title: Development and validation of a clinical prediction rule for candidemia in hospitalized patients with severe sepsis and septic shock.
abstract: OBJECTIVE
  To develop and internally validate a prediction rule for the presence of candidemia in patients with severe sepsis and septic shock (candidemia rule) that will fill the gap left by previous rules. To compare the accuracy of the available Candida prediction models.
  
  
  METHODS
  Retrospective cohort study.
  
  
  METHODS
  Barnes-Jewish Hospital, St. Louis, Missouri.
  
  
  METHODS
  Two thousand five hundred ninety-seven consecutive patients with a positive blood culture and severe sepsis or septic shock.
  
  
  METHODS
  Logistic regression and a bootstrap resampling procedure were employed for model development and internal validation.
  
  
  RESULTS
  Two hundred sixty-six (10.2%) had blood cultures positive for Candida spp. Mortality was significantly higher in patients with candidemia than in patients with bacteremia (47.0% versus 28.4%; P<.001). Administration of total parenteral nutrition, prior antibiotic exposure, transfer from an outside hospital or admission from a nursing home, mechanical ventilation and presence of a central vein catheter were independent predictors of candidemia while the lung as a source for infection was protective. The prediction rule had an area under the receiver operating characteristic curve of 0.798 (95% CI 0.77-0.82). Internal validation using bootstrapping technique with 1000 repetitions produced a similar area under the receiver operating characteristic curve of 0.797 (bias, -0.037; root mean square error 0.039). Our prediction rule outperformed previous rules with a better calibration slope of 0.96 and Brier score of 0.08.
  
  
  CONCLUSIONS
  We developed and internally validated a prediction rule for candidemia in hospitalized patients with severe sepsis and septic shock that outperformed previous prediction rules. Our study suggests that locally derived prediction models may be superior by accounting for local case mix and risk factor distribution.
authors: Division of Pulmonary, Critical Care, and Sleep Medicine And Division of Infectious Diseases, University of New Mexico School of Medicine, Albuquerque, NM.
authors: Cristina Vazquez
authors: CV
authors: Guillamet
authors: Division of Pulmonary, Critical Care, and Sleep Medicine, University of New Mexico School of Medicine, Albuquerque, NM.
authors: Rodrigo
authors: R
authors: Vazquez
authors: Division of Pharmacy Practice, St. Louis College of Pharmacy, St. Louis, MO.
authors: Scott T
authors: ST
authors: Micek
authors: Division of Translational Informatics, University of New Mexico School of Medicine, Albuquerque, NM.
authors: Oleg
authors: O
authors: Ursu
authors: Division of Pulmonary and Critical Care Medicine, Washington University School of Medicine, St. Louis, MO. Electronic address: mkollef@dom.wustl.edu.
authors: Marin
authors: M
authors: Kollef
mesh_terms: D002175:Candida / Q000302:isolation & purification; D058387:Candidemia / Q000453:epidemiology* / Q000401:mortality / Q000517:prevention & control; D015331:Cohort Studies; D003661:Decision Support Techniques; D005260:Female; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D008923:Missouri / Q000453:epidemiology; D011237:Predictive Value of Tests; D012372:ROC Curve; D012189:Retrospective Studies; D012307:Risk Factors; D012772:Shock, Septic / Q000453:epidemiology* / Q000401:mortality / Q000517:prevention & control
keywords: Candida; Mortality; Outcomes; Prediction; Septic shock