#2643 CD4+ T cells are associated with mortality in males with type 2 cardiorenal syndrome independently of the Seattle Heart Failure Model score

Abstract Background and Aims Immune system dysregulation appears to contribute to the pathogenesis and prognosis of the reciprocal dysfunction that occurs in cardiorenal syndrome (CRS). However, there is little evidence available regarding the potential alterations of the cellular components of the immune system and their clinical significance in patients with CRS. The Seattle Heart Failure Model (SHFM) is a well-established, multivariable risk model for predicting survival in heart failure (HF) patients, including lymphocytes but not indices of kidney function among its variables. The aim of our prospective study was to examine the incremental value of a selected panel of immune cell subsets on the mortality risk prediction of the SHFM in a cohort of type 2 CRS patients. Method 36 stable male patients with CRS type II were included in the final analysis of our prospective study. Exclusion criteria included history of malignancy, autoimmunity and active or chronic infections. The peripheral blood immune cell subsets CD14++CD16-, CD14++CD16+ and CD14+CD16++ absolute values and percentages out of total monocytes and NK cells (CD3+CD16+56+), CD3-CD19+ B lymphocytes, CD3+ CD4+ T cells, CD3+CD8+ T cells and T regulatory cells (Tregs) (CD4+CD25+FoxP3+) absolute values and percentages out of total lymphocytes were measured by flow cytometry. The Seattle Heart Failure Model (SHFM) score was derived from the online updated calculator https://depts.washington.edu/shfm. After baseline evaluation, patients were followed until the end of the established observation period, progression to end-stage kidney disease (ESKD) or until the study endpoint was reached, which was defined as a combined outcome of all-cause mortality and cardiovascular mortality. Logistic regression analysis was used to identify predictors of observed mortality and SHFM predicted mortality among various cell subtypes in CRS patients. Comparison of the prognostic accuracy of various models was performed using area under the curve (AUC) analysis. Results The mean age of our cohort was 73 ± 9 years with an eGFR 36.8 ± 12.9 ml/min/1.73 m2. Most patients had HF with reduced ejection fraction (52%) and described symptoms of HF indicative for NYHA class II and III (55% and 45%) respectively. During a mean follow-up of 29.8 ± 3.4 months, 21 patients (i.e. 58%) died while 5 patients (i.e. 14%) progressed to ESKD. The score for 1-year mortality derived from SHFM was significantly correlated with the observed mortality (r = 0.500, p = 0.002) but not with the occurrence of ESKD during follow-up. Total lymphocytes (r −0.516, p = 0.001), T-lymphocytes (r −0.543, p = 0.002), CD4+ T cells (r −0.518, p = 0.001), CD8+ T cells (r −0.409, p = 0.013) and T-regs (r −0.376, p = 0.024) counts were all significantly related to the mortality score derived from SHFM apart from relating to the observed mortality in our population (p < 0.05 for all relations with observed mortality). The proinflammatory, intermediate CD14++CD16+ monocytes counts were associated with the observed mortality (r 0.383, p = 0.021) but not with SHFM score derived mortality. After adjustment for the SHFM score derived mortality, only the CD4+ T cell count was significantly and independently associated with the observed mortality (OR 0.99, p = 0.045) whereas T-regs count showed a non-significant trend for an independent association with the observed mortality after adjustment (OR 0.95, p = 0.063). The addition of CD4+ T cells count, or Tregs count on SHFM improved AUC for mortality but not significantly [AUC SHFM 0.833, SHFM + CD4+ T cells 0.933 (p = 0.155 vs SHFM), SHFM + Tregs 0.933 (p = 0.145 vs SHFM)]. Conclusion In a small group of male patients with type 2 CRS, CD4+ T lymphocyte count was independently associated with mortality even after adjustment for the established mortality score derived from SHFM. However, the combination of both SHFM and CD4+ T cells count did not improve significantly the accuracy of the prediction models, probably attributed to our small sample size. Larger clinical studies are needed to validate the importance of specific lymphocyte subpopulations in the prognosis and management of patients with cardiorenal syndrome.