TY - JOUR
T1 - Body temperature patterns as a predictor of hospital-acquired sepsis in afebrile adult intensive care unit patients
T2 - A case-control study
AU - Drewry, Anne M.
AU - Fuller, Brian M.
AU - Bailey, Thomas C.
AU - Hotchkiss, Richard S.
N1 - Funding Information:
The authors thank Karen Steger-May, with the Division of Biostatistics at Washington University in St Louis, for her assistance with statistical analysis. AMD, BMF and TCB each acknowledge that this publication was made possible by the Washington University Institute of Clinical and Translational Sciences grant UL1 TR000448 from the National Center for Advancing Translational Sciences. RSH was supported by National Institutes of Health (NIH) grants GM 44118 and GM 55194. The content is solely the responsibility of the authors and does not necessarily represent the official views of the NIH.
Funding Information:
RSH reports receiving grant support from MedImmune, Bristol-Myers Squibb, Agennix and Aurigene. AMD, BMF and TCB declare that they have no competing interests.
PY - 2013/9/12
Y1 - 2013/9/12
N2 - Introduction: Early treatment of sepsis improves survival, but early diagnosis of hospital-acquired sepsis, especially in critically ill patients, is challenging. Evidence suggests that subtle changes in body temperature patterns may be an early indicator of sepsis, but data is limited. The aim of this study was to examine whether abnormal body temperature patterns, as identified by visual examination, could predict the subsequent diagnosis of sepsis in afebrile critically ill patients. Methods: Retrospective case-control study of 32 septic and 29 non-septic patients in an adult medical and surgical ICU. Temperature curves for the period starting 72 hours and ending 8 hours prior to the clinical suspicion of sepsis (for septic patients) and for the 72-hour period prior to discharge from the ICU (for non-septic patients) were rated as normal or abnormal by seven blinded physicians. Multivariable logistic regression was used to compare groups in regard to maximum temperature, minimum temperature, greatest change in temperature in any 24-hour period, and whether the majority of evaluators rated the curve to be abnormal. Results: Baseline characteristics of the groups were similar except the septic group had more trauma patients (31.3% vs. 6.9%, p = .02) and more patients requiring mechanical ventilation (75.0% vs. 41.4%, p = .008). Multivariable logistic regression to control for baseline differences demonstrated that septic patients had significantly larger temperature deviations in any 24-hour period compared to control patients (1.5°C vs. 1.1°C, p = .02). An abnormal temperature pattern was noted by a majority of the evaluators in 22 (68.8%) septic patients and 7 (24.1%) control patients (adjusted OR 4.43, p = .017). This resulted in a sensitivity of 0.69 (95% CI [confidence interval] 0.50, 0.83) and specificity of 0.76 (95% CI 0.56, 0.89) of abnormal temperature curves to predict sepsis. The median time from the temperature plot to the first culture was 9.40 hours (IQR [inter-quartile range] 8.00, 18.20) and to the first dose of antibiotics was 16.90 hours (IQR 8.35, 34.20). Conclusions: Abnormal body temperature curves were predictive of the diagnosis of sepsis in afebrile critically ill patients. Analysis of temperature patterns, rather than absolute values, may facilitate decreased time to antimicrobial therapy.
AB - Introduction: Early treatment of sepsis improves survival, but early diagnosis of hospital-acquired sepsis, especially in critically ill patients, is challenging. Evidence suggests that subtle changes in body temperature patterns may be an early indicator of sepsis, but data is limited. The aim of this study was to examine whether abnormal body temperature patterns, as identified by visual examination, could predict the subsequent diagnosis of sepsis in afebrile critically ill patients. Methods: Retrospective case-control study of 32 septic and 29 non-septic patients in an adult medical and surgical ICU. Temperature curves for the period starting 72 hours and ending 8 hours prior to the clinical suspicion of sepsis (for septic patients) and for the 72-hour period prior to discharge from the ICU (for non-septic patients) were rated as normal or abnormal by seven blinded physicians. Multivariable logistic regression was used to compare groups in regard to maximum temperature, minimum temperature, greatest change in temperature in any 24-hour period, and whether the majority of evaluators rated the curve to be abnormal. Results: Baseline characteristics of the groups were similar except the septic group had more trauma patients (31.3% vs. 6.9%, p = .02) and more patients requiring mechanical ventilation (75.0% vs. 41.4%, p = .008). Multivariable logistic regression to control for baseline differences demonstrated that septic patients had significantly larger temperature deviations in any 24-hour period compared to control patients (1.5°C vs. 1.1°C, p = .02). An abnormal temperature pattern was noted by a majority of the evaluators in 22 (68.8%) septic patients and 7 (24.1%) control patients (adjusted OR 4.43, p = .017). This resulted in a sensitivity of 0.69 (95% CI [confidence interval] 0.50, 0.83) and specificity of 0.76 (95% CI 0.56, 0.89) of abnormal temperature curves to predict sepsis. The median time from the temperature plot to the first culture was 9.40 hours (IQR [inter-quartile range] 8.00, 18.20) and to the first dose of antibiotics was 16.90 hours (IQR 8.35, 34.20). Conclusions: Abnormal body temperature curves were predictive of the diagnosis of sepsis in afebrile critically ill patients. Analysis of temperature patterns, rather than absolute values, may facilitate decreased time to antimicrobial therapy.
UR - http://www.scopus.com/inward/record.url?scp=84883703903&partnerID=8YFLogxK
U2 - 10.1186/cc12894
DO - 10.1186/cc12894
M3 - Article
C2 - 24028682
AN - SCOPUS:84883703903
SN - 1364-8535
VL - 17
JO - Critical Care
JF - Critical Care
IS - 5
M1 - R200
ER -