Unraveling the relationships between alpha- and beta-adrenergic modulation and the risk of heart failure

Background: The effects of α and ß adrenergic receptor modulation on the risk of developing heart failure (HF) remains uncertain due to a lack of randomized controlled trials. This study aimed to estimate the effects of α and ß adrenergic receptors modulation on the risk of HF and to provide proof of principle for genetic target validation studies in HF. Methods: Genetic variants within the cis regions encoding the adrenergic receptors α1A, α2B, ß1, and ß2 associated with blood pressure in a 757,601-participant genome-wide association study (GWAS) were selected as instruments to perform a drug target Mendelian randomization study. Effects of these variants on HF risk were derived from the HERMES GWAS (542,362 controls; 40,805 HF cases). Results: Lower α1A or ß1 activity was associated with reduced HF risk: odds ratio (OR) 0.83 (95% CI 0.74–0.93, P = 0.001) and 0.95 (95% CI 0.93–0.97, P = 8 × 10−6). Conversely, lower α2B activity was associated with increased HF risk: OR 1.09 (95% CI 1.05–1.12, P = 3 × 10−7). No evidence of an effect of lower ß2 activity on HF risk was found: OR 0.99 (95% CI 0.92–1.07, P = 0.95). Complementary analyses showed that these effects were consistent with those on left ventricular dimensions and acted independently of any potential effect on coronary artery disease. Conclusions: This study provides genetic evidence that α1A or ß1 receptor inhibition will likely decrease HF risk, while lower α2B activity may increase this risk. Genetic variant analysis can assist with drug development for HF prevention

Patients' and public views and attitudes towards the sharing of health data for research: A narrative review of the empirical evidence

Introduction: International sharing of health data opens the door to the study of the so-called 'Big Data', which holds great promise for improving patient-centred care. Failure of recent data sharing initiatives indicates an urgent need to invest in societal trust in researchers and institutions. Key to an informed understanding of such a 'social license' is identifying the views patients and the public may hold with regard to data sharing for health research. Methods: We performed a narrative review of the empirical evidence addressing patients' and public views and attitudes towards the use of health data for research purposes. The literature databases PubMed (MEDLINE), Embase, Scopus and Google Scholar were searched in April 2019 to identify relevant publications. Patients' and public attitudes were extracted from selected references and thematically categorised. Results: Twenty-seven papers were included for review, including both qualitative and quantitative studies and systematic reviews. Results suggest widespread - though conditional - support among patients and the public for data sharing for health research. Despite the fact that participants recognise actual or potential benefits of data research, they expressed concerns about breaches of confidentiality and potential abuses of the data. Studies showed agreement on the following conditions: value, privacy, risk minimisation, data security, transparency, control, information, trust, responsibility and accountability. Conclusions: Our results indicate that a social license for data-intensive health research cannot simply be presumed. To strengthen the social license, identified conditions ought to be operationalised in a governance framework that incorporates the diverse patient and public values, needs and interests

CODE-EHR best-practice framework for the use of structured electronic health-care records in clinical research.

Big data is important to new developments in global clinical science that aim to improve the lives of patients. Technological advances have led to the regular use of structured electronic health-care records with the potential to address key deficits in clinical evidence that could improve patient care. The COVID-19 pandemic has shown this potential in big data and related analytics but has also revealed important limitations. Data verification, data validation, data privacy, and a mandate from the public to conduct research are important challenges to effective use of routine health-care data. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including representation from patients, clinicians, scientists, regulators, journal editors, and industry members. In this Review, we propose the CODE-EHR minimum standards framework to be used by researchers and clinicians to improve the design of studies and enhance transparency of study methods. The CODE-EHR framework aims to develop robust and effective utilisation of health-care data for research purposes

CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research.

Big data is central to new developments in global clinical science aiming to improve the lives of patients. Technological advances have led to the routine use of structured electronic healthcare records with the potential to address key gaps in clinical evidence. The covid-19 pandemic has demonstrated the potential of big data and related analytics, but also important pitfalls. Verification, validation, and data privacy, as well as the social mandate to undertake research are key challenges. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including patient representatives, clinicians, scientists, regulators, journal editors and industry. We propose the CODE-EHR Minimum Standards Framework as a means to improve the design of studies, enhance transparency and develop a roadmap towards more robust and effective utilisation of healthcare data for research purposes

CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research

Big data is central to new developments in global clinical science aiming to improve the lives of patients. Technological advances have led to the routine use of structured electronic healthcare records with the potential to address key gaps in clinical evidence. The covid-19 pandemic has demonstrated the potential of big data and related analytics, but also important pitfalls. Verification, validation, and data privacy, as well as the social mandate to undertake research are key challenges. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including patient representatives, clinicians, scientists, regulators, journal editors and industry. We propose the CODE-EHR Minimum Standards Framework as a means to improve the design of studies, enhance transparency and develop a roadmap towards more robust and effective utilisation of healthcare data for research purposes

Using eco-design tools: An overview of experts' practices

International audienceThe practice of eco-design requires relating traditional design criteria to new environmental criteria. So far, few studies have investigated the nature and singularities of eco-design. This article provides some elements of response based upon the redesign of a consumer product (disposable razor). The study was conducted by three groups of experienced eco-designers using existing eco-design tools (SIMAPRO, ECOFAIRE, ECODESIGN PILOT). A protocol analysis with a three-level coding of transactions was carried out for this purpose. Two main findings are reported: (1) environmental assessment, solution finding and strategy definition are the activities which differentiate eco-design from design; (2) environmental initial assessment and strategy definition are more heavily influenced by eco-designers’ expertise than support from tools.Highlights► This study investigates the nature and singularities of eco-design compared to traditional design. ► A protocol analysis based on the observation of three experienced eco-designers' teams is conducted. ► Each team implements a different existing eco-design tool to redesign the same consumer product. ► Environmental assessment, solution finding and strategy definition appear to be specific to eco-design practice. ► Initial environmental assessment and strategy definition are heavily influenced by eco-designers' expertise

Genetic drug target validation using Mendelian randomisation

Mendelian randomisation (MR) analysis of drug targets has potential to aid drug development. Here, the authors introduce a mathematical framework to elucidate this specific application of MR

A population-based study of 92 clinically recognised risk factors for heart failure: co-occurrence, prognosis and preventive potential.

BACKGROUND Primary prevention strategies for heart failure(HF) have had limited success, possibly due to a wide range of underlying risk factors(RFs). Systematic evaluations of the prognostic burden and preventive potential across this wide range of risk factors are lacking. OBJECTIVE To estimate evidence, prevalence and co-occurrence for primary prevention and impact on prognosis of RFs for incident HF. METHODS We systematically reviewed trials and observational evidence of primary HF prevention across 92 putative aetiologic RFs for HF identified from US and European clinical practice guidelines. We identified 170 885 individuals aged ≥30 years with incident HF from 1997-2017, using linked primary and secondary care UK electronic health records(EHR) and rule-based phenotypes(ICD-10, Read Version 2, OPCS-4 procedure and medication codes) for each of 92 RFs. RESULTS Only 10/92 factors had high quality observational evidence for association with incident HF; 7 had effective RCT-based interventions for HF prevention(RCT-HF), and 6 for CVD prevention, but not HF(RCT-CVD), and the remainder had no RCT-based preventive interventions(RCT-0). We were able to map 91/92 risk factors to EHR using 5961 terms, and 88/91 factors were represented by at least one patient. In the 5 years prior to HF diagnosis, 44.3% had ≥4 RFs. By RCT evidence, the most common RCT-HF RFs were hypertension(48.5%), stable angina(34.9%), unstable angina(16.8%), myocardial infarction(15.8%), and diabetes(15.1%); RCT-CVD RFs were smoking(46.4%) and obesity(29.9%); and RCT-0 RFs were atrial arrhythmias(17.2%), cancer(16.5%),), heavy alcohol intake(14.9%). Mortality at 1 year varied across all 91 factors(lowest: pregnancy-related hormonal disorder 4.2%; highest: phaeochromocytoma 73.7%). Among new HF cases, 28.5% had no RCT-HF RFs and 38.6% had no RCT-CVD RFs. 15.6% had either no RF or only RCT-0 RFs. CONCLUSION 1 in 6 individuals with HF have no recorded RFs or RFs without trials. We provide a systematic map of primary preventive opportunities across a wide range of RFs for HF, demonstrating a high burden of co-occurrence and the need for trials tackling multiple RFs

CODE-EHR best practice framework for the use of structured electronic healthcare records in clinical research:international stakeholder consensus organised by the European Society

Big data is central to new developments in global clinical science aiming to improve the lives of patients. Technological advances have led to the routine use of structured electronic healthcare records with the potential to address key gaps in clinical evidence. The covid-19 pandemic has demonstrated the potential of big data and related analytics, but also important pitfalls. Verification, validation, and data privacy, as well as the social mandate to undertake research are key challenges. The European Society of Cardiology and the BigData@Heart consortium have brought together a range of international stakeholders, including patient representatives, clinicians, scientists, regulators, journal editors and industry. We propose the CODE-EHR Minimum Standards Framework as a means to improve the design of studies, enhance transparency and develop a roadmap towards more robust and effective utilisation of healthcare data for research purposes