Undertaking multi-centre randomised controlled trials in primary care: learnings and recommendations from the PULsE-AI trial researchers

Background Conducting effective and translational research can be challenging and few trials undertake formal reflection exercises and disseminate learnings from them. Following completion of our multicentre randomised controlled trial, which was impacted by the COVID-19 pandemic, we sought to reflect on our experiences and share our thoughts on challenges, lessons learned, and recommendations for researchers undertaking or considering research in primary care. Methods Researchers involved in the Prediction of Undiagnosed atriaL fibrillation using a machinE learning AlgorIthm (PULsE-AI) trial, conducted in England from June 2019 to February 2021 were invited to participate in a qualitative reflection exercise. Members of the Trial Steering Committee (TSC) were invited to attend a semi-structured focus group session, Principal Investigators and their research teams at practices involved in the trial were invited to participate in a semi-structured interview. Following transcription, reflexive thematic analysis was undertaken based on pre-specified themes of recruitment, challenges, lessons learned, and recommendations that formed the structure of the focus group/interview sessions, whilst also allowing the exploration of new themes that emerged from the data. Results Eight of 14 members of the TSC, and one of six practices involved in the trial participated in the reflection exercise. Recruitment was highlighted as a major challenge encountered by trial researchers, even prior to disruption due to the COVID-19 pandemic. Researchers also commented on themes such as the need to consider incentivisation, and challenges associated with using technology in trials, especially in older age groups. Conclusions Undertaking a formal reflection exercise following the completion of the PULsE-AI trial enabled us to review experiences encountered whilst undertaking a prospective randomised trial in primary care. In sharing our learnings, we hope to support other clinicians undertaking research in primary care to ensure that future trials are of optimal value for furthering knowledge, streamlining pathways, and benefitting patients

2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation: executive summary.

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2017 HRS/EHRA/ECAS/APHRS/SOLAECE expert consensus statement on catheter and surgical ablation of atrial fibrillation: executive summary.

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Undertaking multi-centre randomised controlled trials in primary care: learnings and recommendations from the PULsE-AI trial researchers.

BACKGROUND: Conducting effective and translational research can be challenging and few trials undertake formal reflection exercises and disseminate learnings from them. Following completion of our multicentre randomised controlled trial, which was impacted by the COVID-19 pandemic, we sought to reflect on our experiences and share our thoughts on challenges, lessons learned, and recommendations for researchers undertaking or considering research in primary care. METHODS: Researchers involved in the Prediction of Undiagnosed atriaL fibrillation using a machinE learning AlgorIthm (PULsE-AI) trial, conducted in England from June 2019 to February 2021 were invited to participate in a qualitative reflection exercise. Members of the Trial Steering Committee (TSC) were invited to attend a semi-structured focus group session, Principal Investigators and their research teams at practices involved in the trial were invited to participate in a semi-structured interview. Following transcription, reflexive thematic analysis was undertaken based on pre-specified themes of recruitment, challenges, lessons learned, and recommendations that formed the structure of the focus group/interview sessions, whilst also allowing the exploration of new themes that emerged from the data. RESULTS: Eight of 14 members of the TSC, and one of six practices involved in the trial participated in the reflection exercise. Recruitment was highlighted as a major challenge encountered by trial researchers, even prior to disruption due to the COVID-19 pandemic. Researchers also commented on themes such as the need to consider incentivisation, and challenges associated with using technology in trials, especially in older age groups. CONCLUSIONS: Undertaking a formal reflection exercise following the completion of the PULsE-AI trial enabled us to review experiences encountered whilst undertaking a prospective randomised trial in primary care. In sharing our learnings, we hope to support other clinicians undertaking research in primary care to ensure that future trials are of optimal value for furthering knowledge, streamlining pathways, and benefitting patients

Garotas de loja, história social e teoria social [Shop Girls, Social History and Social Theory]

Shop workers, most of them women, have made up a significant proportion of Britain’s labour force since the 1850s but we still know relatively little about their history. This article argues that there has been a systematic neglect of one of the largest sectors of female employment by historians and investigates why this might be. It suggests that this neglect is connected to framings of work that have overlooked the service sector as a whole as well as to a continuing unease with the consumer society’s transformation of social life. One element of that transformation was the rise of new forms of aesthetic, emotional and sexualised labour. Certain kinds of ‘shop girls’ embodied these in spectacular fashion. As a result, they became enduring icons of mass consumption, simultaneously dismissed as passive cultural dupes or punished as powerful agents of cultural destruction. This article interweaves the social history of everyday shop workers with shifting representations of the ‘shop girl’, from Victorian music hall parodies, through modernist social theory, to the bizarre bombing of the Biba boutique in London by the Angry Brigade on May Day 1971. It concludes that progressive historians have much to gain by reclaiming these workers and the service economy that they helped create

Ablation versus anti-arrhythmic therapy for reducing all hospital episodes from recurrent atrial fibrillation: a prospective, randomized, multi-centre, open label trial

Aims: There is rising healthcare utilization related to the increasing incidence and prevalence of atrial fibrillation (AF) worldwide. Simplifying therapy and reducing hospital episodes would be a valuable development. The efficacy of a streamlined AF ablation approach was compared to drug therapy and a conventional catheter ablation technique for symptom control in paroxysmal AF. Methods and results: We recruited 321 patients with symptomatic paroxysmal AF to a prospective randomized, multi-centre, open label trial at 13 UK hospitals. Patients were randomized 1:1:1 to cryo-balloon ablation without electrical mapping with patients discharged same day [Ablation Versus Anti-arrhythmic Therapy for Reducing All Hospital Episodes from Recurrent (AVATAR) protocol]; optimization of drug therapy; or cryo-balloon ablation with confirmation of pulmonary vein isolation and overnight hospitalization. The primary endpoint was time to any hospital episode related to treatment for atrial arrhythmia. Secondary endpoints included complications of treatment and quality-of-life measures. The hazard ratio (HR) for a primary endpoint event occurring when comparing AVATAR protocol arm to drug therapy was 0.156 (95% CI, 0.097–0.250; P < 0.0001 by Cox regression). Twenty-three patients (21%) recorded an endpoint event in the AVATAR arm compared to 76 patients (74%) within the drug therapy arm. Comparing AVATAR and conventional ablation arms resulted in a non-significant HR of 1.173 (95% CI, 0.639–2.154; P = 0.61 by Cox regression) with 23 patients (21%) and 19 patients (18%), respectively, recording primary endpoint events (P = 0.61 by log-rank test). Conclusion: The AVATAR protocol was superior to drug therapy for avoiding hospital episodes related to AF treatment, but conventional cryoablation was not superior to the AVATAR protocol. This could have wide-ranging implications on how demand for AF symptom control is met. Trial registration Clinical Trials Registration: NCT02459574

Identification of undiagnosed atrial fibrillation using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI) in primary care: a multi-centre randomised controlled trial in England

OBJECTIVE: The PULsE-AI trial sought to determine the effectiveness of a screening strategy that included a machine learning risk prediction algorithm in conjunction with diagnostic testing for identification of undiagnosed atrial fibrillation (AF) in primary care. This study aimed to evaluate the cost-effectiveness of implementing the screening strategy in a real-world setting. METHODS: Data from the PULsE-AI trial - a prospective, randomized, controlled trial conducted across six general practices in England from June 2019 to February 2021 - were used to inform a cost-effectiveness analysis that included a hybrid screening decision tree and Markov AF disease progression model. Model outcomes were reported at both individual- and population-level (estimated UK population ≥30 years of age at high-risk of undiagnosed AF) and included number of patients screened, number of AF cases identified, mean total and incremental costs (screening, events, treatment), quality-adjusted-life-years (QALYs), and incremental cost-effectiveness ratio (ICER). RESULTS: The screening strategy was estimated to result in 45,493 new diagnoses of AF across the high-risk population in the UK (3.3 million), and an estimated additional 14,004 lifetime diagnoses compared with routine care only. Per-patient costs for high-risk individuals who underwent the screening strategy were estimated at £1,985 (vs £1,888 for individuals receiving routine care only). At a population-level, the screening strategy was associated with a cost increase of approximately £322 million and an increase of 81,000 QALYs. The screening strategy demonstrated cost-effectiveness versus routine care only at an accepted ICER threshold of £20,000 per QALY-gained, with an ICER of £3,994/QALY. CONCLUSIONS: Compared with routine care only, it is cost-effective to target individuals at high risk of undiagnosed AF, through an AF risk prediction algorithm, who should then undergo diagnostic testing. This AF risk prediction algorithm can reduce the number of patients needed to be screened to identify undiagnosed AF, thus alleviating primary care burden