Effect of uric acid in animal models of ischemic stroke: A systematic review and meta-analysis

Abstract

Addition of uric acid (UA) to thrombolytic therapy, although safe, showed limited efficacy in improving patients' stroke outcome, despite alleged neuroprotective effects of UA in preclinical research. This systematic review assessed the effects of UA on brain structural and functional outcomes in animal models of ischemic stroke. We searched Medline, Embase and Web of Science to identify 16 and 14 eligible rodent studies for qualitative and quantitative synthesis, respectively. Range of evidence met 10 of a possible 13 STAIR criteria. Median (Q1, Q3) quality score was 7.5 (6, 10) on the CAMARADES 15-item checklist. For each outcome, we used standardised mean difference (SMD) as effect size and random-effects modelling. Meta-analysis showed that UA significantly reduced infarct size (SMD: -1.18; 95% CI [-1.47, -0.88]; p < 0.001), blood-brain barrier (BBB) impairment/oedema (SMD: -0.72; 95% CI [-0.97, -0.48]; p < 0.001) and neurofunctional deficit (SMD: -0.98; 95% CI [-1.32, -0.63]; p < 0.001). Overall, there was low to moderate between-study heterogeneity and sizeable publication bias. In conclusion, published rodent data suggest that UA improves outcome following ischemic stroke by reducing infarct size, improving BBB integrity and ameliorating neurofunctional condition. Specific recommendations are given for further high-quality preclinical research required to better inform clinical research.

Keywords: animal model; brain damage; ischemic stroke; neurofunctional deficit; uric acid.

Figure 1.

Flow diagram to depict the processes for literature search in three databases and subsequent study selection for qualitative and quantitative synthesis. K: number of comparisons; n: number of animals.

Figure 2.

Effect of UA on infarct size: (a) forest plot and between-study heterogeneity and (b) funnel plot showing published studies (filled circles), trim-and-fill assigned studies (open circles), and the pooled estimate of efficacy before adjusting for publication bias (dashed vertical line).

Figure 3.

Subgroup stratified meta-analysis of the effect of UA on infarct size, in the domain of study characteristics: effects of (a) species, (b) ischaemia duration, (c) use of neuroprotective anaesthetic and (d) UA treatment timing, on UA effect size. Data are effect size and 95% confidence interval (CI). The horizontal gray bar represents the 95% CI of the pooled estimate of efficacy. TE: thromboembolism; Pre: pre-ischaemic; Post: post-ischaemic.

Figure 4.

Subgroup stratified meta-analysis of the effect of UA on infarct size, in the domain of study quality: effects of (a) randomisation to treatment group, (b) blinding outcome assessment, (c) prespecified inclusion/exclusion criteria and (d) brain perfusion monitoring, on UA effect size. Data are effect size and 95% confidence interval (CI). The horizontal gray bar represents the 95% CI of the pooled estimate of efficacy.

Figure 5.

Effect of UA on BBB impairment/oedema: (a) forest plot and between-study heterogeneity and (b) funnel plot showing published studies (filled circles), trim-and-fill assigned studies (open circles), and the pooled estimate of efficacy before adjusting for publication bias (dashed vertical line).

Figure 6.

Effect of UA on neurofunctional deficit: (a) forest plot and between-study heterogeneity; (b) funnel plot showing published studies (filled circles), trim-and-fill assigned studies (open circles), and the pooled estimate of efficacy before adjusting for publication bias (dashed vertical line) and (c) forest plot from sensitivity analysis using studies reporting medians for neurofunctional score.

Figure 7.

Association between the effect sizes of UA for infarct and neurofunctional deficit reduction, using weighted Spearman’s correlation.