title: Novel predictors of sepsis outperform the American Burn Association sepsis criteria in the burn intensive care unit patient.
abstract: The purpose of this study was to determine whether systemic inflammatory response syndrome (SIRS) and American Burn Association (ABA) criteria predict sepsis in the burn patient and develop a model representing the best combination of novel clinical sepsis predictors. A retrospective, case-controlled, within-patient comparison of burn patients admitted to a single intensive care unit from January 2005 to September 2010 was made. Blood culture results were paired with documented sepsis: positive-sick, negative-sick (collectively defined as sick), and negative-not sick. Data for all predictors were collected for the 72 hours before blood culture. Variables were evaluated using regression and area under the curve (AUC) analyses. Fifty-nine subjects represented 177 culture periods. SIRS criteria were not discriminative: 98% of the subjects met criteria. ABA sepsis criteria were different on the day before (P = .004). The six best-fit variables identified for the model included heart rate > 130 beats per min, mean arterial pressure < 60 mm Hg, base deficit < -6 mEq/L, temperature < 36°C, use of vasoactive medications, and glucose > 150 mg/dl. The model was significant in predicting positive-sick and sick, with an AUC of 0.775 (P < .001) and 0.714 (P < .001), respectively; comparatively, the ABA criteria AUC was 0.619 (P = .028) and 0.597 (P = .035), respectively. Usefulness of the ABA criteria to predict sepsis is limited to the day before blood culture is obtained. A significant contribution of this research is the identification of six novel sepsis predictors for the burn patient.
authors.affiliation: School of Nursing, University of Texas Health Science Center, Houston, Texas, USA.
authors.forename: Elizabeth A
authors.initials: EA
authors.lastname: Mann-Salinas
authors.forename: Mara M
authors.initials: MM
authors.lastname: Baun
authors.forename: Janet C
authors.initials: JC
authors.lastname: Meininger
authors.forename: Clinton K
authors.initials: CK
authors.lastname: Murray
authors.forename: James K
authors.initials: JK
authors.lastname: Aden
authors.forename: Steven E
authors.initials: SE
authors.lastname: Wolf
authors.forename: Charles E
authors.initials: CE
authors.lastname: Wade
mesh_terms: D000136:Acid-Base Equilibrium; D000328:Adult; D000704:Analysis of Variance; D019540:Area Under Curve; D015415:Biomarkers / Q000097:blood; D001786:Blood Glucose / Q000032:analysis; D001794:Blood Pressure / Q000502:physiology; D001831:Body Temperature / Q000502:physiology; D002053:Burn Units; D002056:Burns / Q000097:blood / Q000503:physiopathology*; D016022:Case-Control Studies; D005260:Female; D006339:Heart Rate / Q000502:physiology; D006801:Humans; D007362:Intensive Care Units; D016015:Logistic Models; D008297:Male; D011237:Predictive Value of Tests; D012189:Retrospective Studies; D012307:Risk Factors; D018805:Sepsis / Q000097:blood / Q000382:microbiology / Q000503:physiopathology*; D018746:Systemic Inflammatory Response Syndrome / Q000097:blood / Q000503:physiopathology*
chemical_list: D015415:Biomarkers; D001786:Blood Glucose