Background Preventing thrombosis is an important part of atrial fibrillation (AF) treatment. However, it may increase the risk of bleeding, and bleeding risk assessment tools' predictive value remains unclear. This network meta‐analysis investigated the sensitivity and specificity of HAS‐BLED, and other bleeding risk assessment tools, to predict major bleeding events in AF patients. Methods The PubMed, EMBASE, and Cochrane Central Register of Controlled Trials databases were searched using keywords, including “AF,” “bleeding,” and “HAS‐BLED,” for results published through 30 November 2018. The predictive sensitivity and specificity of each bleeding risk assessment tool was analyzed by network meta‐analysis. Results Our analysis included 18 studies, recruiting a total of 321 888 people. The bleeding risk assessment tools analyzed in this study included the ABC‐bleeding score, ATRIA, European score, GARFIELD‐AF, HAS‐BLED, HEMORR2HAGES, ORBIT, Shireman, and mOBRI. A comprehensive analysis of sensitivity and specificity, based on an inconsistency model, showed that European score, ABC, and mOBRI have relatively high‐sensitivity but low‐specificity tools, whereas HAS‐BLED and HEMORR2HAGES have balanced sensitivity and specificity. ORBIT, ATRIA, Shireman, and GARFIELD‐AF had relatively high specificity but low sensitivity. A consistency model analysis showed similar results. Conclusions HAS‐BLED is a balanced bleeding risk assessment tool in terms of sensitivity and specificity, whereas the European score, ABC, and mOBRI are high‐sensitivity tools and ORBIT, ATRIA, Shireman, and GARFIELD‐AF are high‐specificity tools.

No abstract

Background: New Oral Anticoagulants (NOACs) are effective and widely used to prevent and treat thromboembolic diseases, but the response to NOACs differs according to ABCB1 genotypes. Objective: We investigated the effects of ABCB1 genotypes on the pharmacokinetics and clinical outcomes of NOACs. Methods: We searched PubMed, Embase, and the Cochrane Library for studies on ABCB1 genotypes published from the inception of these databases until May 23, 2018. The Weighted Mean Difference (WMD) and Odds Ratio (OR) with 95% Confidence Interval (CI) were calculated for continuous and dichotomous data, respectively. Summary results were calculated using a random effects model. Results: Ten studies involving 2609 individuals were included in the systematic review, and three studies involving 535 individuals were included in the meta-analysis. Overall, four ABCB1 single-nucleotide polymorphisms were identified in the review. Carriers of the ABCB1 rs1045642 CC genotype had lower maximum plasma concentration (Cmax) than those of TT (WMD = −16.99 ng/mL; 95% CI = −33.39 to −0.59; P = 0.04), and carriers of the rs2032582 GG genotype showed lower Cmax than those of the A/T allele (WMD = −19.21 ng/mL; 95% CI = −36.62 to −1.80; P = 0.03). Carriers of the rs1045642 CC genotype showed lower area under the curve from time 0 to infinity (AUC0–∞) than those of the T allele (WMD = −78.58 ng·h/mL; 95% CI = −151.14 to −6.01; P = 0.03). ABCB1 rs4148738 genotypes did not affect the risks of ischemic stroke or systemic embolism (OR = 0.88), ischemic events (OR = 0.98), bleeding (OR = 0.94), major bleeding (OR = 1.14), or minor bleeding (OR = 0.94) in patients treated with dabigatran. Conclusion: Cmax was lower in carriers of ABCB1 rs1045642 CC than in those of TT and in carriers of rs2032582 GG than in those of the A/T allele, and AUC0–∞ was lower in carriers of rs1045642 CC than in those of TT. Conversely, ABCB1 rs4148738 genotypes did not affect primary clinical endpoints in dabigatran-administered patients. Future studies should analyze the relationships of ABCB1 genotypes with the pharmacokinetics and clinical outcomes of specific NOACs.

Background: The purpose of this study was to identify genetic variations associated with the metabolism of dabigatran in healthy Chinese subjects, with particular focus given to pharmacokinetics (PK) and pharmacodynamics (PD).Methods: Healthy Chinese adults aged 18–65 years with unknown genotypes from a bioequivalence trial were included according to the protocol registered at ClinicalTrial.org (NCT03161496). All subjects received a single dose (150 mg) of dabigatran etexilate. PK (main outcomes: area under the concentration-time, AUC0-t, of total and free dabigatran) and PD (main outcomes: anti-FIIa activity, APTT, and PT) parameters were evaluated. Whole-exome sequencing and genome-wide association analyses were performed. Additionally, candidate gene association analyses related to dabigatran were conducted.Results: A total of 118 healthy Chinese subjects were enrolled in this study. According to the p-value suggestive threshold (1.0 × 10−4), the following three SNPs were found to be associated with the AUC0–t of total dabigatran: SLC4A4 SNP rs138389345 (p = 5.99 × 10−5), FRAS1 SNP rs6835769 (p = 6.88 × 10−5), and SULT1A1 SNP rs9282862 (p = 7.44 × 10−5). Furthermore, these SNPs were also found to have significant influences on the AUC0–t of free dabigatran, maximum plasma concentration, and anti-FIIa activity (p < 0.05). Moreover, we identified 30 new potential SNPs of 13 reported candidate genes (ABCB1, ABCC2, ABCG2, CYP2B6, CYP1A2, CYP2C19, CYP3A5, CES1, SLCO1B1, SLC22A1, UGT1A1, UGT1A9, and UGT2B7) that were associated with drug metabolism.Conclusion: Genetic variations were indeed found to impact dabigatran metabolism in a population of healthy Chinese subjects. Further research is needed to explore the more detailed functions of these SNPs. Additionally, our results should be verified in studies that use larger sample sizes and investigate other ethnicities.

No abstract