Brad S Karon1, Nicole V Tolan2, Amy M Wockenfus2, Darci R Block2, Nikola A Baumann2, Sandra C Bryant3, Casey M Clements4. 1. Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, United States. Electronic address: Karon.bradley@mayo.edu. 2. Department of Laboratory Medicine and Pathology, Mayo Clinic, Rochester, MN 55905, United States. 3. Division of Biomedical Statistics and Informatics, Mayo Clinic, Rochester, MN 55905, United States. 4. Department of Emergency Medicine, Mayo Clinic, Rochester, MN 55905, United States.
Abstract
BACKGROUND: Lactate, white blood cell (WBC) and neutrophil count, procalcitonin and immature granulocyte (IG) count were compared for the prediction of sepsis, and severe sepsis or septic shock, in patients presenting to the emergency department (ED). METHODS: We prospectively enrolled 501 ED patients with a sepsis panel ordered for suspicion of sepsis. WBC, neutrophil, and IG counts were measured on a Sysmex XT-2000i analyzer. Lactate was measured by i-STAT, and procalcitonin by Brahms Kryptor. We classified patients as having sepsis using a simplification of the 1992 consensus conference sepsis definitions. Patients with sepsis were further classified as having severe sepsis or septic shock using established criteria. Univariate receiver operating characteristic (ROC) analysis was performed to determine odds ratio (OR), area under the ROC curve (AUC), and sensitivity/specificity at optimal cut-off for prediction of sepsis (vs. no sepsis), and prediction of severe sepsis or septic shock (vs. no sepsis). RESULTS: There were 267 patients without sepsis; and 234 with sepsis, including 35 patients with severe sepsis or septic shock. Lactate had the highest OR (1.44, 95th% CI 1.20-1.73) for the prediction of sepsis; while WBC, neutrophil count and percent (neutrophil/WBC) had OR>1.00 (p<0.05). All biomarkers had AUC<0.70 and sensitivity and specificity <70% at the optimal cut-off. Initial lactate was the best biomarker for predicting severe sepsis or septic shock, with an odds ratio (95th% CI) of 2.70 (2.02-3.61) and AUC 0.89 (0.82-0.96). CONCLUSION: Traditional biomarkers (lactate, WBC, neutrophil count, procalcitonin, IG) have limited utility in the prediction of sepsis.
BACKGROUND:Lactate, white blood cell (WBC) and neutrophil count, procalcitonin and immature granulocyte (IG) count were compared for the prediction of sepsis, and severe sepsis or septic shock, in patients presenting to the emergency department (ED). METHODS: We prospectively enrolled 501 ED patients with a sepsis panel ordered for suspicion of sepsis. WBC, neutrophil, and IG counts were measured on a Sysmex XT-2000i analyzer. Lactate was measured by i-STAT, and procalcitonin by Brahms Kryptor. We classified patients as having sepsis using a simplification of the 1992 consensus conference sepsis definitions. Patients with sepsis were further classified as having severe sepsis or septic shock using established criteria. Univariate receiver operating characteristic (ROC) analysis was performed to determine odds ratio (OR), area under the ROC curve (AUC), and sensitivity/specificity at optimal cut-off for prediction of sepsis (vs. no sepsis), and prediction of severe sepsis or septic shock (vs. no sepsis). RESULTS: There were 267 patients without sepsis; and 234 with sepsis, including 35 patients with severe sepsis or septic shock. Lactate had the highest OR (1.44, 95th% CI 1.20-1.73) for the prediction of sepsis; while WBC, neutrophil count and percent (neutrophil/WBC) had OR>1.00 (p<0.05). All biomarkers had AUC<0.70 and sensitivity and specificity <70% at the optimal cut-off. Initial lactate was the best biomarker for predicting severe sepsis or septic shock, with an odds ratio (95th% CI) of 2.70 (2.02-3.61) and AUC 0.89 (0.82-0.96). CONCLUSION: Traditional biomarkers (lactate, WBC, neutrophil count, procalcitonin, IG) have limited utility in the prediction of sepsis.
Authors: Adam R Aluisio; Stephanie Garbern; Tess Wiskel; Zeta A Mutabazi; Olivier Umuhire; Chin Chin Ch'ng; Kristina E Rudd; Jeanne D'Arc Nyinawankusi; Jean Claude Byiringiro; Adam C Levine Journal: Am J Emerg Med Date: 2018-03-10 Impact factor: 2.469
Authors: Laura Evans; Andrew Rhodes; Waleed Alhazzani; Massimo Antonelli; Craig M Coopersmith; Craig French; Flávia R Machado; Lauralyn Mcintyre; Marlies Ostermann; Hallie C Prescott; Christa Schorr; Steven Simpson; W Joost Wiersinga; Fayez Alshamsi; Derek C Angus; Yaseen Arabi; Luciano Azevedo; Richard Beale; Gregory Beilman; Emilie Belley-Cote; Lisa Burry; Maurizio Cecconi; John Centofanti; Angel Coz Yataco; Jan De Waele; R Phillip Dellinger; Kent Doi; Bin Du; Elisa Estenssoro; Ricard Ferrer; Charles Gomersall; Carol Hodgson; Morten Hylander Møller; Theodore Iwashyna; Shevin Jacob; Ruth Kleinpell; Michael Klompas; Younsuck Koh; Anand Kumar; Arthur Kwizera; Suzana Lobo; Henry Masur; Steven McGloughlin; Sangeeta Mehta; Yatin Mehta; Mervyn Mer; Mark Nunnally; Simon Oczkowski; Tiffany Osborn; Elizabeth Papathanassoglou; Anders Perner; Michael Puskarich; Jason Roberts; William Schweickert; Maureen Seckel; Jonathan Sevransky; Charles L Sprung; Tobias Welte; Janice Zimmerman; Mitchell Levy Journal: Intensive Care Med Date: 2021-10-02 Impact factor: 17.440