A SCORING SYSTEM FOR PREDICTING GROUP-A STREPTOCOCCAL THROAT INFECTION

Background. Sore throat is very common in general practice and is usua lly caused by viral infection. Nevertheless, up to 95% of patients may be treated with antibiotics. Previous diagnostic systems have not tra nsferred well from one area to another because of an inability to allo w for changing prevalence of streptococcus. Aim. To measure the occurr ence rates of symptoms and signs in sore throat patients with and with out streptococcal infection, and to develop a Bayesian scoring system which is easily adapted for prevalence to predict if patients have bac terial infection. Method. Occurrence rates of symptoms and signs were measured for 206 patients with sore throat symptoms over a 3-year peri od. Bayesian probability scores (B-scores) for each data item were cal culated from the ocurrence rates in the patients with positive throat cultures for group A streptococci and the rates in patients with negat ive throat cultures. The B-score values were then used to predict the probability of positive culture for each patient. Results. The strepto coccal throat B-score system predicted positive culture with a sensiti vity of 71% and a specificity of 71%. In comparison, the unaided gener al practitioners predicted infection with a sensitivity of 61% and a s pecificity of 65%. If the B-score prediction had been used to decide o n treatment, more patients with streptococci present on culture would have been treated with antibiotic (71% instead of 68%) and appreciably fewer patients with negative streptococcal cultures would have been t reated (29% instead of 59%). Conclusion. Use of the B-score system cou ld result in significant savings in unnecessary antibiotic prescriptio n, and unnecessary throat swab cultures, while achieving better levels of treatment.