Sex-differences in oral anticoagulation therapy in patients hospitalized with atrial fibrillation:a nationwide cohort study

Background Important disparities in the treatment and outcomes of women and men with atrial fibrillation (AF) are well recognized. Whether introduction of direct oral anticoagulants has reduced disparities in treatment is uncertain. Methods and Results All patients who had an incident hospitalization from 2010 to 2019 with nonvalvular AF in Scotland were included in the present cohort study. Community drug dispensing data were used to determine prescribed oral anticoagulation therapy and comorbidity status. Logistic regression modeling was used to evaluate patient factors associated with treatment with vitamin K antagonists and direct oral anticoagulants. A total of 172 989 patients (48% women [82 833 of 172 989]) had an incident hospitalization with nonvalvular AF in Scotland between 2010 and 2019. By 2019, factor Xa inhibitors accounted for 83.6% of all oral anticoagulants prescribed, while treatment with vitamin K antagonists and direct thrombin inhibitors declined to 15.9% and 0.6%, respectively. Women were less likely to be prescribed any oral anticoagulation therapy compared with men (adjusted odds ratio [aOR], 0.68 [95% CI, 0.67–0.70]). This disparity was mainly attributed to vitamin K antagonists (aOR, 0.68 [95% CI, 0.66–0.70]), while there was less disparity in the use of factor Xa inhibitors between women and men (aOR, 0.92 [95% CI, 0.90–0.95]). Conclusions Women with nonvalvular AF were significantly less likely to be prescribed vitamin K antagonists compared with men. Most patients admitted to the hospital in Scotland with incident nonvalvular AF are now treated with factor Xa inhibitors and this is associated with fewer treatment disparities between women and men

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

Identification of undiagnosed atrial fibrillation patients using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI): Study protocol for a randomised controlled trial

Atrial fibrillation (AF) is associated with an increased risk of stroke, enhanced stroke severity, and other comorbidities. However, AF is often asymptomatic, and frequently remains undiagnosed until complications occur. Current screening approaches for AF lack either cost-effectiveness or diagnostic sensitivity; thus, there is interest in tools that could be used for population screening. An AF risk prediction algorithm, developed using machine learning from a UK dataset of 2,994,837 patients, was found to be more effective than existing models at identifying patients at risk of AF. Therefore, the aim of the trial is to assess the effectiveness of this risk prediction algorithm combined with diagnostic testing for the identification of AF in a real-world primary care setting. Eligible participants (aged =30?years and without an existing AF diagnosis) registered at participating UK general practices will be randomised into intervention and control arms. Intervention arm participants identified at highest risk of developing AF (algorithm risk score?=?7.4%) will be invited for a 12-lead electrocardiogram (ECG) followed by two-weeks of home-based ECG monitoring with a KardiaMobile device. Control arm participants will be used for comparison and will be managed routinely. The primary outcome is the number of AF diagnoses in the intervention arm compared with the control arm during the research window. If the trial is successful, there is potential for the risk prediction algorithm to be implemented throughout primary care for narrowing the population considered at highest risk for AF who could benefit from more intensive screening for AF. Trial Registration: NCT04045639

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

Transient Loss of Consciousness in a Patient with a Brugada Like ECG

Syncope in a patient with a Brugada syndrome channelopathy carries significant prognostic implications and warrants consideration of implantable cardioverter defibrillator (ICD) implantation. We report a case of a 62- year-old gentleman who presented with a transient loss of consciousness and an electrocardiogram (ECG) suggestive of type 1 Brugada syndrome. Further investigation revealed evidence of a silent myocardial infarction and negative ventricular tachycardia stimulation and Ajmaline testing. Careful review of the ECG’s subsequently showed the type 1 pattern was present in only V1

Transient loss of consciousness in a patient with a Brugada like ECG

Syncope in a patient with a Brugada syndrome channelopathy carries significant prognostic implications and warrants consideration of implantable cardioverter defibrillator (ICD) implantation. We report a case of a 62- year-old gentleman who presented with a transient loss of consciousness and an electrocardiogram (ECG) suggestive of type 1 Brugada syndrome. Further investigation revealed evidence of a silent myocardial infarction and negative ventricular tachycardia stimulation and Ajmaline testing. Careful review of the ECG’s subsequently showed the type 1 pattern was present in only V1

Ischaemic Lumbosacral Plexopathy Following Aorto-Iliac Bypass Graft: Case Report and Review of Literature

A 77-year-old man had aorto-iliac bypass for an abdominal aortic aneurysm (AAA). This was complicated by occlusion that needed extension of the graft to the right femoral artery. He was unable to move his right leg with numbness after surgery. This was caused by extensive lumbosacral plexopathy on the right side. Lumbosacral plexopathy is uncommon because the plexus has a rich blood supply. The incidence of ischaemic lumbosacral plexopathy is higher with re-operative and emergency AAA reconstruction. This may predispose the lumbosacral plexus to ischaemic injury. Consideration should be given to maintaining retrograde perfusion of the internal iliac artery

Survival following localised aortic atherosclerotic plaque rupture

Spontaneous rupture of the aorta due to ruptured atherosclerotic plaque is extremely rare. Despite the high prevalence of atherosclerosis, only four cases have been reported to have been identified and treated successfully; the remainder were diagnosed postmortem. We report a surviving case of pericardial tamponade due to highly localised aortic atherosclerotic plaque rupture

Using machine learning to predict anticoagulation control in atrial fibrillation: A UK Clinical Practice Research Datalink study

Objective: To investigate the predictive performance of machine learning (ML) algorithms for estimating anticoagulation control in patients with atrial fibrillation (AF) who are treated with warfarin. Methods: This was a retrospective cohort study of adult patients (≥18 years) between 2007 and 2016 using linked primary and secondary care data (Clinical Practice Research Datalink GOLD and Hospital Episode Statistics). Various ML techniques were explored to predict suboptimal anticoagulation control, defined as time in therapeutic range (TTR) 80 years and <70 kg, respectively). Addition of time-varying data to the LSTM NN improved predictive performance, plateauing at AUC of 0.830 at 30 weeks. Conclusion: ML algorithms displayed clinically useful ability to predict patients who are at greater risk of suboptimal control. The addition of time-varying data to the algorithm, especially prior INR measurements, improved predictive performance. These algorithms provide improved predictive tools for identifying patients who may benefit from more frequent INR monitoring or switching to alternative therapies

Sex-differences in oral anticoagulation therapy in patients hospitalized with atrial fibrillation: a nationwide cohort study

No abstract available