BackgroundAccording to recent research, there is a considerable correlation between the severity of coronary artery disease and the platelet-to-high-density lipoprotein cholesterol ratio (PHR), which suggests that PHR is a potentially valuable inflammatory biomarker. However, the body of current research offers insufficiently strong evidence to clarify the connection between PHR and the incidence of stroke. Therefore, this study aims to elucidate any potential associations between PHR and stroke risk.MethodsThis study employed data from the China Health and Retirement Longitudinal Study (CHARLS) covering the period from 2011 to 2018. It included 5,872 participants who did not have a history of stroke in 2011. These patients were separated into four groups according to their baseline PHR quartiles. The main goal of the study was to focus on stroke outcomes. Stroke was defined as an occurrence of a cerebrovascular accident confirmed by a physician. We employed Cox proportional hazards regression models to investigate the association between PHR and the likelihood of experiencing a stroke. Furthermore, we conducted restricted cubic spline regression analysis and subgroup analysis.ResultsThe average follow-up period was 77.5 months, during which 390 participants experienced a stroke. In comparison to the lowest quartile group, participants in the highest quartile of PHR had a 49% increased risk of stroke (HR 1.49, 95% CI 1.13–1.96, p = 0.004). The adjusted multivariable Cox regression analysis maintained the statistical significance of this association (aHR 1.42, 95% CI 1.06–1.90, p = 0.019). After adjustment, a positive linear relationship between stroke risk and PHR was identified through restricted cubic spline regression analysis (nonlinear p > 0.05). Additionally, the impact of stroke was consistent across a variety of subgroups, as evidenced by subgroup analysis.ConclusionOur study indicates that higher PHR levels are significantly associated with an increased risk of stroke and that these levels can be used to identify groups that are at high risk of stroke.
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