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Background and Aim: Stroke represents a significant public health challenge, necessitating the exploration of preventive measures. This network meta‐analysis aimed to assess the efficacy of different vitamin treatments compared to a placebo in preventing stroke. Methods: A systematic electronic search in databases including PubMed, EmBASE, Web of Science, clinicaltrials.gov, and Google Scholar until 31 May 2023 was conducted, to identify published studies investigating the association between vitamin intake and the risk of stroke. Pooled risk ratio (RR) with 95% confidence intervals (CIs) was calculated using a frequentist network meta‐analysis. Furthermore, we ranked vitamins based on p‐scores, facilitating a comparative assessment of their effectiveness in preventing stroke. Results: A total of 56 studies, including 17 randomized controlled trials (RCTs) and 39 cohort studies were analyzed. Direct estimates obtained from network meta‐analysis, we found that vitamin A (RR:.81 [.72–.91]), vitamin B‐complex (RR:.85 [.74–.97]), vitamin B6 (RR: 79 [.68–.92]), folate (RR:.86 [.75–.97]), vitamin C (RR:.77 [.70–.85]) and vitamin D (RR:.73 [.64–.83]) were significantly associated with a decreased stroke risk. However, no significant association was observed for vitamin B2, vitamin B12, and vitamin E. Subsequent to network meta‐analysis, vitamins were ranked in decreasing order of their efficacy in stroke prevention based on p‐score, with vitamin D (p‐score =.91), vitamin C (p‐score =.79), vitamin B6 (p‐score =.70), vitamin A (p‐score =.65), vitamin B‐complex (p‐score =.53), folate (p‐score =.49), vitamin B2 (p‐score =.39), vitamin E (p‐score =.28), vitamin B12 (.13) and placebo (.10). Conclusion: Our study has established noteworthy connections between vitamin A, vitamin B‐complex, vitamin B6, folate, vitamin C, and vitamin D in the realm of stroke prevention. These findings add substantial weight to the accumulating evidence supporting the potential advantages of vitamin interventions in mitigating the risk of stroke. However, to solidify and validate these observations, additional research is imperative. Well‐designed clinical trials or cohort studies are needed to further explore these associations and formulate clear guidelines for incorporating vitamin supplementation into effective stroke prevention strategies. [ABSTRACT FROM AUTHOR]

Early prognostication of patient outcomes in intracerebral hemorrhage (ICH) is critical for patient care. We aim to investigate protein biomarkers' role in prognosticating outcomes in ICH patients. We assessed 22 protein biomarkers using targeted proteomics in serum samples obtained from the ICH patient dataset (N = 150). We defined poor outcomes as modified Rankin scale score of 3–6. We incorporated clinical variables and protein biomarkers in regression models and random forest-based machine learning algorithms to predict poor outcomes and mortality. We report Odds Ratio (OR) or Hazard Ratio (HR) with 95% Confidence Interval (CI). We used five-fold cross-validation and bootstrapping for internal validation of prediction models. We included 149 patients for 90-day and 144 patients with ICH for 180-day outcome analyses. In multivariable logistic regression, UCH-L1 (adjusted OR 9.23; 95%CI 2.41–35.33), alpha-2-macroglobulin (aOR 5.57; 95%CI 1.26–24.59), and Serpin-A11 (aOR 9.33; 95%CI 1.09–79.94) were independent predictors of 90-day poor outcome; MMP-2 (aOR 6.32; 95%CI 1.82–21.90) was independent predictor of 180-day poor outcome. In multivariable Cox regression models, IGFBP-3 (aHR 2.08; 95%CI 1.24–3.48) predicted 90-day and MMP-9 (aOR 1.98; 95%CI 1.19–3.32) predicted 180-day mortality. Machine learning identified additional predictors, including haptoglobin for poor outcomes and UCH-L1, APO-C1, and MMP-2 for mortality prediction. Overall, random forest models outperformed regression models for predicting 180-day poor outcomes (AUC 0.89), and 90-day (AUC 0.81) and 180-day mortality (AUC 0.81). Serum biomarkers independently predicted short-term poor outcomes and mortality after ICH. Further research utilizing a multi-omics platform and temporal profiling is needed to explore additional biomarkers and refine predictive models for ICH prognosis. [ABSTRACT FROM AUTHOR]

Mild cognitive impairment (MCI) is an early phase of cognitive decline signalling the beginning of severe neurological diseases. Carotid intima‐media thickness (cIMT) has shown some correlation with MCI development. This study was conducted to investigate the impact of elevated cIMT on the risk of MCI in adults. A literature search was conducted in PubMed, EMBASE, Cochrane Library, Scopus, Google Scholar and CINAHL databases till 30 July 2021, with keywords: ('Carotid Intima‐Media Thickness' OR 'cIMT' OR 'IMT' AND 'Cognitive Impairment' OR 'Cognition' OR 'Cognitive Decline' AND 'Mild Cognitive Impairment' OR 'MCI'). Pooled standardized mean difference (SMD)/odds ratio (OR) and 95% confidence interval (CI) were determined for factor–disease association using either fixed (when I2 <50%) or random effect (when I2 >50%) models. Eight studies involving 1,585 MCI cases and 6,700 normal subjects were included in our meta‐analysis which showed no significant association of increased cIMT with the risk of MCI [SMD 1.17, 95% CI −0.09 to 2.42]. However, sensitivity analysis revealed an outlier study significantly affecting the effect size. On omitting the outlier study, the re‐evaluated meta‐analysis revealed a significant association of cIMT with the risk of MCI [SMD 0.52, 95% CI 0.26 to 0.78]. This significant association was also observed during subgroup analysis in Caucasian population [SMD 0.65, 95% CI 0.13 to 1.18] but not in Asian population [SMD 0.39, 95% CI −0.01 to 0.79]. Elevated cIMT poses a potential risk for MCI. However, more population‐based studies are required to corroborate these findings. [ABSTRACT FROM AUTHOR]

Objective: The prevalence of post-stroke anxiety (PSA) is reported to be 20%-25%. There is insufficient evidence on the efficacy of antidepressants for treating anxiety in such patients. This Prospective Randomized Open Blinded Endpoint (PROBE) study was designed to assess the safety and efficacy of fluoxetine in PSA., Methods: In this single-center pilot study conducted in India, post-stroke patients (between 1 to 6 months) were randomized to fluoxetine (intervention group: 20 mg/day for 12 weeks) or standard medical care (control group). The primary outcome was improvement in the Hamilton Anxiety Rating Scale (HAM-A) at 12 weeks. The secondary outcomes were anxiety remission (>50% improvement in HAM-A), modified Rankin Scale (mRS), Barthel Index (BI), quality of life (SF-36), and Hamilton Depression Rating Scale (HAM-D). A linear regression analysis was done for determinants of HAM-A to account for baseline differences in the intervention and control groups., Results: A total of 60 patients were randomized: (30: intervention, 30: control). The overall prevalence of post-stroke anxiety among participants in the study was 50.8%, and 31.5% experienced both anxiety and depression. The average HAM-A score at baseline was 11, and average follow-up score at study conclusion was 4. There was similar improvement in the HAM-A score at 12 weeks post-randomization in the intervention and control groups [fluoxetine: -8.0 (95% CI = -11.0 to -4.0); control: -7.0 (95% CI = -9.5 to -4.0); P = 0.91]. Likewise, there was no significant difference between intervention and control groups at 12 weeks post-randomization on the mRS, BI, SF-36, or HAM-D. There were no serious adverse events in either group during the study., Conclusion: Fluoxetine and standard medical care had comparable improvement in HAM-A in post-stroke patients with mild anxiety at 12 weeks. Further study of the pharmacological treatment of post-stroke patients with more severe anxiety is needed., Clinical Trial Registration: CTRI/2018/12/016568., Competing Interests: Declaration of conflicting interestsThe author(s) declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.