title: [Multivariate model to predict Streptococcus pyogenes tonsillitis].
abstract: OBJECTIVE
  to develop a multivariate model to predict the Streptococcus pyogenes isolation in patients with acute tonsillitis.
  
  
  METHODS
  cross-sectional analytic study on patients with acute tonsillitis without a recent history of antimicrobial consumption. We evaluated 14 signs and 18 symptoms. A pharyngeal culture was realized on 5% sheep blood agar. Group A streptococci was identified by standard methods.
  
  
  METHODS
  sensitivity, specificity, predictive values, chi2, Fisher's exact test, crude and adjusted odds ratio (OR) with 95% CI using dichotomical logistic regression with direct method and Hosmer and Lemeshow-goodness-fit test.
  
  
  RESULTS
  there were 213 participants, 37% were males; a mean age of 14.9 years. We isolated Streptococcus pyogenes in 15%, and 84 % of them had received antimicrobials. We identified signs and symptoms associated with Streptococcus pyogenes isolation: painful swallowing (OR=4.45, 95% CI = 1.13-17.53); tonsils with exudates (OR=3.20, 95% CI = 1.22-8.43); smelly breath (OR=2.78, 95% CI = 1.09-7.10); painful neck nodes (OR=2.70, 95% CI = 1.05-6.96). The presence of nasal symptoms was a protective factor (OR=0.25, 95% CI = 0.09-0.71).
  
  
  CONCLUSIONS
  the prevalence of Streptococcus pyogenes tonsillitis was similar to other reports. We found signs and symptoms associated to Streptococcus pyogenes isolation that allowed us to elaborate a decision algorithm.
authors.affiliation: Centro de Investigación Biomédica de Occidente, Instituto Mexicano del Seguro Social, Guadalajara, Jalisco. avillase@prodigy.net.mx
authors.forename: Alberto
authors.initials: A
authors.lastname: Villaseñor-Sierra
authors.forename: José Ramiro
authors.initials: JR
authors.lastname: Caballero-Hoyos
authors.forename: Juan José
authors.initials: JJ
authors.lastname: Jáuregui-Lomelí
authors.forename: Jesús
authors.initials: J
authors.lastname: Flores-Sánchez
authors.forename: Francisco
authors.initials: F
authors.lastname: Martínez-Sandoval
mesh_terms: D000208:Acute Disease; D000293:Adolescent; D000328:Adult; D000465:Algorithms; D002648:Child; D002675:Child, Preschool; D003430:Cross-Sectional Studies; D005260:Female; D005544:Forecasting; D006801:Humans; D008297:Male; D008875:Middle Aged; D008962:Models, Theoretical; D013290:Streptococcal Infections / Q000175:diagnosis* / Q000382:microbiology*; D013297:Streptococcus pyogenes; D014069:Tonsillitis / Q000175:diagnosis* / Q000382:microbiology*; D055815:Young Adult