Performance of a predictive model for streptococcal pharyngitis in children

Context: Group A β-hemolytic streptococcus (GABHS) pharyngitis is a common childhood illness. The clinical diagnosis is difficult to determine and laboratory tests have limitations; hence, the condition is generally over-diagnosed and overtreated. Several clinical pediatric-specific predictive models have been published but none have been prospectively studied. Objective: To test the performance of a previously published predictive model for GABHS pharyngitis in children in different clinical settings and during different seasons. Design: Prospective cohort study. Settings: Pediatric emergency department and 2 pediatric outpatient clinics. Patients: Children aged between 1 and 18 years with pharyngitis on initial examination at study sites between April 1, 1999, and March 31, 2000. Interventions: Recording of clinical features during initial evaluation using a standardized form and recovery of GABHS from patients' throats using reference standard methods. Main Outcome Measures: Posttest probability for GABHS positive throat culture associated with the model's positive predictors (moderate to severe tonsillar swelling, cervical lymphadenopathy [moderate to severe tenderness and enlargement of cervical lymph nodes], scarletiniform rash, and the absence of coryza) and the models' negative predictors (absence of the above signs and the presence of coryza). Results: Of 587 patients analyzed, 218 (37%) had a positive throat culture for GABHS. Forty-nine percent were boys. Mean ± SD age was 6.7 ± 3.9 years. There was no difference between the subsets within the sample. The post-test probability values for a positive throat culture associated with positive and negative predictors of the model were 79% and 12%, respectively. Conclusions: A pediatric predictive model for GABHS pharyngitis performed better than physicians' subjective estimates for a positive throat culture and was comparable with a rapid antigen detection test. The model performed consistently well in different populations and across seasons. It can be useful if reliable microbiological testing and/or follow-up are not attainable.