Composite Blood-Count Inflammatory Indices in Diabetic Kidney Disease and Advanced, Largely Dialysis-Dependent Non-Diabetic Chronic Kidney Disease: A Single-Centre, Four-Group Cross-Sectional Study

Background/Objective: The neutrophil-to-lymphocyte ratio (NLR), monocyte-to-lymphocyte ratio (MLR), and systemic inflammation response index (SIRI) have been proposed as markers of diabetic kidney disease (DKD); however, comparisons are almost always confined to individuals with diabetes mellitus (DM). We examined whether an elevated index is specific to DKD or accompanies chronic kidney disease (CKD) and dialysis of any cause and whether any index adds information to routinely available variables. Methods: In this retrospective cross-sectional study, 232 participants were analysed in four groups: 60 controls without DM or kidney disease, 63 with DM alone, 66 with DKD (12 receiving dialysis), and 43 with non-diabetic CKD, a predominantly advanced and dialysis-dependent comparator (32 receiving dialysis; median estimated glomerular filtration rate [eGFR] 7.4 mL/min/1.73 m2). Among the 129 participants with DM, each index was added separately to two comparator models defined before the indices were analysed: Model 1, routinely available correlates of DKD; Model 2, variables not determined by renal function (age, sex, glycated haemoglobin [HbA1c], and fasting glucose); And Model 3, fitted for the 109 participants with CKD of either cause, took its cause as the outcome, and was adjusted for age, sex, eGFR, and dialysis status. Contributions were assessed using likelihood ratio block tests with Bonferroni correction for the three indices tested within each model. Results: All three indices differed across the groups (p < 0.001) and were highest in the non-diabetic CKD group. Within the nephropathy groups, all three indices were higher in participants receiving dialysis, whereas DKD and non-diabetic CKD did not differ significantly within the small strata of comparable severity. No index improved Model 1 (area under the curve [AUC] 0.803; p ≥ 0.076) or Model 3 (AUC 0.874; p ≥ 0.569). All three improved Model 2 (AUC 0.683; MLR Δχ2 = 6.61, p = 0.010), but only MLR remained significant after Bonferroni correction, the optimism-corrected gain in AUC was at most 0.033, and no index remained significant after the 12 participants receiving dialysis were excluded (p ≥ 0.091). Each index was inversely correlated with eGFR among participants with DM (Spearman’s ρ = −0.31 to −0.37). Conclusions: In this single-centre cohort, the indices focused on renal impairment and dialysis, not on diabetes-specific processes. These indices provided no additional insight beyond routine renal impairment markers already included in the model; thus, they were redundant rather than informative. The study design cannot differentiate between DM and non-DM kidney disease in individuals with DM, and these results need validation through prospective, stage-matched studies.