Seasonal variation has been implicated in the occurrence of ischemic stroke; however, evidence regarding seasonal differences in inflammatory biomarkers remains inconsistent. This study aimed to investigate seasonal patterns of inflammatory markers and blood pressure (BP) in patients with acute ischemic stroke and to evaluate whether these differences are independent of clinical confounders. This single-center retrospective study included 168 patients with acute ischemic stroke admitted during summer and winter. Clinical characteristics and laboratory indicators—including sCD40L, lipoprotein-associated phospholipase A2 (Lp-PLA2), high-sensitivity C-reactive protein (hs-CRP), blood pressure, and blood glucose—were collected. Stroke severity and etiology were assessed using the NIHSS score and TOAST classification. Between-group comparisons were performed using independent samples t-tests or Mann–Whitney U tests, as appropriate. Analysis of covariance (ANCOVA) was conducted to adjust for potential confounders, including age, sex, hypertension, diabetes mellitus, and NIHSS score, and to assess interaction effects. In unadjusted analyses, patients admitted in winter had significantly higher levels of systolic blood pressure (SBP), sCD40L, Lp-PLA2, and hs-CRP compared with those admitted in summer (all P 0.05), suggesting potential confounding by baseline clinical characteristics. Notably, a significant interaction between season and hypertension was observed for SBP (P < 0.05), suggesting that seasonal effects on blood pressure may differ according to hypertension status. Although unadjusted analyses suggested higher inflammatory marker levels and SBP in winter, these differences were not independent after controlling for confounding factors. These findings suggest that the observed seasonal differences may be largely explained by patient-level characteristics rather than being solely attributable to seasonal classification. However, the observed interaction between season and hypertension highlights potential heterogeneity in blood pressure responses, which may have implications for individualized risk management.
Zhang et al. (Mon,) studied this question.