Coronary revascularisation practices have evolved over the last three decades. This study sought to examine the variations in percutaneous coronary intervention (PCI) and coronary artery bypass graft (CABG) rates, alongside mortality from acute myocardial infarction (AMI) across a group of 16 high-income countries between 2006 and 2020.
Retrospective observational analysis using data from the Organisation for Economic Co-operation and Development (OECD) database between 2006 and 2020. Estimated annual percent change in revascularisation was analysed using Joinpoint regression model, and mortality rates were evaluated using the locally weighted scatterplot smoothing model.
Publicly available data on PCI and CABG procedure rates alongside AMI mortality rate from 2006 to 2020.
16 countries from the OECD database.
Not applicable.
Standardised PCI and CABG procedure rates and AMI age-standardised mortality rate (ASMR) from 2006 to 2020.
Over the 15 year period, 14.0 million PCI and 2.8 million CABG procedures were collectively recorded across 16 countries. PCI rates varied among nations, but from 2006 to 2020 increased in 11 of the 16 nations overall, led by Finland (+36.0%), Ireland (+34.5%) and France (+31.5%). Meanwhile, CABG rates declined in 14 out of the 16 countries, with Luxembourg (–71.3%), the UK (–62.6%) and Finland (–60.6%) experiencing the most substantial decreases. Throughout the study period, the PCI-to-CABG ratio increased, while AMI ASMR decreased consistently across all countries.
Despite evidence supporting CABG over PCI in specific scenarios, CABG rates have declined, and PCI rates have increased. Possible factors for this trend may include patient preference and advancement in interventional techniques. The varied use of PCI among these nations, alongside a sustained decline in AMI mortality rates, may be expected given the importance of optimal medical therapy in the management of ischaemic heart disease. The results further suggest the significance of factors beyond revascularisation in driving improved outcomes.
To establish, through patient and public involvement (PPI) events, the exercise barriers, facilitators and preferences of people with heart failure with preserved ejection fraction (HFpEF).
Qualitative ‘best fit’ framework analysis was used to analyse field notes and transcripts collected during three patient and public involvement meetings and three workshops. The best fit framework was based on the COM-B model of behaviour change, which has identified that Capability, Opportunity and Motivation components are essential for Behaviour change. The Consolidated criteria for Reporting Qualitative research checklist was used to structure the report.
Setting and participants: Community dwelling older adults with HFpEF.
24 people with HFpEF (n=16 female, 66%), 2 spouses and 2 people with chronic conditions participated in the PPI meetings and workshops. Multiple exercise-related capability (negative symptoms, functional ability, resilience and self-efficacy and knowledge and skill); opportunity (appealing components, optimal conditions, adequate support); and motivation factors (well-being, physical gains, goal achievement, sense of enjoyment) were identified as essential to facilitating change in exercise behaviours in people with HFpEF.
This study provides insight into capability, opportunity and motivation conditions that people with HFpEF feel are necessary to enable them to engage in exercise-related behaviour change. This work extends previous post hoc work by moving beyond identification of broad influencers that may enable or impede exercise intervention engagement, to identify intervention conditions necessary to affect change.
by Michael Seid, David Bridgeland, Christine L. Schuler, David M. Hartley
Improving the healthcare system is a persistent and pressing challenge. Collaborative Learning Health Systems, or Learning Health Networks (LHNs), are a novel, replicable organizational form in healthcare delivery that show substantial promise for improving health outcomes. To realize that promise requires a scientific understanding that can serve LHNs’ improvement and scaling. We translated social and organizational theories of collaboration to a computational (agent-based) model to develop a computer simulation of an LHN and demonstrate the potential of this new tool for advancing the science of LHNs. Model sensitivity analysis showed a small number of parameters with outsized effect on outcomes. Contour plots of these influential parameters allow exploration of alternative strategies for maximizing model outcomes of interest. A simulated trial of two common health system interventions – pre-visit planning and use of a registry – suggested that the efficacy of these could depend on LHN current state. By translating heuristic theories of LHNs to a specifiable, reproducible, and explicit model, this research advances the scientific study of LHNs using tools available from complex systems science.Rare diseases (RD) are collectively common and often genetic. Families value and can benefit from precise molecular diagnoses. Prolonged diagnostic odysseys exacerbate the burden of RD on patients, families and the healthcare system. Genome sequencing (GS) is a near-comprehensive test for genetic RD, but existing care models—where consultation with a medical geneticist is a prerequisite for testing—predate GS and may limit access or delay diagnosis. Evidence is needed to guide the optimal positioning of GS in care pathways. While initiating GS prior to geneticist consultation has been trialled in acute care settings, there are no data to inform the utility of this approach in outpatient care, where most patients with RD seek genetics services. We aim to evaluate the diagnostic yield, time to diagnosis, clinical and personal utility and incremental cost-effectiveness of GS initiated at the time of referral triage (pre-geneticist evaluation) compared with standard of care.
200 paediatric patients referred to one of two large genetics centres in Ontario, Canada, for suspected genetic RD will be randomised into a 1:1 ratio to the intervention (GS first) or standard of care (geneticist first) arm. An unblinded, permuted block randomisation design will be used, stratified within each recruitment site by phenotype and prior genetic testing. The primary outcome measure is time to genetic diagnosis or to cessation of active follow-up. Survival analysis will be used to analyse time-to-event data. Additional measures will include patient-reported and family-reported measures of satisfaction, understanding and perceived test utility, clinician-reported measures of perceived test utility and management impact, and healthcare system utilisation and costs.
This study was approved by Clinical Trials Ontario. Results will be disseminated, at minimum, via peer-reviewed journals, professional conferences and internal reports to funding bodies. Efforts will be made to share aggregated study results with participants and their families.