Background: Serum uric acid (UA) has been reported to be associated with ischemic stroke and inflammation. However, whether or not UA is related to the recurrence of ischemic stroke, and whether inflammation plays a role in the relationship between them remain inconclusive.Objective: We sought to explore the relationship between UA and the recurrence of ischemic stroke and to define the role of neutrophil-to-lymphocyte ratio (NLR) in the aforementioned relationship.Methods: A total of 8,995 patients were included in this study. Basic information and blood samples were collected, and whether or not each participant experienced ischemic stroke recurrence within 3 years was documented. Patients were stratified into three groups according to their UA level, as follows: ≤ 266, 267–339, and ≥ 340 μmol/L. COX regression and restricted cubic spline regression models were used to evaluate the clinical correlation between UA and ischemic stroke recurrence, mediation analysis and interaction and joint analysis were used to evaluate the role of NLR in the association of UA and ischemic stroke recurrence, and sensitivity and subgroup analyses were performed to test the robustness of the data.Results: Ischemic stroke recurrence was related to male sex, older age, higher UA level, higher NLR, hypertension, diabetes, and cardiovascular disease. Following adjustment for potential confounders, a high level of UA (≥ 340 μmol/L) increased the risk of recurrence by 92.6% in patients with previous ischemic stroke. We also found that NLR affects the association between UA and the recurrence of ischemic stroke in older adults, suggesting that patients with high NLR and high UA levels are at greater risk for ischemic stroke recurrence.Conclusion: UA level is non-linearly associated with recurrence, and NLR has an additive interaction between UA and ischemic stroke recurrence.

Background: Alzheimer’s disease (AD) is a progressive neurodegenerative disorder with cognitive dysfunction and behavioral impairment. We aimed to use principal components factor analysis to explore the association between gait domains and AD under single and dual-task gait assessments. Methods: A total of 41 AD participants and 41 healthy control (HC) participants were enrolled in our study. Gait parameters were measured using the JiBuEn^® gait analysis system. The principal component method was used to conduct an orthogonal maximum variance rotation factor analysis of quantitative gait parameters. Multiple logistic regression was used to adjust for potential confounding or risk factors. Results: Based on the factor analysis, three domains of gait performance were identified both in the free walk and counting backward assessments: “rhythm” domain, “pace” domain and “variability” domain. Compared with HC, we found that the pace factor was independently associated with AD in two gait assessments; the variability factor was independently associated with AD only in the counting backwards assessment; and a statistical difference still remained after adjusting for age, sex and education levels. Conclusions: Our findings indicate that gait domains may be used as an auxiliary diagnostic index for Alzheimer’s disease.