title: A predictive model to identify Clostridium difficile toxin in hospitalized patients with diarrhea.
abstract: OBJECTIVE
  Although Clostridium difficile is a common pathogen in hospitalized patients with diarrhea, no study has attempted to develop a predictive model to estimate the likelihood of C. difficile positivity.
  
  
  METHODS
  We conducted a cross-sectional study at a single hospital of 271 patients with diarrhea for whom stool was tested for C. difficile toxin. The sample was randomly divided into a subset to derive the model (n = 180) and another to validate it (n =91), and independent predictors of toxin positivity were identified using logistical regression analysis.
  
  
  RESULTS
  C. difficile toxin was present in 81 patients and absent in 190. In the derivation set, a positive toxin was independently predicted (p < 0.0005) by readmission within 2 wk of prior hospitalization, by a white blood cell count > or = 10,000/mm3, and by presence of fecal leukocytes. In the validation set, C. difficile toxin was present in 24, 29, and 77% of patients with 0, 1, and > or = 2 risk factors, respectively.
  
  
  CONCLUSIONS
  If validated prospectively and/or other centers, the model could identify patients who should be considered for empirical management while awaiting results of toxin assays.
authors.affiliation: Department of Medicine, Case Western Reserve University School of Medicine, University Hospitals of Cleveland, Ohio 44106, USA.
authors.forename: G S
authors.initials: GS
authors.lastname: Cooper
authors.forename: M M
authors.initials: MM
authors.lastname: Lederman
authors.forename: R A
authors.initials: RA
authors.lastname: Salata
mesh_terms: D000368:Aged; D001427:Bacterial Toxins / Q000032:analysis*; D016009:Chi-Square Distribution; D016360:Clostridioides difficile; D003430:Cross-Sectional Studies; D003967:Diarrhea / Q000453:epidemiology / Q000209:etiology*; D005243:Feces / Q000737:chemistry; D005260:Female; D006760:Hospitalization; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D011379:Prognosis; D012372:ROC Curve; D011897:Random Allocation; D018709:Statistics, Nonparametric
chemical_list: D001427:Bacterial Toxins