Evaluation of a Combination "Lymphocyte Apoptosis Model" to Predict Survival of Sepsis Patients in an Intensive Care Unit

Wenqiang Jiang; Wenhong Zhong; Yiyu Deng; Chunbo Chen; Qiaosheng Wang; Maohua Zhou; Xusheng Li; Cheng Sun; Hongke Zeng


BMC Anesthesiol. 2018;18(89) 

In This Article

Abstract and Introduction


Background: A major challenge in sepsis intervention is unclear risk stratification. We postulated that a panel of biomarkers of lymphocyte apoptosis and immune function, termed the "lymphocyte apoptosis model," would be an effective tool for predicting 28-day survival for sepsis patients.

Methods: A total of 52 consecutive sepsis patients were enrolled. Peripheral blood samples were collected on day 1 of admission for quantification of biomarkers of lymphocyte apoptosis and immune function, including lymphocyte count, lymphocyte apoptotic percentage, expression on monocyte HLA-DR, CD4+/CD8+ T cell ratio, T helper type 1 to type 2 ratio (Th1/Th2), cytochrome c levels, and various proinflammatory cytokine levels. Sepsis severity was classified using Acute Physiology and Chronic Health Evaluation II (APACHE II) and Sequential Organ Failure Assessment (SOFA) scores. Survival was assessed at 28 days.

Results: Compared with survivors, non-survivors had significantly higher lymphocyte apoptotic percentages and plasma cytochrome c levels and significantly lower lymphocyte counts, Th1/Th2 ratios, and HLA-DR expression on day 1 of admission. Multivariate analysis identified cytochrome c levels (odds ratio [OR]1.829, p = 0.025), lymphocyte apoptotic percentage (OR 1.103, p = 0.028), lymphocyte count (OR 0.150, p = 0.047), and HLA-DR expression (OR 0.923, p = 0.021) as independent predictors of 28-day mortality. A logistic regression equation incorporating the independent risk factors predicted 28-day mortality with greater accuracy than did the APACHE II score or single components biomarkers.

Conclusions: The "lymphocyte apoptosis model" may be useful for risk stratification and predicting prognosis of sepsis patients.