Background and PurposeAdditional folic acid (FA) treatment appears to have a neutral effect on reducing vascular risk in countries that mandate FA fortification of food (e.g., USA and Canada). However, it is uncertain whether FA therapy reduces stroke risk in countries without FA food fortification. The purpose of this study was to comprehensively evaluate the efficacy of FA therapy on stroke prevention in countries without FA food fortification. MethodsPubMed, EMBASE, and clinicaltrials.gov from January 1966 to August 2016 were searched to identify relevant studies. Relative risk (RR) with 95% confidence interval (CI) was used as a measure of the association between FA supplementation and risk of stroke, after pooling data across trials in a random-effects model. ResultsThe search identified 13 randomized controlled trials (RCTs) involving treatment with FA that had enrolled 65,812 participants, all of which stroke was reported as an outcome measure. After all 13 RCTs were pooled, FA therapy versus control was associated with a lower risk of any future stroke (RR, 0.85; 95% CI, 0.77 to 0.95). FA alone or combination of FA and minimal cyanocobalamin (≤0.05 mg/day) was associated with a lower risk of future stroke (RR, 0.75; 95% CI, 0.66 to 0.86) whereas combination of FA and cyanocobalamin (≥0.4 mg/day) was not associated with a lower risk of future stroke (RR, 0.95; 95% CI, 0.86 to 1.05). ConclusionsFA supplement reduced stroke in countries without mandatory FA food fortification. The benefit was found mostly in patients receiving FA alone or combination of FA and minimal cyanocobalamin.

The genes encoding the enzymes for metabolising alcohol dehydrogenase 1B (ADH1B) and aldehyde dehydrogenase 2 (ALDH2) -- exhibit genetic polymorphism and ethnic variations. Although the ALDH2*2 variant allele has been widely accepted as protecting against the development of alcoholism in Asians, the association of the ADH1B*2 variant allele with drinking behaviour remains inconclusive. The goal of this study was to determine whether the polymorphic ADH1B and ALDH2 genes are associated with stroke in male Han Chinese with high alcohol consumption. Sixty-five stroke patients with a history of heavy drinking (HDS) and 83 stroke patients without such a history (NHDS) were recruited for analysis of the ADH1B and ALDH2 genotypes from the stroke registry in the Tri-Service General Hospital, Taipei, Taiwan, between January 2000 and December 2001. The allelotypes of ADH1B and ALDH2 were determined using the polymerase chain reaction-restriction fragment length polymorphism method. The HDS patients (3 per cent) showed a significantly lower ALDH2*2 allele frequency than NHDS patients (27 per cent) (p < 0.001). After controlling for age, patients with HDS were associated with a significantly higher occurrence of cigarette smoking (p < 0.01) and liver dysfunction (p < 0.01). Multiple logistic regression analyses revealed that the ALDH2*2 variant allele was an independent variable exhibiting strong protection (odds ratio 0.072; 95 per cent confidence interval 0.02-0.26) against HDS after adjustment for hypertension, diabetes mellitus, smoking status and liver dysfunction. By contrast, allelic variations in ADH1B exerted no significant effect on HDS. The present study indicated that, unlike ALDH2*2, ADH1B*2 appears not to be a significant negative risk factor for high alcohol consumption in male Han Chinese with stroke.

Background: Epidemiological evidence suggests that heavy alcohol consumption increases the risk for either stroke or liver disease. The goal of this study was to determine whether heavy drinkers with mild liver disorder (MLD) are at risk of hemorrhagic stroke. Methods:All of the 524 patients recruited were males with a first-ever acute stroke and were consecutively admitted to the Tri-Service General Hospital between January 2000 and December 2001. The risk factors, liver function, stroke subtypes, and hemostatic factors were assessed among 68 patients defined as heavy drinker stroke (HDS) and 456 patients as nonheavy drinker stroke (NHDS). Results: HDS patients had a significantly higher incidence of hemorrhagic stroke than NHDS patients. HDS patients were also associated with significantly higher occurrence of cigarette smoking, hyperuricemia, liver dysfunction, and significantly lower platelet counts. HDS patients with MLD were more likely to have hemorrhagic stroke (76.5%) than HDS patients without MLD (33.3%) and NHDS patients with (40.3%) or without (26.7%) MLD. HDS patients with MLD also exhibited a significantly higher glutamic oxaloacetic transaminase/glutamic pyruvic transaminase ratio (2.0 ± 1.2) and lower platelet number (185,000 ± 85,000 per µl) when compared with HDS patients without MLD (1.4 ± 0.5; 206,000 ± 59,000 per µl) and NHDS patients with (1.1 ± 1.0; 256,000 ± 97,000 per µl) or without (1.4 ± 0.7; 216,000 ± 68,000 per µl) MLD. Conclusions: HDS patients with MLD are at higher risk for hemorrhagic stroke in part due to the changes in hemostatic factors, although other factors may also contribute to hemorrhagic stroke.

This study proposes the inverse problem algorithm (IPA) with five risk factors applied to the semi-quantitative analysis of carotid stenosis 272 patients with suspected ischemic stroke. The IPA is known to provide a substantiated machine learning-based prediction of the expected outcomes by solving an inverse matrix of variable coefficients. In case of carotid stenosis prediction, such risk factors as patient’s age, mean arterial pressure (MAP), glucose AC, low-density lipoprotein-cholesterol (LDL-C), and C-Reactive protein (CRP) were assessed for the main group of 217 patients. Their results were processed by the STATISTICA program with a customized loss function ([Formula: see text]), yielding the first-order nonlinear semi-empirical formula with 16 terms. The loss function was calculated via the total mismatch between the theoretical predictions and true carotid stenosis cases (%) for all 217 patients. Thus, the carotid stenosis (%) compromised solution array [[Formula: see text]] was optimized using [Formula: see text] individual data points via the proposed algorithm. The results showed a complete regression with loss function [Formula: see text]=2.3543, variance [Formula: see text]=87.46%, and correlation coefficient [Formula: see text]. The reference group of 55 more patients with the same preliminary diagnosis and symptoms was selected to validate the method predictive feasibility, which was found quite satisfactory. The decreasing order of three dominant risk factors was as follows: CRP, glucose AC, and MAP, whereas age and LDL-C weakly influenced the program computation results. The IPA showed a strong convergence by its default characteristic. The reduction of the number of variables in computation deteriorated the prediction accuracy, exhibiting the algorithm’s high sensitivity to the number of variables.