Because metabolic syndrome is a significant risk factor for cardio-cerebrovascular diseases and the relationship between metabolic syndrome (including its components) and the prognosis of stroke is controversial, this study was conducted to evaluate whether metabolic syndrome is associated with a high recurrence and mortality of stroke.
This study was registered in the PROSPERO database (CRD42020177118). We searched for relevant observational cohort studies published from inception to April 23, 2020, using PubMed, Embase, and the Cochrane Library. Effect estimates with 95% confidence intervals (CIs) were pooled using the random-effects model. The primary and secondary outcomes were stroke recurrence and all-cause mortality, respectively. Leave-one-out sensitivity analyses and nonparametric trim-and-fill method were used to identify the stability of the results.
Thirteen cohort studies comprising 59,919 participants >60 years of age were included for analysis. Overall, metabolic syndrome was significantly associated with stroke recurrence (relative risk [RR] 1.46, 95% CI 1.07–1.97, p = 0.02). Among the metabolic syndrome components, low levels of high-density lipoprotein cholesterol (HDL-C) (RR 1.32, 95% CI 1.11–1.57, p = 0.002) and ≥2 metabolic syndrome components (RR 1.68, 95% CI 1.44–1.94, p < 0.001) significantly predicted stroke recurrence, whereas elevated triglycerides, elevated waist circumference, hyperglycemia, and hypertension failed to account for risk factors for stroke recurrence. Moreover, metabolic syndrome, not its components, was significantly associated with all-cause mortality (RR 1.27, 95% CI 1.18–1.36, p < 0.001). The stability of these results was further confirmed by the leave-one-out sensitivity analyses and nonparametric trim-and-fill method.
The present study indicates that metabolic syndrome and some of its components (low HDL-C and number of metabolic syndrome components) seem to be risk factors for stroke recurrence. Although metabolic syndrome is also associated with all-cause mortality, the role of its components in predicting all-cause mortality deserves further study.