The pan-immune-inflammation value is associated with all-cause and cardiovascular mortality among individuals with diabetes

Abstract

Diabetes is a major global health burden, with chronic inflammation playing a central role in its progression and complications. The pan-immune-inflammation value (PIV) is a novel composite biomarker reflecting systemic immune inflammation. However, its prognostic value for mortality in individuals with diabetes remains unclear. We conducted a retrospective cohort analysis using the nationally representative National Health and Nutrition Examination Survey (NHANES) data, including participants aged ≥ 20 with available PIV data. PIV was calculated using a validated equation and then log-transformed (ln) before analysis. Multivariable Cox regression models were employed to evaluate this association. We further explored the dose-response relationship using restricted cubic splines (RCS) and threshold analysis to identify potential non-linear effects. The robustness of findings was confirmed through subgroup and sensitivity analyses, and the potential mediating role of estimated glomerular filtration rate (eGFR) was investigated. During a median follow-up of 94.9 months, 2,549 deaths were recorded, including 727 attributable to cardiovascular diseases. Elevated lnPIV levels were strongly associated with increased all-cause and cardiovascular mortality. Critical thresholds were identified at lnPIV values of 5.056 for all-cause mortality and 5.586 for cardiovascular mortality. These core associations were stable across all subgroup and sensitivity analyses. Furthermore, mediation analysis estimated that eGFR accounted for 5.1% and 6.4% of the lnPIV-associated risk for all-cause and cardiovascular mortality, respectively. Pan-immune-inflammation value was found to be independently associated with increased risks of all-cause and cardiovascular mortality in individuals with diabetes, characterized by a nonlinear association and a distinct threshold effect. These findings suggest that PIV could serve as a practical biomarker for risk stratification, potentially identifying patients who may benefit from more intensive management of both inflammation and renal function.