Background
Uric acid (UA) is associated with renal and patient survivals but the causal association in nature remains unclear. Also, no finding is yet available regarding longitudinal UA control (trajectory).
Methods
We enrolled 808 subjects diagnosed with stage 3 chronic kidney disease from 2007 to 2017. We plotted the mean UA over a period of 6 months with a minimum of three samples of UA was required. From the sampled points, we generated for each patient an interpolated line by joining mean values of the UA levels over time. And from the lines from all patients, we classified them into three groups of trajectories (low, medium and high) through group-based trajectory modeling, and then we further separated into either a treatment or no-treatment subgroups. Due to multiple comparisons, we performed post hoc analysis by Bonferroni adjustment. Using the univariate competing-risks regression, we calculated the competing risk analysis with subdistribution hazard ratio of possible confounders.
Results
All of the 6 trajectories appeared as gradually falling functions with time without any of the curves crossed over one another. For all-cause mortality risk, none of the variables (including age, gender, coronary arterial disease, cerebrovascular disease, diabetes mellitus, renin-angiotensin-aldosterone system inhibitors, trajectories of UA, and treatment of UA) was statistically significant. All 6 trajectories appeared as steady curve without crossovers among them over the entire period of follow-up. Patients with DM were statistically more likely to undergo dialysis. There was only a trend that the on-treatment trajectories, compared to their no-treatment trajectories, had lower risks for dialysis. There was no effect of UA control on patients’ survival.
Conclusions
Initial treatment of UA is utterly important for UA control. However, the long-term effects on patients and renal survivals maybe minor without statistical significance.
Keyword: uric acid, patient survival, renal survival, long-term effect, trajectory, competing risk analysis