64 research outputs found

    Contemporary guideline-directed medical therapy in de novo, chronic, and worsening heart failure patients:First data from the TITRATE-HF study

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    Aims: Despite clear guideline recommendations for initiating four drug classes in all patients with heart failure (HF) with reduced ejection fraction (HFrEF) and the availability of rapid titration schemes, information on real-world implementation lags behind. Closely following the 2021 ESC HF guidelines and 2023 focused update, the TITRATE-HF study started to prospectively investigate the use, sequencing, and titration of guideline-directed medical therapy (GDMT) in HF patients, including the identification of implementation barriers. Methods and results: TITRATE-HF is an ongoing long-term HF registry conducted in the Netherlands. Overall, 4288 patients from 48 hospitals were included. Among these patients, 1732 presented with de novo, 2240 with chronic, and 316 with worsening HF. The median age was 71 years (interquartile range [IQR] 63–78), 29% were female, and median ejection fraction was 35% (IQR 25–40). In total, 44% of chronic and worsening HFrEF patients were prescribed quadruple therapy. However, only 1% of HFrEF patients achieved target dose for all drug classes. In addition, quadruple therapy was more often prescribed to patients treated in a dedicated HF outpatient clinic as compared to a general cardiology outpatient clinic. In each GDMT drug class, 19% to 36% of non-use in HFrEF patients was related to side-effects, intolerances, or contraindications. In the de novo HF cohort, 49% of patients already used one or more GDMT drug classes for other indications than HF. Conclusion: This first analysis of the TITRATE-HF study reports relatively high use of GDMT in a contemporary HF cohort, while still showing room for improvement regarding quadruple therapy. Importantly, the use and dose of GDMT were suboptimal, with the reasons often remaining unclear. This underscores the urgency for further optimization of GDMT and implementation strategies within HF management.</p

    Contemporary guideline-directed medical therapy in de novo, chronic, and worsening heart failure patients: First data from the TITRATE-HF study

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    AIMS: Despite clear guideline recommendations for initiating four drug classes in all patients with heart failure (HF) with reduced ejection fraction (HFrEF) and the availability of rapid titration schemes, information on real-world implementation lags behind. Closely following the 2021 ESC HF guidelines and 2023 focused update, the TITRATE-HF study started to prospectively investigate the use, sequencing, and titration of guideline-directed medical therapy (GDMT) in HF patients, including the identification of implementation barriers. METHODS AND RESULTS: TITRATE-HF is an ongoing long-term HF registry conducted in the Netherlands. Overall, 4288 patients from 48 hospitals were included. Among these patients, 1732 presented with de novo, 2240 with chronic, and 316 with worsening HF. The median age was 71 years (interquartile range [IQR] 63-78), 29% were female, and median ejection fraction was 35% (IQR 25-40). In total, 44% of chronic and worsening HFrEF patients were prescribed quadruple therapy. However, only 1% of HFrEF patients achieved target dose for all drug classes. In addition, quadruple therapy was more often prescribed to patients treated in a dedicated HF outpatient clinic as compared to a general cardiology outpatient clinic. In each GDMT drug class, 19% to 36% of non-use in HFrEF patients was related to side-effects, intolerances, or contraindications. In the de novo HF cohort, 49% of patients already used one or more GDMT drug classes for other indications than HF. CONCLUSION: This first analysis of the TITRATE-HF study reports relatively high use of GDMT in a contemporary HF cohort, while still showing room for improvement regarding quadruple therapy. Importantly, the use and dose of GDMT were suboptimal, with the reasons often remaining unclear. This underscores the urgency for further optimization of GDMT and implementation strategies within HF management

    Pandora's Poison, Chlorine, Health, and a New Environmental Strategy, BY JOE THORNTON

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    Bias in normalization: Causes, consequences, detection and remedies

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    Introduction. Normalization is an optional step in LCIA that is used to better understand the relative importance and magnitude of the impact category indicator results. It is used for error checking, as a first step in weighting, and for standalone presentation of results. A normalized score for a certain impact category is obtained by determining the ratio of the category indicator result of the product and that of a reference system, such as the world in a certain year or the population of a specific area in a certain year. Biased Normalization. In determining these two quantities, the numerator, the denominator, or both can suffer from incompleteness due to a lack of emission data and/or characterisation factors. This leads to what we call a biased normalization. As a consequence, the normalized category indicator result can be too low or too high. Some examples from hypothetical and real case studies demonstrate this. Consequences of Biased Normalization. Especially when for some impact categories the normalized category indicator result is right, for others too low, and for others too high, severe problems in using normalized scores can show up. It is shown how this may affect the three types of usage of normalized results: error checking, weighting and standalone presentation. Detection and Remedies of Biased Normalization. Some easy checks are proposed that at least alert the LCA practitioner of the possibility of a biased result. These checks are illustrated for an example system on hydrogen production. A number of remedies of this problem is possible. These are discussed. In particular, case-dependent normalization is shown to solve some problems, but on the expense of creating other problems. Discussion. It appears that there is only one good solution: data-bases and tables of characterisation factors must be made more completely, so that the risk of detrimental bias is reduced. On the other hand, the use of the previously introduced checks should become a standard element in LCA practice, and should be facilitated with LCA software
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