Fusion pacing with biventricular, left ventricular-only and multipoint pacing in cardiac resynchronisation therapy: Latest evidence and strategies for use

Despite advances in the field of cardiac resynchronisation therapy (CRT), response rates and durability of therapy remain relatively static. Optimising device timing intervals may be the most common modifiable factor influencing CRT efficacy after implantation. This review addresses the concept of fusion pacing as a method for improving patient outcomes with CRT. Fusion pacing describes the delivery of CRT pacing with a programming strategy to preserve intrinsic atrioventricular (AV) conduction and ventricular activation via the right bundle branch. Several methods have been assessed to achieve fusion pacing. QRS complex duration (QRSd) shortening with CRT is associated with improved clinical response. Dynamic algorithm-based optimisation targeting narrowest QRSd in patients with intact AV conduction has shown promise in people with heart failure with left bundle branch block. Individualised dynamic programming achieving fusion may achieve the greatest magnitude of electrical synchrony, measured by QRSd narrowing

Implementing civic engagement within mental health services in South East Asia: a systematic review and realist synthesis of current evidence

Introduction: Civic engagement (CE) has the potential to transform mental health services and could be particularly important for low and middle-income countries (LMICs), which are rapidly developing to respond to the burden of poor mental health. Research from high income countries has found many challenges associated with the meaningful implementation of CE in practice, but this has been underexplored in LIMCS and in South East Asia (SEA) in particular. Methods: We completed a realist synthesis and systematic review of peer reviewed publications and grey literature to identify the context and actions which promote successful implementation of CE approaches in SEA. We used a theory-driven approach—realist synthesis—to analyse data and develop context-mechanism-outcome configurations that can be used to explain how civic engagement approaches operate in South East Asian contexts. We worked closely with patient and public representatives to guide the review from the outset. Results: Fifty-seven published and unpublished articles were included, 24 were evaluations of CE, including two Randomized Controlled Trials. The majority of CE interventions featured uptake or adaptation of Western models of care. We identified important cultural differences in the enactment of civic engagement in SEA contexts and four mechanisms which, alongside their contextual barriers and facilitators, can be used to explain how civic engagement produces a range of outcomes for people experiencing mental health problems, their families and communities. Our review illustrates how CE interventions can be successfully implemented in SEA, however Western models should be adapted to fit with local cultures and values to promote successful implementation. Barriers to implementation included distrust of services/outside agencies, stigma, paternalistic cultures, limited resource and infrastructure. Conclusion: Our findings provide guidance for the implementation of CE approaches within SEA contexts and identify areas for further research. Due to the collectivist nature of many SEA cultures, and the impact of shared traumas on community mental health, CE might best be implemented at community level, with a focus on relational decision making. Registration This review is registered on PROSPERO: CRD42018087841

Recommendations for benefit–risk assessment methodologies and visual representations

Purpose The purpose of this study is to draw on the practical experience from the PROTECT BR case studies and make recommendations regarding the application of a number of methodologies and visual representations for benefit–risk assessment. Methods Eight case studies based on the benefit–risk balance of real medicines were used to test various methodologies that had been identified from the literature as having potential applications in benefit–risk assessment. Recommendations were drawn up based on the results of the case studies. Results A general pathway through the case studies was evident, with various classes of methodologies having roles to play at different stages. Descriptive and quantitative frameworks were widely used throughout to structure problems, with other methods such as metrics, estimation techniques and elicitation techniques providing ways to incorporate technical or numerical data from various sources. Similarly, tree diagrams and effects tables were universally adopted, with other visualisations available to suit specific methodologies or tasks as required. Every assessment was found to follow five broad stages: (i) Planning, (ii) Evidence gathering and data preparation, (iii) Analysis, (iv) Exploration and (v) Conclusion and dissemination. Conclusions Adopting formal, structured approaches to benefit–risk assessment was feasible in real-world problems and facilitated clear, transparent decision-making. Prior to this work, no extensive practical application and appraisal of methodologies had been conducted using real-world case examples, leaving users with limited knowledge of their usefulness in the real world. The practical guidance provided here takes us one step closer to a harmonised approach to benefit–risk assessment from multiple perspectives

OPTIMISE: MS study protocol: a pragmatic, prospective observational study to address the need for, and challenges with, real world pharmacovigilance in multiple sclerosis

IntroductionThe power of ‘real world’ data to improve our understanding of the clinical aspects of multiple sclerosis (MS) is starting to be realised. Disease modifying therapy (DMT) use across the UK is driven by national prescribing guidelines. As such, the UK provides an ideal country in which to gather MS outcomes data. A rigorously conducted observational study with a focus on pharmacovigilance has the potential to provide important data to inform clinicians and patients while testing the reliability of estimates from pivotal trials when applied to patients in the UK.Methods and analysisThe primary aim of this study is to characterise the incidence and compare the risk of serious adverse events in people with MS treated with DMTs. The OPTIMISE:MS database enables electronic data capture and secure data transfer. Selected clinical data, clinical histories and patient-reported outcomes are collected in a harmonised fashion across sites at the time of routine clinical visits. The first patient was recruited to the study on 24 May 2019. As of January 2021, 1615 individuals have baseline data recorded; follow-up data are being captured and will be reported in due course.Ethics and disseminationThis study has ethical permission (London City and East; Ref 19/LO/0064). Potential concerns around data storage and sharing are mitigated by the separation of identifiable data from all other clinical data, and limiting access to any identifiable data. The results of this study will be disseminated via publication. Participants provide consent for anonymised data to be shared for further research use, further enhancing the value of the study.</jats:sec

Exploiting relationships between outcomes in Bayesian multivariate network meta-analysis with an application to relapsing-remitting multiple sclerosis

In multivariate network meta‐analysis (NMA), the piecemeal nature of the evidence base means that there may be treatment‐outcome combinations for which no data is available. Most existing multivariate evidence synthesis models are either unable to estimate the missing treatment‐outcome combinations, or can only do so under particularly strong assumptions, such as perfect between‐study correlations between outcomes or constant effect size across outcomes. Many existing implementations are also limited to two treatments or two outcomes, or rely on model specification that is heavily tailored to the dimensions of the dataset. We present a Bayesian multivariate NMA model that estimates the missing treatment‐outcome combinations via mappings between the population mean effects, while allowing the study‐specific effects to be imperfectly correlated. The method is designed for aggregate‐level data (rather than individual patient data) and is likely to be useful when modeling multiple sparsely reported outcomes, or when varying definitions of the same underlying outcome are adopted by different studies. We implement the model via a novel decomposition of the treatment effect variance, which can be specified efficiently for an arbitrary dataset given some basic assumptions regarding the correlation structure. The method is illustrated using data concerning the efficacy and liver‐related safety of eight active treatments for relapsing‐remitting multiple sclerosis. The results indicate that fingolimod and interferon beta‐1b are the most efficacious treatments but also have some of the worst effects on liver safety. Dimethyl fumarate and glatiramer acetate perform reasonably on all of the efficacy and safety outcomes in the model

Challenges and Opportunities of Real-World Data: Statistical Analysis Plan for the Optimise:MS Multicenter Prospective Cohort Pharmacovigilance Study.

Introduction: Optimise:MS is an observational pharmacovigilance study aimed at characterizing the safety profile of disease-modifying therapies (DMTs) for multiple sclerosis (MS) in a real world population. The study will categorize and quantify the occurrence of serious adverse events (SAEs) in a cohort of MS patients recruited from clinical sites around the UK. The study was motivated particularly by a need to establish the safety profile of newer DMTs, but will also gather data on outcomes among treatment-eligible but untreated patients and those receiving established DMTs (interferons and glatiramer acetate). It will also explore the impact of treatment switching. Methods: Causal pathway confounding between treatment selection and outcomes, together with the variety and complexity of treatment and disease patterns observed among MS patients in the real world, present statistical challenges to be addressed in the analysis plan. We developed an approach for analysis of the Optimise:MS data that will include disproportionality-based signal detection methods adapted to the longitudinal structure of the data and a longitudinal time-series analysis of a cohort of participants receiving second-generation DMT for the first time. The time-series analyses will use a number of exposure definitions in order to identify temporal patterns, carryover effects and interactions with prior treatments. Time-dependent confounding will be allowed for via inverse-probability-of-treatment weighting (IPTW). Additional analyses will examine rates and outcomes of pregnancies and explore interactions of these with treatment type and duration. Results: To date 14 hospitals have joined the study and over 2,000 participants have been recruited. A statistical analysis plan has been developed and is described here. Conclusion: Optimise:MS is expected to be a rich source of data on the outcomes of DMTs in real-world conditions over several years of follow-up in an inclusive sample of UK MS patients. Analysis is complicated by the influence of confounding factors including complex treatment histories and a highly variable disease course, but the statistical analysis plan includes measures to mitigate the biases such factors can introduce. It will enable us to address key questions that are beyond the reach of randomized controlled trials