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Prospective validation of a clinical prediction model for Lyme meningitis in children
Aris C Garro1, Maia Rutman, Kari Simonsen
1Rhode Island Hospital, Pediatric Emergency Medicine, Claverick Building, 2nd Floor, Providence, RI 02906, USA. agarro@lifespan.org
Objective:
Lyme meningitis is difficult to differentiate from other causes of aseptic meningitis in Lyme disease-endemic regions. Parenteral antibiotics are indicated for Lyme meningitis but not viral causes of aseptic meningitis. A clinical prediction model was developed to distinguish Lyme meningitis from other causes of aseptic meningitis. Our objective was to prospectively validate this model.
Methods:
Children between 2 and 18 years of age presenting to Hasbro Children's Hospital from April through October of 2006 and 2007 were enrolled if a lumbar puncture for meningitis showed a cerebrospinal fluid white blood cell count of >8 cells per microL. Cerebrospinal fluid was sent for Lyme antibody testing. The probability of Lyme meningitis was calculated by using the percentage of cerebrospinal fluid mononuclear cells, duration of headache, and presence of cranial neuropathy by using the prediction model. Definite Lyme meningitis cases were defined as cerebrospinal fluid pleocytosis with (1) positive Lyme serology confirmed by immunoblot or (2) erythema migrans rash. Possible Lyme meningitis cases were defined as cerebrospinal fluid pleocytosis with positive cerebrospinal fluid Lyme antibody. Sensitivity, specificity, and likelihood ratios for definite and possible Lyme meningitis were determined by using 10% increments of calculated probability of Lyme meningitis.
Results:
Fifty children were enrolled, including 14 children with definite Lyme meningitis, 6 with possible Lyme meningitis, and 30 with aseptic meningitis. A calculated probability of <10% for Lyme meningitis had a negative likelihood ratio of 0.006 for definite and possible Lyme meningitis cases. A calculated probability of >50% for Lyme meningitis had a positive likelihood ratio of 100 using these definitions.
Conclusions:
A clinical prediction model using the percentage of cerebrospinal fluid mononuclear cells, headache duration, and presence of cranial neuropathy can differentiate children with Lyme meningitis from children with aseptic meningitis. Our findings suggest categories of low (<10%), indeterminate (10%-50%), and high (>50%) probability of Lyme meningitis.
Insights
A clinical prediction model accurately differentiates Lyme meningitis from aseptic meningitis in children. The model uses cerebrospinal fluid cell counts, headache duration, and cranial neuropathy to assess probability, aiding treatment decisions.
Area of Science:
- Pediatric Infectious Diseases
- Neurology
- Clinical Diagnostics
Background:
- Lyme meningitis is challenging to distinguish from other aseptic meningitis causes in endemic areas.
- Accurate differentiation is crucial as Lyme meningitis requires antibiotic treatment, unlike viral meningitis.
Purpose of the Study:
- To prospectively validate a clinical prediction model for differentiating Lyme meningitis from other causes of aseptic meningitis in children.
- To assess the model's utility in guiding clinical management and antibiotic therapy decisions.
Main Methods:
- Prospective validation of a prediction model in children (2-18 years) with meningitis.
- Model incorporates cerebrospinal fluid mononuclear cell percentage, headache duration, and cranial neuropathy.
- Case definitions included definite (pleocytosis with positive Lyme serology/rash) and possible (pleocytosis with positive CSF Lyme antibody) Lyme meningitis.
Main Results:
- The model demonstrated high accuracy in differentiating Lyme meningitis.
- A calculated probability <10% had a negative likelihood ratio of 0.006 for Lyme meningitis.
- A calculated probability >50% had a positive likelihood ratio of 100 for Lyme meningitis.
Conclusions:
- The clinical prediction model effectively distinguishes pediatric Lyme meningitis from aseptic meningitis.
- The model categorizes probability into low (<10%), indeterminate (10%-50%), and high (>50%) ranges.
- This tool can aid clinicians in diagnosing and managing suspected cases of Lyme meningitis in children.
