Details:

Alternative Title:
Arch Pediatr Adolesc Med
Publisher's site:
http://dx.doi.org/10.1001/archpediatrics.2010.250
Personal Author:
Fine, Andrew M. ; Brownstein, John S. ; Nigrovic, Lise E. ; Kimia, Amir A. ; Olson, Karen L. ; ... More +
Fine, Andrew M. ; Brownstein, John S. ; Nigrovic, Lise E. ; Kimia, Amir A. ; Olson, Karen L. ; Thompson, Amy D. ; Mandl, Kenneth D. Less -
Description:
Objective

To develop a novel diagnostic algorithm for Lyme disease among children with facial palsy by integrating public health surveillance data with traditional clinical predictors.

Design

Retrospective cohort study.

Setting

Children’s Hospital Boston emergency department,1995–2007

Patients

264 children under age 20 years presenting with peripheral facial palsy who were evaluated for Lyme disease

Main outcome measures

Multivariate regression was used to identify independent clinical and epidemiologic predictors of Lyme facial palsy.

Results

65% of children from high-risk counties during Lyme season tested positive, compared to 5% of children without geographic or seasonal risk factors present. Among patients with both seasonal and geographic risk factors, 80% with one clinical risk factor (fever or headache) and 100% with two clinical factors had Lyme. Factors independently associated with Lyme facial palsy were presentation from June-November (odds ratio 25, 95% CI 8.3–113), residence in a county where the most recent three year average Lyme incidence exceeded 4 cases/100,000 (18, 6.5–69), fever (3.9, 1.5–11), and headache (2.7, 1.3–5.8). Clinical experts correctly treated 68/94 (72%) patients with Lyme facial palsy, but a tool incorporating geographical and seasonal risk identified all 94 cases.

Conclusions

Most clinicians intuitively integrate geographic information into Lyme disease management, but we demonstrate quantitatively how formal use of geographically-based incidence in a clinical algorithm improves diagnostic accuracy. These findings demonstrate potential for improved outcomes from investments in health information technology that foster bidirectional communication between public health and clinical settings.


Subject:
[+]
Adolescent
Analysis Of Variance
Child
Child, Preschool
Cohort Studies
Confidence Intervals
Decision Support Techniques
Emergency Service, Hospital
Facial Paralysis
Female
Hospitals, Pediatric
Humans
Incidence
Linear Models
Lyme Disease
Male
Multivariate Analysis
Odds Ratio
Predictive Value Of Tests
Reproducibility Of Results
Retrospective Studies
Risk Assessment
Severity Of Illness Index
Young Adult

Source:
Arch Pediatr Adolesc Med. 165(1):61-67.
Pubmed ID:
21199982
Pubmed Central ID:
PMC3644029
Document Type:
Journal Article
Funding:
G08 LM009778/LM/NLM NIH HHS/United States ; G08LM009778/LM/NLM NIH HHS/United States ; K01HK000055/HK/PHITPO CDC HHS/United States ; P01HK000016/HK/PHITPO CDC HHS/United States ; P01HK000088-01/HK/PHITPO CDC HHS/United States ; ... More +
G08 LM009778/LM/NLM NIH HHS/United States ; G08LM009778/LM/NLM NIH HHS/United States ; K01HK000055/HK/PHITPO CDC HHS/United States ; P01HK000016/HK/PHITPO CDC HHS/United States ; P01HK000088-01/HK/PHITPO CDC HHS/United States ; R01 LM007677/LM/NLM NIH HHS/United States Less -
Place as Subject:
Boston, MA
Collection(s):
CDC Public Access
Main Document Checksum:
[+]
urn:sha256:7187ea849bebde2507ceb67d84c943fdd0eeb0538bf65a702baa3d7be003d771
File Type:

Supporting Files

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