EFFECT OF STRATIFIED DOSE OF NOREPINEPHRINE ON CELLULAR IMMUNE RESPONSE IN PATIENTS WITH SEPTIC SHOCK AND THE CONSTRUCTION OF A PROGNOSTIC RISK MODEL

Objective:To explore the effect of a stratified dose of norepinephrine (NE) on cellular immune response in patients with septic shock, and to construct a prognostic model of septic shock. Methods:A total of 160 patients with septic shock (B group) and 58 patients with sepsis (A group) were given standard cluster therapy. Patients with septic shock were divided into four groups (B1-B4 groups: 0.01–0.2, 0.2–0.5, 0.5–1.0, and >1 μg/kg/min) according to the quartile method of the early (72 h) time-weighted average dose of NE and clinical application. The cellular immune indexes at 24 h (T0) and 4–7 days (T1) after admission were collected. The difference method was used to explore the effect of NE stratified dose on cellular immune effect in patients with septic shock. A multivariate COX proportional risk regression model was used to analyze the independent prognostic risk factors, and a prognostic risk model was constructed. Results:The differences of ΔIL-1β, ΔIL-6, ΔIL-10, absolute value difference of T lymphocyte (ΔCD3+/CD45+#) and Th helper T cell (ΔCD3+ CD4+/CD45+#), CD64 infection index difference, ΔmHLA-DR, regulatory T lymphocyte ratio difference (ΔTregs%) between group A, B1, B2, B3, and B4 were statistically significant (P< 0.05). There was a nonlinear relation between the stratified dose of NE and ΔIL-6, ΔIL-10, ΔCD3+/CD45+#, ΔmHLA-DR%. The threshold periods of NE-induced proinflammatory and anti-inflammatory immune changes were 0.3–0.5 μg/kg/min. Multivariate COX model regression analysis showed that age, nutritional patterns, weighted average dose of norepinephrine, IL-6, absolute value of T lymphocytes, and mHLA-DR were independent risk factors affecting the prognosis of patients with septic shock (P< 0.05). The prognostic risk model was constructed (AUC value = 0.813, 95% CI: 0.752–0.901). Conclusion:NE has a certain inhibitory effect on cellular immune function in patients with septic shock. A prognostic risk model was constructed with stronger prediction efficiency for the prognosis of patients with septic shock.