Pediatric Antibiotic-refractory Lyme Arthritis: A Multicenter Case-control Study
Bibliographic record
Abstract
OBJECTIVE: Few factors have consistently been linked to antibiotic-refractory Lyme arthritis (ARLA). We sought to identify clinical and treatment factors associated with pediatric ARLA. METHODS: We performed a case-control study in 3 pediatric rheumatology clinics in a Lyme-endemic region (2000-2013). Eligible children were aged ≤ 18 years with arthritis and had positive testing for Lyme disease by Western blot. Cases were 49 children with persistently active arthritis despite ≥ 8 weeks of oral antibiotics or ≥ 2 weeks of parenteral antibiotics; controls were 188 children whose arthritis resolved within 3 months of starting antibiotics. We compared preselected demographic, clinical, and treatment factors between groups using logistic regression. RESULTS: Characteristics positively associated with ARLA were age ≥ 10 years, prolonged arthritis at diagnosis, knee-only arthritis, and worsening after starting antibiotics. In contrast, children with fever, severe pain, or other signs of systemic inflammation were more likely to respond quickly to treatment. Secondarily, low-dose amoxicillin and treatment nonadherence were also linked to higher risk of ARLA. Greater antibiotic use for children with ARLA was accompanied by higher rates of treatment-associated adverse events (37% vs 15%) and resultant hospitalization (6% vs 1%). CONCLUSION: Older children and those with prolonged arthritis, arthritis limited to the knees, or poor initial response to antibiotics are more likely to have antibiotic-refractory disease and treatment-associated toxicity. Children with severe symptoms of systemic inflammation have more favorable outcomes. For children with persistently active Lyme arthritis after 2 antibiotic courses, pediatricians should consider starting antiinflammatory treatment and referring to a pediatric rheumatologist.
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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 | 0.004 |
| 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 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| 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".