title: Physiological monitoring for critically ill patients: testing a predictive model for the early detection of sepsis.
abstract: OBJECTIVE
  To assess the predictive value for the early detection of sepsis of the physiological monitoring parameters currently recommended by the Surviving Sepsis Campaign.
  
  
  METHODS
  The Project IMPACT data set was used to assess whether the physiological parameters of heart rate, mean arterial pressure, body temperature, and respiratory rate can be used to distinguish between critically ill adult patients with and without sepsis in the first 24 hours of admission to an intensive care unit.
  
  
  RESULTS
  All predictor variables used in the analyses differed significantly between patients with sepsis and patients without sepsis. However, only 2 of the predictor variables, mean arterial pressure and high temperature, were independently associated with sepsis. In addition, the temperature mean for hypothermia was significantly lower in patients without sepsis. The odds ratio for having sepsis was 2.126 for patients with a temperature of 38 degrees C or higher, 3.874 for patients with a mean arterial blood pressure of less than 70 mm Hg, and 4.63 times greater for patients who had both of these conditions.
  
  
  CONCLUSIONS
  The results support the use of some of the guidelines of the Surviving Sepsis Campaign. However, the lowest mean temperature was significantly less for patients without sepsis than for patients with sepsis, a finding that calls into question the clinical usefulness of using hypothermia as an early predictor of sepsis. Alone the group of variables used is not sufficient for discriminating between critically ill patients with and without sepsis.
authors.affiliation: Philips Medical Systems, Andover, MA, USA. Karen.Giuliano@philips.com
authors.forename: Karen K
authors.initials: KK
authors.lastname: Giuliano
mesh_terms: D001794:Blood Pressure; D001831:Body Temperature; D016638:Critical Illness; D042241:Early Diagnosis; D005260:Female; D006339:Heart Rate; D006801:Humans; D007362:Intensive Care Units; D016015:Logistic Models; D008297:Male; D008991:Monitoring, Physiologic; D012119:Respiration; D012680:Sensitivity and Specificity; D018805:Sepsis / Q000175:diagnosis*