Body temperature patterns as a predictor of hospital-acquired sepsis in afebrile adult intensive care unit patients: a case-control study

Abstract

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.

Figures

Figure 1

Illustration of temperature pattern abnormalities observed prior to fever in septic patients. The horizontal axes represent hours prior to the first fever in septic patients. The dotted lines denote a fever of 38.3°C. A normal body temperature pattern fluctuates diurnally by approximately 0.5°C around a mean of 37.0°C (A). In septic patients, temperature patterns may exhibit increases in frequency (B), increases in amplitude (C) or changes in baseline temperature (D) during the 72 hours prior to fever.

Figure 2

Identification of septic and control patients. *Sepsis was defined as the presence of a positive blood or bronchoalveolar lavage culture and at least two systemic inflammatory response syndrome criteria within 24 hours from the time the culture was ordered. LOS, length of stay; NSAID, nonsteroidal anti-inflammatory drug.

Figure 3

Example temperature curves from afebrile septic and control patients. The horizontal axes represent hours prior to the clinical suspicion of sepsis (in septic patients) or hours prior to discharge from the ICU (in control patients). The timestamp for the clinical suspicion of sepsis was defined as the time of the first fever, the time of the first culture (from any site) or the time the first antibiotic was ordered by the ICU medical staff, whichever came first. Note that the temperature plots end eight hours prior to the first clinical suspicion of sepsis.