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Background  Early recognition of patients hospitalized for sepsis at higher risk of poor clinical outcome is a mandatory task and many studies suggested that indicators of the immune status may be useful for this purpose. We performed a retrospective, monocentric cohort study to evaluate whether lymphocyte subsets may be useful in predicting in-hospital mortality of septic patients.    Methods  Data of all consecutive patients with a diagnosis of sepsis at discharge and an available peripherical blood lymphocyte subset (CD4, CD8, CD16/CD56 and CD19) analysis at hospital entry were retrospectively collected between January 2015 and August 2018. Clinical characteristics of patients, past medical history and other laboratory parameters were also considered.    Results  Two-hundred-seventy-eight septic patients, 171 (61.5%) males, mean age 63.2 ± 19.6 years, were enrolled. Total counts of lymphocytes, CD4 T cells, CD8 T cells and B cells were found significantly lower in deceased than in surviving patients. At univariate analyses, CD4 T cells/µL (OR 0.99 for each incremental unit, 95%CI 0.99–1.10, p < 0.0001), age (OR 1.06, 95%CI 1.04–1.09, p < 0.0001), procalcitonin (OR 1.01, 95%CI 1.01–1.02, p < 0.0001) and female gender (OR 2.81, 95%CI 1.49–5.28, p = 0.001) were associated with in-hospital mortality. When a dichotomic threshold of < 400/µL for CD4 T cells as a dependent variable was considered in multivariate models, age (OR 1.04; 95%CI 1.01–1.09, p = 0.018); female gender (OR 3.18; 95%CI 1.40–7.20, p = 0.006), qSOFA (OR 4.00, 95%CI 1.84–8.67, p < 0.001) and CD4 T cells < 400/µL (OR 5.3; 95%CI 1.65–17.00, p = 0.005) were the independent predictors.    Conclusions  In adjunct to biomarkers routinely determined for the prediction of prognosis in sepsis, CD4 T lymphocytes, measured at hospital entry, may be useful in identifying patients at higher risk of in-hospital death.    Supplementary Information  The online version contains supplementary material available at 10.1186/s12879-021-06481-1.

Circulating lymphocyte subsets as promising biomarkers to identify septic patients at higher risk of unfavorable outcome