Retrospective validation of a rapid Lyme fluorescent immunoassay in differentiating Lyme arthritis from other musculoskeletal presentations in children in a Lyme-endemic region
Bibliographic record
Abstract
ABSTRACT Lyme arthritis can present similarly to other causes of joint pain and swelling including septic arthritis and other acute and chronic arthropathies of childhood. Septic arthritis, although rare, constitutes an orthopedic emergency and requires early surgical intervention to reduce the risk of permanent joint damage. Currently, results of standard serologic tests to diagnose Lyme disease take days to weeks, which is unhelpful in acute clinical decision-making. Thus, some children with Lyme arthritis are treated empirically for septic arthritis undergoing unnecessary invasive procedures and hospital admission while on inappropriate antibiotic therapy. We retrospectively validated the Quidel Sofia Lyme Fluorescent Immunoassay, a rapid serologic assay that can detect IgG and/or IgM antibodies to Borrelia burgdorferi in 10 minutes, in residual serum samples collected from 51 children who had Lyme arthritis and 55 children with musculoskeletal presentations who were Lyme negative. The sensitivity and specificity of the Sofia IgG to identify cases of Lyme arthritis in children were 100% (95% confidence interval [CI] of 93.0%–100%) and 96.4% (95% CI: 87.5%–99.6%), respectively. The positive likelihood ratio (LR) was 27.5 (95% CI 7–107), and the negative LR was 0.00 (95% LR 0.00–0.15). We propose that the Sofia IgG, a rapid method for identifying Lyme arthritis, may be useful in differentiating Lyme arthritis from other forms of arthritis. Used in conjunction with readily available clinical and laboratory variables, it could help to rapidly identify children who are at low risk of septic arthritis in Lyme-endemic regions. IMPORTANCE Lyme arthritis is a common manifestation of Lyme disease in children, with clinical features overlapping with other causes of acute and chronic joint pain/swelling in children. We have demonstrated that the Sofia IgG is a reliable test to rule in and rule out the diagnosis of Lyme arthritis in children with musculoskeletal presentations in a Lyme-endemic region. When used in conjunction with clinical and laboratory variables routinely considered when differentiating Lyme arthritis from other diagnoses, the Sofia IgG has the potential to fill an important gap in care, especially when acute decision-making is necessary. The Sofia IgG should be included in prospective research studies examining clinical prediction tools to identify children at low risk of septic arthritis.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".