The utility of bandemia in prognostication and prediction of mortality in sepsis. (May 2023)

• Record Type: Journal Article
• Authors: Prasanna, Nivedita; DelPrete, Benjamin; Ho, Geoffrey; Yamane, David; Elshikh, Amira; Rashed, Amir; Sparks, Andrew; Davison, Danielle; Hawkins, Katrina
• Is Part Of: Journal of the Intensive Care Society. Volume 24:Number 2(2023)
• Page Start: 201
• Page End: 205
• Publication Date: 2023-05
• Subjects: Sepsis -- biomarkers -- bandemia; Critical care medicine -- Periodicals; Intensive care units -- Periodicals; 616.028
• DOI: 10.1177/17511437211069307
• Languages: English
• ISSNs: 1751-1437

Abstract

Background: Bandemia, defined as a band count >10%, is indicative of underlying infection and is increasingly being used for early detection of sepsis. While an absolute band level has been linked to worse outcomes, its trend has not been extensively studied as a prognostic marker. In this study, we assessed patients admitted to the ICU with sepsis or septic shock and evaluated the correlation between bandemia trends and clinical trajectory among these patients. Methods: This study was a retrospective chart review. Band counts, serum lactate levels, and SOFA scores at 0 and 72 h after admission to the ICU were collected. Patients were risk stratified into groups depending on their SOFA trends, and corresponding band trends and serum lactate levels were compared. Results: 134 patients were included for analysis. There was a statistically significant decrease in bandemia trends for patients with a reduction in SOFA scores [median (IQR)−4.5 (−11, 0); p < 0.0001], and a statistically significant increase in bandemia trends for patients with worsening SOFA scores [median (IQR) 4 (0, 8); p = 0.0007] . Conclusion: Early trends of serum band levels in patients with sepsis or septic shock may help to predict a clinical trajectory and overall prognosis. More investigation is warranted as to whether incorporating bandemia trends, when used in conjunction with other known markers such as lactate levels, may help to guide bedside clinical decisions such as risk stratification, tailored therapies, and ultimately improve outcomes.