Abstract
The endothelial activation and stress index (EASIX) can predict endothelial intricacies as well as survival in distinct clinical circumstances. Accordingly, we hypothesize that EASIX may also serve as a predictor for stroke prevalence and mortality outcomes-all-cause mortality (ACM) and cardiovascular mortality (CVM) due to stroke. To validate our hypothesis, we deployed the National Health and Nutrition Examination Survey data. This cohort study employed 1999-2018 NHANES data. To evaluate EASIX effects on stroke risk, weighted logistic regression models were deployed. Meanwhile, we utilized the weighted Cox proportional hazards model for the calculation of hazard ratios (HRs) and 95% confidence intervals (CI) for mortality outcomes. The Kaplan-Meier curves were utilized, seeking the assessment of the interplay between the EASIX and both ACM and CVM among stroke patients. Using restricted cubic spline (RCS) curves, the potential non-linear or linear relations were investigated between the EASIX and both stroke prevalence and mortality outcomes. Subgroup analyses were performed to further assess the interconnection that existed between the EASIX and both stroke presence and its mortality outcomes. Interaction tests between covariates were also performed. Assessment of diagnostic value was done via receiver operating characteristic (ROC) curves. The area under the curve (AUC) was measured to estimate the EASIX predictive values for stroke prevalence and mortality outcomes. Of 43,853 participants, 1674 had a stroke; among them, there were (743/1671, 44.46%) ACM and 225 (13.46%) CVM. After full adjustment, EASIX was positively related to the likelihood of having a stroke (odds ratio [OR] = 1.16, 95% CI: 1.07-1.25). Unlike participants whose EASIX was in the lowest quartile (Q1), those in other quartiles (Q3/Q4) had an increased likelihood of having a stroke (OR = 1.34, 95% CI: 1.04-1.74; OR = 1.54, 95% CI 1.20-1.96, correspondingly). During a median follow-up of 71 months, Cox regression analysis manifested a positive interplay between EASIX and ACM (HR = 1.30, 95% CI: 1.17-1.44) and CVM (HR = 1.29, 95% CI: 1.06-1.58). The results showcased a non-linear interplay between EASIX and stroke presence and mortality outcomes. Additionally, subgroup analysis indicated no significant interactions between EASIX and any categorical covariates for CVM. Nervelessness, significant interaction effects existed between EASIX and the prevalence of stroke in categorical covariates such as hypertension, diabetes, and coronary heart disease (CHD; P < 0.001), as well as between EASIX and ACM in the categorical covariate of gender (P = 0.03). The ROC curves illustrated that the cutoff value of EASIX for stroke incidence and CVM was 0.56, and 0.58 for ACM, with an AUC of 0.663 (95% CI: 0.649-0.677) for stroke prevalence, as well as for ACM with an AUC of 0.620 (95% CI: 0.595-0.649) and for CVM with an AUC of 0.587 (95% CI: 0.549-0.626). The EASIX demonstrated a positive non-linear association with the prevalence and mortality outcomes amongst individuals at the age of 20 years and older who experienced a stroke, as identified in the NHANES dataset. Heightened EASIX scores were significantly related to an escalated risk of both stroke prevalence and mortality outcomes. Collectively, EASIX may be a valuable biomarker for assessing mortality risks in stroke patients and stroke prevalence. Looking forward, implementing EASIX in primary care settings could facilitate the early screening of endothelial function, thereby identifying high-risk patients and guiding appropriate referrals for specialized medical care. This approach can promote patient outcomes and reduce mortality rates among those who have suffered a stroke. Nevertheless, further validation in diverse countries and among various ethnic groups is necessary.