A Clinical Prediction Rule for Bacterial Musculoskeletal Infections in Children with Monoarthritis in Lyme Endemic Regions

Abstract

Study objective: Children with a bacterial musculoskeletal infection (MSKI) require prompt identification and treatment. In Lyme disease endemic areas, children with an MSKI can present similarly to those with Lyme arthritis. Our goal was to derive a clinical prediction rule to accurately identify children at a low risk for an MSKI.

Methods: We enrolled children with monoarthritis presenting to 1 of 6 Pedi Lyme Net centers and performed a procalcitonin (PCT) and a first-tier Lyme C6 enzyme immunoassay (EIA) test. Our primary outcome was an MSKI (septic arthritis, osteomyelitis, or pyomyositis). Using recursive partitioning with k-fold cross validation, we derived a clinical prediction rule to identify children at a low risk of an MSKI. We calculated the accuracy of our novel rule in a derivation cohort.

Results: Of the 735 children in the derivation cohort with an available research biosample, 39 (5%) had an MSKI (18 had septic arthritis, 20 had osteomyelitis, and 1 had pyomyositis), 260 (37%) had Lyme arthritis, and 436 (53%) had other inflammatory arthritis. Children with a PCT level of more than or equal to 0.50 ng/mL and those with a C-reactive protein (CRP) level of more than or equal to 0.6 mg/dL with a negative Lyme C6 EIA were classified as not low risk for an MSKI. Of the 451 (61%) children categorized as low risk, none had an MSKI (sensitivity 100%, 95% confidence interval 91.0% to 100%; specificity 74.2%, 95% confidence interval 70.5% to 77.6%).

Conclusion: A novel clinical decision rule that includes PCT, CRP, and a first-tier Lyme EIA was highly sensitive for MSKIs. Although broader external validation is required, the application of this rule may safely reduce invasive testing, procedures, and treatment for low risk children.