Lyme Arthritis in Rheumatological Practice: A Survey of Canadian Pediatric Rheumatologists
Bibliographic record
Abstract
Objectives Arthritis is a common manifestation of Lyme disease (LD) in children and resembles other forms of inflammatory arthritis including JIA. Up to 15% of children with Lyme arthritis (LA) have persistent arthritis despite adequate antibiotic therapy, called post-infectious LA (PILA), and present diagnostic and treatment challenges. The impact of LA is likely to grow with the predicted increase in incidence and geographic distribution of LD.[1,2] The study’s objective was to gain an understanding of the clinical burden, clinical practices, and research priorities of Canadian pediatric rheumatologists (PRs) in caring for children with LA. Methods An online survey was distributed to all PRs identified through the Canadian Rheumatology Association membership directory in May 2024. We collected information on practice characteristics, models of care, management, and research priorities regarding LA. Descriptive statistics are reported. Results 40/69 PRs (58%) responded; 80% (32/40), reported caring for patients with LA. PRs in the Atlantic and Eastern regions see the most LA (Table 1). 56% of respondents feel that PRs should assess the response to the first course of antibiotics; 26% would involve PRs only after another health care provider determines incomplete response to the first course of antibiotics, 3% only in a patient diagnosed with PILA, and 23% depending on other factors, primarily non-PRs musculoskeletal examination abilities. Following the first course of antibiotics, in children who have improved, but have persistent symptomatic arthritis, 66% (21/32) would recommend a 2nd course of oral antibiotics; 16% (5/32) would recommend an intraarticular steroid injection (IAS) (4 with antibiotics, 1 alone); and 19% (6/32) were unsure/didn’t respond. In children with minimal/no response to the first course of antibiotics, the top responses were divided between a 2nd course of oral antibiotics (9/32), IV antibiotics (9/32) or an IAS with antibiotics (9/32). The top priorities identified for research were to (1) determine optimal treatment for patients who do not fully respond to the first course of antibiotics, (2) define optimal models of care, and (3) develop tests to aid in the diagnosis of LA and differentiate it from other forms of arthritis. Table 1 Demographics, practice characteristics, and selected additional survey responses Conclusion Children with LA are seen by PRs across Canada however models of care vary and there is variability in treatment approaches. We have identified research priorities including determining optimal treatment in those who do not respond to the first course of antibiotics and exploring models of care which will allow timely access to high-quality care. [1.] Clow K. PLoS One 2017;12(12):e0189393. [2.] Murison K. PLoS One 2023;18(12):e0295909.
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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) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.007 |
| Science and technology studies | 0.003 | 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) | 0.002 | 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".