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Purpose: Renal impairment (RI) has been regarded as a risk factor for unfavorable neurologic outcomes after mechanical thrombectomy (MT) in acute ischemic stroke. However, most of the previous studies were conducted on patients with anterior circulation stroke. Accordingly, the influence of RI on MT outcomes has not been well elucidated in detail in acute vertebrobasilar stroke. Methods: Consecutive stroke patients with MT due to acute vertebrobasilar artery occlusion between March 2015 and December 2020 at four institutions were included. Multivariable logistic regression analysis was conducted to assess the associations between RI and outcomes and mortality at 3 months, and the development of intracerebral hemorrhage (ICH) after the procedure. Additionally, the multivariable Cox proportional hazards model was performed to determine the influence of RI on survival probability after patient discharge. Results: A total of 110 patients were included in the final analysis. The presence of RI (OR = 0.268, 95% CI: 0.077–0.935), National Institute of Health Stroke Scale scores (OR = 0.849, 95% CI: 0.791–0.910), and puncture-to-recanalization time (OR = 0.981, 95% CI: 0.966–0.997) were related to outcomes. There was no significant association between RI and 3-month mortality or ICH. The cumulative survival probability after adjusting for relevant risk factors demonstrated that RI remained significantly associated with poorer survival after MT compared to patients without RI (HR = 2.111, 95% CI: 0.919–4.847). Conclusion: RI was an independent risk factor for poor 3-month neurologic outcomes and survival probability after MT in patients with acute vertebrobasilar stroke. [ABSTRACT FROM AUTHOR]

Polygenic risk scores (PRSs) have an important relevance to approaches for clinical usage in intracranial aneurysm (IA) patients. Hence, we aimed to develop IA-predicting PRS models including the genetic basis shared with acute ischemic stroke (AIS) in Korean populations. We applied a weighted PRS (wPRS) model based on a previous genome-wide association study (GWAS) of 250 IA patients in a hospital-based multicenter cohort, 222 AIS patients in a validation study, and 296 shared controls. Risk predictability was analyzed by the area under the receiver operating characteristic curve (AUROC). The best-fitting risk models based on wPRSs were stratified into tertiles representing the lowest, middle, and highest risk groups. The weighted PRS, which included 29 GWASs (p < 5×10−8) and two reported genetic variants (p < 0.01), showed a high predictability in IA patients (AUROC = 0.949, 95% CI: 0.933–0.966). This wPRS was significantly validated in AIS patients (AUROC = 0.842, 95% CI: 0.808–0.876; p < 0.001). Two-stage risk models stratified into tertiles showed an increased risk for IA (OR = 691.25, 95% CI: 241.77–1976.35; p = 3.1×10−34; sensitivity/specificity = 0.728/0.963), which was replicated in AIS development (OR = 39.76, 95% CI: 16.91–93.49; p = 3.1×10−17; sensitivity/specificity = 0.284/0.963). A higher wPRS for IA may be associated with an increased risk of AIS in the Korean population. These findings suggest that IA and AIS may have a shared genetic architecture and should be studied further to generate a precision medicine model for use in personalized diagnosis and treatment. [ABSTRACT FROM AUTHOR]