6 research outputs found

    Effects of intravenous iron replacement therapy on cardiovascular outcomes in patients with heart failure: A systematic review and meta-analysis

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    (1) Background: Iron deficiency (ID) is an important adverse prognostic marker in patients with heart failure (HF); however, it is unclear whether intravenous iron replacement reduces cardiovascular mortality in this patient group. Here, we estimate the effect of intravenous iron replacement therapy on hard clinical outcomes following the publication of IRONMAN, the largest trial in this field. (2) Methods: In this systematic review and meta-analysis, prospectively registered with PROSPERO and reported according to PRISMA guidelines, we searched PubMed and Embase for randomized controlled trials investigating intravenous iron replacement in patients with HF and co-existing ID. The primary outcome was cardiovascular mortality and secondary outcomes were all-cause mortality, hospitalizations for HF and a combination of the primary outcome and hospitalizations for HF. (3) Results: A total of 1671 items were identified and after removal of duplicates we screened titles and abstracts of 1202 records. Some 31 studies were identified for full-text review and 12 studies were included in the final review. The odds ratio (OR) for cardiovascular death using a random effects model was 0.85 (95% CI 0.69 to 1.04) and for all-cause mortality it was 0.83 (95% CI 0.59 to 1.15). There was a significant reduction in hospitalizations for HF (OR 0.49, 95% CI 0.35 to 0.69) and the combination of hospitalizations for HF and cardiovascular death (OR 0.65, 95% CI 0.5 to 0.85). (4) Conclusions: This review supports the use of IV iron replacement reducing hospitalization rates for HF, however more research is required to determine the effect on cardiovascular mortality and to identify the patient population most likely to benefit

    BULK SEPARATION AND PURIFICATION OF CH4/CO2 MIXTURES ON 4A/13X MOLECULAR-SIEVES BY USING PRESSURE SWING ADSORPTION

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    Results of bulk gas separation and purification of a CH4/CO2 mixture by pressure swing adsorption (PSA) are reported. Bulk gas separation and purification of CH4/CO2 mixture have direct application in landfill gases and tertiary oil recovery and effluent separations. ZMS-13X/4A with calculated kinetic selectivities equal to 0.604 and 0.601, respectively, were used as sorbents. The step times corresponding to various flow rates and compositions were chosen to allow sorption of CO2 but preclude penetration of CH4 into the micropores. By using a simulated biogas mixture (66% CH4 and 34% CO2) as a feed, the results for bulk gas separation for a PSA cycle between 1.2-36.0 P(H)/P(L) ratios over ZMS-13X adsorbent was 95% or more CH4 in the raffinate, whereas with a 10/90 CH4/CO2 feed, purification over ZMS-4A at P(H)/P(L) ratios of 10-304 gave 85-90% CH4 at 900 and 1800 mL/min flow rates

    A constellation of science-based data driven products to improve financing of Sustainable Agri-Food Systems

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    Investing in agri-food systems in developing countries is often considered risky, specifically for private investors, and impacts are difficult to quantify leading to an insufficient allocation of capital to the sector. This is caused due to Information asymmetries and poor primary data between financial institutions and potential borrowers in rural financial markets. This results in inadequate risk, return, impact assessment models and high transaction costs for capital deployment.To overcome these challenges, we have developed the "OneSF Analyzer", a "constellation" of data-products designed to "de-risk" investments, through multidimensional assessments and monitoring of agri-food systems (productivity, environment, gender etc.), along with financial health assessments of the investee. in this report, we present the science, data, analytics, and the design components of agro-climatic hazards and their impacts on crop productivity (Phase 1) of "OneSF Analyzer". We also present phase wise planned improvements to the OneSF Analyzer both with regards to scalability/computation, as well as expanding insights to support pre-investment decisions by financial institutions
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