Background: Atrial fibrillation (AF) is a common cardiac arrhythmia that increases the risk of stroke. Medical therapy for decreasing stroke risk involves anticoagulation, which may increase bleeding risk for certain patients. In determining optimal therapy for stroke prevention for patients with AF, clinicians use tools with various clinical, imaging, and patient characteristics to weigh stroke risk against therapy-associated bleeding risk. Aim: Review published literature and summarize available risk stratification tools for stroke and bleeding prediction in patients with AF. Methods: We searched for English-language studies in PubMed®, Embase®, and the Cochrane Database of Systematic Reviews published between January 1, 2000, and February 14, 2018. Two reviewers screened citations for studies that examined tools for predicting thromboembolic and bleeding risks in patients with AF. Data regarding study design, patient characteristics, interventions, outcomes, quality and applicability were extracted. Results: 61 studies were relevant to predicting thromboembolic risk and 38 to predicting bleeding risk. Data suggest that CHADS2, CHA2DS2-VASc, and ABC risk scores have the best evidence predicting thromboembolic risk (moderate strength of evidence for limited prediction ability of each score) and that HAS-BLED has the best evidence for predicting bleeding risk (moderate strength of evidence). Limitations: Studies were heterogeneous in methodology and populations of interest, setting, interventions, and outcomes analyzed. Conclusion: CHADS2, CHA2DS2-VASc, and ABC stroke have the best prediction for stroke events, and HAS-BLED provides the best prediction for bleeding risk. Future studies should define the role of imaging tools and biomarkers in enhancing the accuracy of risk prediction tools. Primary Funding Source: Patient-Centered Outcomes Research Institute (PROSPERO #CRD42017069999)

Background The UNAIDS “90-90-90” global treatment target aims to achieve 73% virologic suppression among HIV-infected persons worldwide by 2020. Objective Using a microsimulation model of HIV detection, disease and treatment, we estimate the clinical and economic value of reaching this ambitious goal in South Africa. Design We model: the Current Pace strategy, simulating existing scale-up efforts and gradual increases in overall virologic suppression from 24% to 36% in 5 years; and the UNAIDS Target strategy, simulating 73% suppression in 5 years. Data Sources Published estimates and South African survey data inform HIV transmission rates (0.16–9.03/100PY), HIV-specific age-stratified fertility rates (1.0–9.1/100PY), and costs (ART: $11–31/month, routine care: $20–157/month). Target population South African HIV-infected population, including incident infections over the next ten years Perspective Modified societal perspective, excluding time and productivity costs Time Horizon Five and ten years Interventions Aggressive HIV case-detection, efficient linkage to care, rapid treatment scale-up and adherence/retention interventions toward the UNAIDS Target strategy Outcome Measures HIV transmissions, deaths, years of life saved (YLS), maternal orphans, costs (2014USD), and cost-effectiveness Base Case Analysis Compared to Current Pace over (5- and) 10-years, the UNAIDS Target strategy would avert (873,000) 2,051,000 HIV transmissions, (1,174,000) 2,478,000 deaths, and (726,000) 1,689,000 maternal orphans, while saving (3,002,000) 13,340,000 life-years. The additional budget required for the UNAIDS Target strategy would be ($7.965) $15.979 billion, yielding an incremental cost-effectiveness ratio (ICER) of ($2,720/YLS) $1,260/YLS, (<50%) <20% of South Africa per capita GDP. Results of Sensitivity Analysis Outcomes generally varied <20% from base case outcomes when we varied key input parameters within plausible ranges. Limitations Several pathways may lead to 73% overall suppression which were examined in sensitivity analysis. Conclusions Reaching the “90-90-90” HIV suppression target would be costly but both extraordinarily effective and cost-effective in South Africa. Global health policy makers should mobilize the political and economic support to make the 90-90-90 aspiration a reality.