Interrelationship Between Dyslipidemia and Hyperuricemia in Patients with Uncontrolled Type 2 Diabetes: Clinical Implications and a Risk Identification Algorithm

Background and Objectives: Dyslipidemia and hyperuricemia frequently co-exist in uncontrolled type 2 diabetes mellitus (T2DM), amplifying renal and cardiovascular risk. This study aimed to develop and evaluate an optimized Renal–Metabolic Risk Score (RMRS) integrating renal and lipid parameters to identify patients with both conditions. Materials and Methods: We conducted a retrospective observational study including 304 patients with uncontrolled T2DM hospitalized at the Emergency County Hospital Oradea, Romania (2022–2023). Hyperuricemia was defined as uric acid > 6 mg/dL in females and >7 mg/dL in males; dyslipidemia was diagnosed according to standard lipid thresholds. RMRS was calculated from standardized values of urea, TG/HDL ratio, and eGFR, with variable weights derived from logistic regression coefficients. The score was normalized to a 0–100 scale. Receiver operating characteristic (ROC) analysis assessed discriminative performance; quartile analysis explored stratification ability. Results: The prevalence of dyslipidemia and hyperuricemia co-occurrence was 81.6%. RMRS was significantly higher in the co-occurrence group compared to others (median 16.9 vs. 10.0; p < 0.001). ROC analysis showed an AUC of 0.78, indicating good discrimination. Quartile analysis demonstrated a monotonic gradient in co-occurrence prevalence from 64.5% in Q1 to 96.1% in Q4. Conclusions: The Renal–metabolic Risk Score (RMRS) demonstrated moderate discriminative performance in identifying patients with uncontrolled T2DM at risk for combined hyperuricemia and dyslipidemia. Because it relies on inexpensive, routine laboratory parameters, RMRS may be particularly useful in resource-limited settings to support early risk stratification, dietary counseling, and timely referral. Further validation in larger and more diverse cohorts is required before its clinical adoption.