Data Management And Sharing System of China National Clinical Research Center for Neurological Diseases

Journal：Brain and Behavior

Publication type: Original Research

IF(IF): 3.405

PMID: 36749599 Link To Pubmed Full text Download

Minor stroke and transient ischemic stroke is a special subtype of stroke. There has a high incidence of another stroke in patients with minor stroke and Transient Ischemic Attack(TIA) after the index event, commonly within 3 months ,but mostly within first 2 days.[1-4] Insulin resistance (IR),a common physiologic state with diminished insulin sensitivity of peripheral cells [5],has been proved to be related to the development of stroke[5] , cardiovascular disease[6] , obesity and hypertension[7] .Previous studies used hyperinsulinemic euglycemic clamp and homeostasis model assessment of insulin resistance (HOMA-IR) to assess IR. Complication and disability to detect early stage insulin resistance limited their use in routine clinical practice.[8] Triglyceride-glucose index (TyG), has been demonstrated recently to be a reliable surrogate marker for insulin resistance.[9] Studies have revealed the higher TyG level predicted adverse prognosis after acute coronary syndrome(ASC)[10-12] and ischmic stroke[13]. However, It is unclear whether TyG has an influence on prognosis of minor Stroke and TIA .This study explore the impact of TyG index on poor prognosis in patients with minor stroke and TIA and to improve secondary prevention strategies.

Exclusion criteria: age ＜30 or ＞80；BMI ＜16 or ＞40 ；mRS ≥4 points at admission ;cancer; TIA Predicted resting metabolic rate at baseline was calculated by Harris-Benedict equation, also was assessed using Mifflin St Jeor, WHO/FAO/UNU and Oxford equations. Pearson correlation coefficients between BMR defined by Harris-Benedict equation and other equations were derived. Continuous variables was expressed as mean ± standard deviation when normally distributed or medians with interquartile ranges. Categorical variables were presented as frequencies. In the univariate analysis, Kruskal–Wallis test was used for comparisons of skewed continuous variables. Categorical variables were compared with the χ2 statistics or Fisher exact test as appropriate. RMR was analyzed according to quartiles or continuous variable. The relationship between RMR with the 12-month all-cause mortality were investigated using multivariable Cox proportional hazards regression analysis (hazard ratio [HR] and 95% confidence intervals [95% CI]). And the association between the RMR and 12-month poor functional outcomes were explored by multivariable logistic regression analysis (odds ratio [OR] and 95% confidence intervals [95% CI]). The Kaplan-Meier event-free survival curves associated with RMR were compared using log-rank tests. Prespecified subgroup analysis to evaluate the effects of age, BMI, TOAST, hs-CRP, diabetes, minor stroke on RMR were performed with an interaction test.