Visit-to-visit lipid variability and adverse kidney events in real-world type 2 diabetes patients.

Aim: To examine the association between long-term variability in low-density lipoprotein cholesterol (LDL-C) and the development of adverse kidney events among type 2 diabetes patients.

Methods: Kidney events of interest included sustained estimated glomerular filtration rate (eGFR) < 15 mL/min/1.73 m, 30 % eGFR decline, and composite kidney events. The Cox proportional hazard model was used to assess the association between LDL-C variability and kidney events.

Results: A total of 15,444 patents were included (54 % male, mean age of 62.3 years, baseline HbA1c of 7.6 %, and eGFR of 84.2 mL/min/1.73 m). The risk of kidney events increased with greater LDL-C variability across variability indices, except for that measured by coefficient of variation. Specifically, average real variability had the best predictive performance, with an optimal cut-off value of 19.26 for discriminating patients' risk of a sustained eGFR < 15 mL/min/1.73 m. A greater effect of lipid variability on kidney event risk was observed among a subset of patients aged < 75 years, with eGFR ≥ 90 mL/min/1.73 m, or having fewer diabetes-related complications.

Conclusions: An increased risk of adverse kidney events with greater visit-to-visit variability in LDL-C highlights the clinical importance of monitoring both the single-point LDL-C and its stability over time.