observe the anticipated delay in time to presentation or increased severity at presentation, suggesting that, within Canada, care adapted well to provide support to new patient consults without negative impacts. The COVID-19 pandemic was associated with an initial 50% decrease in registry enrolment but has since improved.
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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 | 0.011 | 0.036 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.001 |
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".