Combined predictive value of uric acid and serum lipid for stroke events in non-valvular atrial fibrillation patients

TL;DR

This study shows that combining uric acid and lipid levels improves stroke risk prediction in patients with non-valvular atrial fibrillation.

Contribution

A new stroke risk prediction model (CHA2DS2-VASc+SUA+TG+LDL) is developed by integrating uric acid and lipid biomarkers.

Findings

High uric acid and triglyceride levels are linked to increased stroke risk in non-valvular AF patients.

The new model outperforms existing scores in predicting ischemic stroke events.

Gender-specific thresholds for uric acid and triglycerides improve risk stratification.

Abstract

Serum uric acid (SUA) and lipid metabolism disorders are closely associated with atrial fibrillation (AF) and its prognosis. In patients with non-valvular AF (NAF), we evaluated the combined predictive value of SUA, triglycerides (TG), and low-density lipoprotein (LDL) for stroke to enhance stroke risk prediction and management.

We included 3,176 NAF patients treated at the First Affiliated Hospital of Dalian Medical University from January 2020 to December 2023. We analyzed SUA concentration and lipid profile, along with relevant clinical data, to assess their impact on the occurrence of ischemic stroke (IS) in NAF patients. Due to gender differences in TG (1.39 mmol/L vs. 1.28 mmol/L for males, P = 0.031;1.57 mmol/L vs. 1.28 mmol/L for females, P = 0.001) and SUA levels (424 µmol/L vs. 397 µmol/L for males, P = 0.008; 361 µmol/L vs. 328 µmol/L for females, P = 0.004), we determined the thresholds for SUA (400 µmol/L in males and 330 µmol/L in females) and TG (1.28 mmol/L in males and 1.29 mmol/L in females) that predict stroke events in NAF patients by restricted cubic spline curves. Kaplan–Meier cumulative risk analysis indicates that a gender-based combined assessment of SUA and TG enhances stroke risk stratification in NAF patients. Compared to patients with low levels of SUA and TG, those with high levels of these biomarkers have a higher risk of IS (HR = 1.98). On multivariable Cox regression analysis with potential confounders, elevated SUA and low-density lipoprotein (LDL) levels were significantly associated with an increased risk of stroke. In summary, we developed the CHA2DS2-VASc+SUA+TG+LDL stroke risk prediction model. Its clinical predictive value was assessed using Harrell's C-statistic (C-index), integrated discrimination improvement (IDI) statistics, and net reclassification index (NRI) analysis.

SUA, TG and LDL were strongly associated with stroke for NAF. The combination of SUA, TG, and LDL effectively enhanced the predictive value of the CHA2DS2-VASc score for IS.

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