Background The Centor and McIsaac scores guide testing and treatment for group A streptococcal (GAS) pharyngitis in patients presenting with a sore throat, but were derived on relatively small samples. We perform a national-scale validation of the prediction models on a large, geographically diverse population. Methods Analysis of data collected from 206,870 patients 3 years and above who presented with a painful throat to a United States national retail health chain, from September 2006-December 2008. Main outcome meaures were the proportions of patients testing positive for GAS pharyngitis according to Centor and McIsaac scores (both scales 0-4). Results For patients 15 years and older, 23% (95% confidence interval (CI) 22%-23%) tested GAS positive including 7% (7-8%) of those with a Centor score of 0, 12% (11-12%) with 1, 21% (21-22%) with 2, 38% (38-39%) with 3, and 57% (56-58%) with 4. For patients 3 years and older, 27% (95% CI 27-27%) tested GAS positive with 8% (8-9%) of those testing positive with McIsaac score 0, 14% (13-14%) with 1, 23% (23-23%) with 2, 37% (37-37%) with 3, and 55% (55-56%) with 4. 95% CI’s overlapped between the MinuteClinic derived probabilities and the prior reports. Conclusion Our study validates the Centor and McIsaac scores and more precisely classifies risk of GAS infection among patients presenting with a painful throat to a retail health chain.

Purpose To develop and validate the positive predictive value (PPV) of an algorithm to identify anaphylaxis using health plan administrative and claims data. Previously published positive predictive values (PPVs) for anaphylaxis using ICD-9-CM codes range from 52-57%. Methods We conducted a retrospective study using administrative and claims data from eight health plans. Using diagnosis and procedure codes, we developed an algorithm to identify potential cases of anaphylaxis from the Mini-Sentinel Distributed Database between January 2009 and December 2010. A random sample of medical charts (N=150) was identified for chart abstraction. Two physician adjudicators reviewed each potential case. Using physician adjudicator judgments on whether the case met diagnostic criteria for anaphylaxis, we calculated a PPV for the algorithm. Results Of the 122 patients for whom complete charts were received, 77 were judged by physician adjudicators to have anaphylaxis. The PPV for the algorithm was 63.1% (95% CI: 53.9%-71.7%), using the clinical criteria by Sampson as the gold standard. The PPV was highest for inpatient encounters with ICD-9-CM codes of 995.0 or 999.4. By combining only the top performing ICD-9-CM codes, we identified an algorithm with a PPV of 75.0%, but only 66% of cases of anaphylaxis were identified using this modified algorithm. Conclusions The PPV for the ICD-9-CM-based algorithm for anaphylaxis was slightly higher than PPV estimates reported in prior studies, but remained low. We were able to identify an algorithm which optimized the PPV but demonstrated lower sensitivity for anaphylactic events.

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Lyme disease is a frequent cause of facial palsy in children living in an endemic region. Serologic testing and empiric antibiotics should be strongly considered, especially when children present during peak Lyme disease season or with a headache.