Evaluating the effect of inequalities in oral anti-coagulant prescribing on outcomes in people with atrial fibrillation.

Aims: Whilst anti-coagulation is typically recommended for thromboprophylaxis in atrial fibrillation (AF), it is often never prescribed or prematurely discontinued. The aim of this study was to evaluate the effect of inequalities in anti-coagulant prescribing by assessing stroke/systemic embolism (SSE) and bleeding risk in people with AF who continue anti-coagulation compared with those who stop transiently, permanently, or never start. Methods and results: This retrospective cohort study utilized linked Scottish healthcare data to identify adults diagnosed with AF between January 2010 and April 2016, with a CHA2DS2-VASC score of ≥2. They were sub-categorized based on anti-coagulant exposure: never started, continuous, discontinuous, and cessation. Inverse probability of treatment weighting-adjusted Cox regression and competing risk regression was utilized to compare SSE and bleeding risks between cohorts during 5-year follow-up. Of an overall cohort of 47 427 people, 26 277 (55.41%) were never anti-coagulated, 7934 (16.72%) received continuous anti-coagulation, 9107 (19.2%) temporarily discontinued, and 4109 (8.66%) permanently discontinued. Lower socio-economic status, elevated frailty score, and age ≥ 75 were associated with a reduced likelihood of initiation and continuation of anti-coagulation. Stroke/systemic embolism risk was significantly greater in those with discontinuous anti-coagulation, compared with continuous [subhazard ratio (SHR): 2.65; 2.39-2.94]. In the context of a major bleeding event, there was no significant difference in bleeding risk between the cessation and continuous cohorts (SHR 0.94; 0.42-2.14). Conclusion: Our data suggest significant inequalities in anti-coagulation prescribing, with substantial opportunity to improve initiation and continuation. Decision-making should be patient-centred and must recognize that discontinuation or cessation is associated with considerable thromboembolic risk not offset by mitigated bleeding risk.

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.

A Novel Risk Prediction Score for Clinically Significant Bleeding in Patients Anticoagulated for Venous Thromboembolism with Active Cancer.

BACKGROUND: Cancer-associated venous thromboembolism (Ca-VTE) treatment with anticoagulation is associated with bleeding complications and there are limited data on risk factors. Current models do not provide accurate bleeding risk prediction. METHODS: UK Clinical Practice Research Datalink data (2008-2020) were used to generate a cohort of patients with anticoagulant initiation for first Ca-VTE. Patients were observed up to 180 days for significant bleeding including major bleeding and clinically relevant nonmajor bleeding requiring hospitalization (CRNMB-H). A scoring scheme was developed from sub-distribution hazard ratios, and its discrimination (expressed by the C-statistic) estimated from cross-validation. RESULTS: A total of 15,749 patients with Ca-VTE and anticoagulant treatment were included. In total, 537 significant bleeding events, 161 major bleeds, and 376 CRNMB-H were identified after adjudicated review in 4,914 person-years of observation. Incidence rates of 3.3 and 7.7 per 100 person-years were noted for major bleeding and CRNMB-H. Independent predictors of significant bleeding included cancer of the bladder, central nervous system, cervix, kidney, melanoma, prostate and upper gastrointestinal tract, metastases, minor surgery, minor trauma, and history of major bleeding or CRNMB (before or after the Ca-VTE diagnosis). Patients recognized as low, medium, and high risk (30.4, 56.8, and 1.7% of the population, respectively) had a 6-month significant bleeding incidence rate of 5.1, 19.0, and 56.5 per 100 person-years, respectively. Overall C-statistic for significant bleeding was 0.70 (95% confidence interval: 0.65-0.75), and 0.76 (0.68-0.84) and 0.67 (0.61-0.73) for major bleeding and for CRNMB-H, respectively. CONCLUSION: This risk score may identify patients at risk of significant bleeding, while also helping to determine treatment duration.

An Update on Anti-thrombotic Therapy Following Transcatheter Aortic Valve Implantation: Expert Cardiologist Opinion from a UK and Ireland Delphi Group.

Transcatheter aortic valve implantation (TAVI) is an effective and established treatment for symptomatic aortic stenosis. However, there is a lack of consensus concerning the need for peri- and post-procedural anti-thrombotic medication. Contemporary guidelines recommend that anti-thrombotic therapy is balanced against a patient's bleeding risk following TAVI, but do not fully consider the evolving evidence base. The purpose of the Delphi panel recommendations presented here is to provide a consensus elicited from a panel of experts who regularly prescribe anti-thrombotic therapy post-TAVI. The goal was to address evidence gaps across four key topics: anti-thrombotic therapy (anti-platelet and/or anti-coagulant) in TAVI patients in sinus rhythm; anti-thrombotic therapy in TAVI patients with AF; direct oral anti-coagulants versus vitamin K antagonists; and the need for UK/Ireland specific guidance. This consensus statement aims to inform clinical decision-making by providing a concise, evidence-based summary of best practice for prescribing anti-thrombotic therapies following TAVI and highlights areas where further research is needed.

The association between brain volume loss and disability in multiple sclerosis: A systematic review.

BACKGROUND: Multiple sclerosis (MS) is a chronic, inflammatory, demyelinating, degenerative disease of the central nervous system that affects approximately 2.8 million people worldwide. Compelling evidence from observational studies and clinical trials indicates a strong association between brain volume loss (BVL) and the accumulation of disability in MS. However, the considerable heterogeneity in study designs and methods of assessment of BVL invites questions concerning the generalizability of the reported findings. Therefore, we conducted this systematic review to characterize the relationship between BVL and physical disability in patients with MS. METHODS: A systematic literature search of MEDLINE and EMBASE databases was performed supplemented by gray literature searches. The following study designs were included: prospective/retrospective cohort, cross-sectional and case-control. Only English language articles published from 2010 onwards were eligible for final inclusion. There were no restrictions on MS subtype, age, or ethnicity. Of the 1620 citations retrieved by the structured searches, 50 publications met our screening criteria and were included in the final data set. RESULTS: Across all BVL measures, there was considerable heterogeneity in studies regarding the underlying study population, the definitions of BVL and image analysis methodologies, the physical disability measure used, the measures of association reported and whether the analysis conducted was univariable or multivariable. A total of 36 primary studies providing data on the association between whole BVL and physical disability in MS collectively suggest that whole brain atrophy is associated with greater physical disability progression in MS patients. Similarly, a total of 15 primary studies providing data on the association between ventricular atrophy and physical disability in MS suggest that ventricular atrophy is associated with greater physical disability progression in MS patients. Along similar lines, the existing evidence based on a total of 13 primary studies suggests that gray matter atrophy is associated with greater physical disability progression in MS patients. Four primary studies suggest that corpus callosum atrophy is associated with greater physical disability progression in MS patients. The majority of the existing evidence (6 primary studies) suggests no association between white matter atrophy and physical disability in MS. It is difficult to assign a relationship between basal ganglia volume loss and physical disability as well as medulla oblongata width and physical disability in MS due to very limited data. CONCLUSION: The evidence gathered from this systematic review, although very heterogeneous, suggests that whole brain atrophy is associated with greater physical disability progression in MS patients. Our review can help define future imaging biomarkers for physical disability progression and treatment monitoring in MS.

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.

A consensus viewpoint on the role of direct factor Xa inhibitors in the management of cancer-associated venous thromboembolism in the UK.

OBJECTIVE: Cancer patients are at high risk of venous thromboembolism (VTE), a significant cause of cancer-related death. Historically, low molecular weight heparins (LMWH) were the gold standard therapy for cancer-associated VTE, but recent evidence supports the use of direct factor Xa inhibitors in cancer-associated VTE and this is now reflected in many guidelines. However, uptake of direct factor Xa inhibitors varies and guidance on the use of direct factor Xa inhibitors in specific cancer sub-populations and clinical situations is lacking. This review presents consensus expert opinion alongside evaluation of evidence to support healthcare professionals in the use of direct factor Xa inhibitors in cancer-associated VTE. METHODS: Recent guidelines, meta-analyses, reviews and clinical studies on anticoagulation therapy for cancer-associated VTE were used to direct clinically relevant topics and evidence to be systematically discussed using nominal group technique. The consensus manuscript and recommendations were developed based on these discussions. RESULTS: Considerations when prescribing anticoagulant therapy for cancer-associated VTE include cancer site and stage, systemic anti-cancer therapy (including vascular access), drug-drug interactions, length of anticoagulation, quality of life and needs during palliative care. Treatment of patients with kidney or liver impairment, gastrointestinal disorders, extremes of bodyweight, elevated bleeding or recurrence risk, VTE recurrence and COVID-19 is discussed. CONCLUSION: Anticoagulant therapy for cancer-associated VTE patients should be carefully selected with consideration given to the relative benefits of specific drugs when individualizing care. Direct factor Xa inhibitors are typically the treatment of choice for preventing VTE recurrence in non-cancer patients and should also be considered as such for cancer-associated VTE in most situations.

Major variation in hepatocellular carcinoma treatment and outcomes in England: a retrospective cohort study.

Objective: Hepatocellular carcinoma (HCC) is increasingly incident in England, while survival remains poor with regional disparities. We aimed to explore the differences in HCC treatment across different geographical regions and to examine the impact on cancer survival. Methods: Incident HCC cases and treatment were identified from the English Hospital Episode Statistics (2016-2017) and then a subset by National Health Service (NHS) regions. Treatment was grouped into curative, palliative and untreated. Median survival was estimated to date of death in the national statistics. Results: The median observed survival was 8.6 months (95% CI 7.5 to 9.9) across all 2160 HCC cases, 52.1 months (CI 50.5, not reached) in 449 (20.8%) treated with curative intent, 21.0 months (CI 18.5 to 24.5) after other cancer-specific treatment in 449 (20.8%), and 2.3 months (CI 2.1 to 2.6) in 1262 (58.4%) untreated. Across NHS regions, <50% of cases received treatment (30.4%-49.6%), while between 14.2% and 27.7% had curative treatment. The 3-year survival was similar (23.5%-29.7%), except in the London region (40.0%). Conclusion: Majority of HCC cases in England are untreated and survival remains low, with variation in outcomes in regions with similar incident rates. A deeper exploration of regional treatments and screening practice is required to improve early detection and survival.

Trends in direct oral anticoagulant (DOAC) prescribing in English primary care (2014-2019).

BACKGROUND: In England, most prescribing of direct-acting oral anticoagulants for atrial fibrillation (AF) is in primary care. However, there remain gaps in our understanding of dosage and disparities in use. We aimed to describe trends in direct oral anticoagulant (DOAC) prescribing, including dose reduction in people with renal impairment and other criteria, and adherence. METHODS: Using English primary care sentinel network data from 2014 to 2019, we assessed appropriate DOAC dose adjustment with creatinine clearance (CrCl). Our primary care sentinel cohort was a subset of 722 general practices, with 6.46 million currently registered patients at the time of this study. RESULTS: Of 6 464 129 people in the cohort, 2.3% were aged ≥18 years with a diagnosis of AF, and 30.8% of these were prescribed vitamin K antagonist and 69.1% DOACs. Appropriate DOAC prescribing following CrCl measures improved between 2014 and 2019; dabigatran from 21.3% (95% CI 15.1% to 28.8%) to 48.7% (95% CI 45.0% to 52.4%); rivaroxaban from 22.1% (95% CI 16.7% to 28.4%) to 49.9% (95% CI 48.5% to 53.3%); edoxaban from 10.0% (95% CI 0.3% to 44.5%) in 2016 to 57.6% (95% CI 54.5% to 60.7%) in 2019; apixaban from 30.8% (95% CI 9.1% to 61.4%) in 2015 to 60.5% (95% CI 57.8% to 63.2%) in 2019.Adherence was highest for factor Xa inhibitors, increasing from 50.1% (95% CI 47.7% to 52.4%) in 2014 to 57.8% (95% CI 57.4% to 58.2%) in 2019. Asian and black/mixed ethnicity was associated with non-adherence (OR 1.81, 95% CI 1.56 to 2.09) as was male gender (OR 1.19, 95% CI 1.15 to 1.22), higher socioeconomic status (OR 1.60, 95% CI 1.52 to 1.68), being an ex-smoker (OR 1.12, 95% CI 1.06 to 1.19) and hypertension (OR 1.07, 95% CI 1.03 to 1.17). CONCLUSIONS: The volume and quality of DOAC prescribing has increased yearly. Future interventions to augment quality of anticoagulant management should target disparities in adherence.

Investigating the feasibility of recruitment to an observational, quality-of-life study of patients diagnosed with atrial fibrillation (AF) who have experienced a bleed while anticoagulated: EQUAL-AF feasibility study protocol.

BACKGROUND: Oral anticoagulation therapies (OATs) are often prescribed in conjunction with medications to restore normal heart rate rhythm which can limit the risk of an atrial fibrillation (AF) related stroke and systemic thromboembolism. However, they are associated with the serious side effect of bleeding. Both clinically relevant nonmajor bleeding (CRNMB) and major bleeding while anticoagulated are believed to have a significant impact on patient quality of life (QoL). There is currently limited research into the effect bleeding has on QoL. The aim of this study is to evaluate the feasibility of identifying and recruiting patients diagnosed with AF, who are taking OATs and have recently experienced a bleed and collecting information on their QoL. METHODS: We will recruit a minimum of 50 patients to this cross-sectional, observational study. We will recruit from general practices, secondary care, and through an online AF forum. We will ask participants to complete three validated patient-reported outcome measures (PROMs), EQ5D, AFEQT, and PACT-Q, approximately 4 weeks following a bleed and again 3 months later. We will randomly select a subset of 10 participants (of those who agree to be interviewed) to undergo a structured interview with a member of the research team to explore the impact of bleeding on their QoL and to gain feedback on the three PROMs used. We will undertake a descriptive analysis of the PROMs and demographic data. We will analyse the qualitative interviews thematically to identify key themes. DISCUSSION: We aim to establish if it is possible to recruit patients and use PROMs to collect information regarding how patient QoL is affected when they experience either a clinically relevant non-major bleed (CRNMB) or major bleed while taking OATs for the management of AF. We will also explore the appropriateness, or otherwise, of the three identified PROMs for assessing quality of life following a bleed. PROMS: Three PROMs were selected following a literature review of similar QoL studies and using the COnsensus-based Standards for the selection of health Measurement INstruments (COSMIN) checklist for comparison. A review of the current literature produced no suitable validated PROM to record QoL experiences in patients who have been diagnosed with AF and have experienced a bleed while anticoagulated. As such, the EQ5D, AFEQT, and PACT-Q (part 2) were deemed most appropriate for use in this feasibility study. TRIAL REGISTRATION: The trial has been adopted onto the NIHR Portfolio (ID no. 47771) and registered with www. CLINICALTRIALS: gov (no. NCT04921176) retrospectively registered in June 2021.

Identification of undiagnosed atrial fibrillation using a machine learning risk prediction algorithm and diagnostic testing (PULsE-AI) in primary care: cost-effectiveness of a screening strategy evaluated in a randomized 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.

Budget impact analysis of a machine learning algorithm to predict high risk of atrial fibrillation among primary care patients.

AIMS: We investigated whether the use of an atrial fibrillation (AF) risk prediction algorithm could improve AF detection compared with opportunistic screening in primary care and assessed the associated budget impact. METHODS AND RESULTS: Eligible patients were registered with a general practice in UK, aged 65 years or older in 2018/19, and had complete data for weight, height, body mass index, and systolic and diastolic blood pressure recorded within 1 year. Three screening scenarios were assessed: (i) opportunistic screening and diagnosis (standard care); (ii) standard care replaced by the use of the algorithm; and (iii) combined use of standard care and the algorithm. The analysis considered a 3-year time horizon, and the budget impact for the National Health Service (NHS) costs alone or with personal social services (PSS) costs. Scenario 1 would identify 79 410 new AF cases (detection gap reduced by 22%). Scenario 2 would identify 70 916 (gap reduced by 19%) and Scenario 3 would identify 99 267 new cases (gap reduction 27%). These rates translate into 2639 strokes being prevented in Scenario 1, 2357 in Scenario 2, and 3299 in Scenario 3. The 3-year NHS budget impact of Scenario 1 would be £45.3 million, £3.6 million (difference ‒92.0%) with Scenario 2, and £46.3 million (difference 2.2%) in Scenario 3, but for NHS plus PSS would be ‒£48.8 million, ‒£80.4 million (64.8%), and ‒£71.3 million (46.1%), respectively. CONCLUSION: Implementation of an AF risk prediction algorithm alongside standard opportunistic screening could close the AF detection gap and prevent strokes while substantially reducing NHS and PSS combined care costs.

Meta-Analysis Comparing Apixaban Versus Rivaroxaban for Management of Patients With Nonvalvular Atrial Fibrillation.

To compare the efficacy and safety of apixaban and rivaroxaban for the prevention of stroke in patients with nonvalvular atrial fibrillation (NVAF) by way of a meta-analysis informed by real-world evidence. Systematic review and meta-analysis of observational studies including patients with NVAF on apixaban and rivaroxaban, which reported stroke/systemic embolism and/or major bleeding. Prospero registration number: CRD42021251719. Estimates of relative treatment effect (based on hazard ratios[HRs]) were pooled using the inverse variance method. Fixed-effects and random effect analyses were conducted. Exploratory meta-regression analyses that included study-level covariates were conducted using the metareg (meta-regression) command of Stata Statistical Software: Release 15.1 (College Station, Texas. StataCorp LLC.). Study level covariates explored in the meta-regression analyses were CHA2DS2-VASc and HAS-BLED scores. A total of 10 unique retrospective real-world evidence studies reported comparative estimates for apixaban versus rivaroxaban in patients with NVAF and were included in the meta-analysis. Adjusted HR was 0.88 (95% [confidence interval] CI 0.81 to 0.95), indicating a significantly lower hazard of stroke/systemic embolism associated with apixaban versus rivaroxaban. Pairwise meta-analysis for a major bleeding episode was significantly lower with apixaban compared with rivaroxaban (HR 0.62; 95% CI 0.56 to 0.69), whereas apixaban was associated with a lower risk of gastrointestinal bleeding compared with rivaroxaban (HR 0.57; 95% CI 0.50 to 0.64). In conclusion, this study suggests that patient CHA2DS2-VASc and HAS-BLED scores might be an important factor when selecting which direct oral anticoagulants to use, given the relation these scores have on treatment outcomes. Apixaban is associated with lower rates of both major and gastrointestinal bleeding than rivaroxaban, with no loss of efficacy.

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

Aims: The aim of the PULsE-AI trial was to assess the effectiveness of a machine learning risk-prediction algorithm in conjunction with diagnostic testing for identifying undiagnosed atrial fibrillation (AF) in primary care in England. Methods and results: Eligible participants (aged ≥30 years without AF diagnosis; n = 23 745) from six general practices in England were randomized into intervention and control arms. Intervention arm participants, identified by the algorithm as high risk of undiagnosed AF (n = 944), were invited for diagnostic testing (n = 256 consented); those who did not accept the invitation, and all control arm participants, were managed routinely. The primary endpoint was the proportion of AF, atrial flutter, and fast atrial tachycardia diagnoses during the trial (June 2019-February 2021) in high-risk participants. Atrial fibrillation and related arrhythmias were diagnosed in 5.63% and 4.93% of high-risk participants in intervention and control arms, respectively {odds ratio (OR) [95% confidence interval (CI)]: 1.15 (0.77-1.73), P = 0.486}. Among intervention arm participants who underwent diagnostic testing (28.1%), 9.41% received AF and related arrhythmia diagnoses [vs. 4.93% (control); OR (95% CI): 2.24 (1.31-3.73), P = 0.003]. Conclusion: The AF risk-prediction algorithm accurately identified high-risk participants in both arms. While the proportions of AF and related arrhythmia diagnoses were not significantly different between high-risk arms, intervention arm participants who underwent diagnostic testing were twice as likely to receive arrhythmia diagnoses compared with routine care. The algorithm could be a valuable tool to select primary care groups at high risk of undiagnosed AF who may benefit from diagnostic testing.

Detecting undiagnosed atrial fibrillation in UK primary care: Validation of a machine learning prediction algorithm in a retrospective cohort study.

AIMS: To evaluate the ability of a machine learning algorithm to identify patients at high risk of atrial fibrillation in primary care. METHODS: A retrospective cohort study was undertaken using the DISCOVER registry to validate an algorithm developed using a Clinical Practice Research Datalink (CPRD) dataset. The validation dataset included primary care patients in London, England aged ≥30 years from 1 January 2006 to 31 December 2013, without a diagnosis of atrial fibrillation in the prior 5 years. Algorithm performance metrics were sensitivity, specificity, positive predictive value, negative predictive value (NPV) and number needed to screen (NNS). Subgroup analysis of patients aged ≥65 years was also performed. RESULTS: Of 2,542,732 patients in DISCOVER, the algorithm identified 604,135 patients suitable for risk assessment. Of these, 3.0% (17,880 patients) had a diagnosis of atrial fibrillation recorded before study end. The area under the curve of the receiver operating characteristic was 0.87, compared with 0.83 in algorithm development. The NNS was nine patients, matching the CPRD cohort. In patients aged ≥30 years, the algorithm correctly identified 99.1% of patients who did not have atrial fibrillation (NPV) and 75.0% of true atrial fibrillation cases (sensitivity). Among patients aged ≥65 years (n = 117,965), the NPV was 96.7% with 91.8% sensitivity. CONCLUSIONS: This atrial fibrillation risk prediction algorithm, based on machine learning methods, identified patients at highest risk of atrial fibrillation. It performed comparably in a large, real-world population-based cohort and the developmental registry cohort. If implemented in primary care, the algorithm could be an effective tool for narrowing the population who would benefit from atrial fibrillation screening in the United Kingdom.

Outcomes in rheumatoid arthritis patients treated with abatacept: a UK multi-centre observational study.

BACKGROUND: Rheumatoid arthritis (RA) is an inflammatory autoimmune disease that causes chronic synovitis, resulting in progressive joint destruction and functional disability and affects approximately 400,000 people in the UK. This real-world study aimed to describe the characteristics, treatment patterns and clinical outcomes of patients who received abatacept in UK clinical practice. METHODS: This was a multi-centre, retrospective, observational study of patients with RA treated with abatacept at four UK centres between 01 January 2013 and 31 December 2017. Data were collected from medical records of each patient from the index date (date of first bDMARD initiation) until the most recent visit, death or end of study (31 December 2017). RESULTS: In total, 213 patients were included in the study. Patients received up to eight lines of therapy (LOTs). Treatment with abatacept, or any other bDMARD, was associated with reductions in DAS28-ESR and DAS28-CRP scores at 6 and 12 months. The distribution of EULAR responses (good/moderate/no response) tended to be more favourable for patients when receiving abatacept than when receiving other bDMARDs (22.8%/41.3%/35.9% versus 16.6%/41.4%/42.1% at 6 months, and 27.9%/36.1%/36.1% versus 21.2%/34.5%/44.2% at 12 months). Patients receiving abatacept at LOT1 (n = 68) spent significantly longer on treatment compared with patients receiving other bDMARDs (53.4 vs. 17.4 months; p< 0.01); a similar trend was observed for LOT2. Among patients who discontinued after 6 months, a greater proportion experienced infection requiring antibiotics when receiving other bDMARDs compared to those receiving abatacept. CONCLUSIONS: RA patients who received bDMARDs, including abatacept, experienced reduced disease activity. When receiving abatacept as first or second line of therapy, patients persisted with treatment significantly longer than those receiving other bDMARDs.

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 12­lead 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.

Real-world utility of HCV core antigen as an alternative to HCV RNA testing: Implications for viral load and genotype.

Following positive serology, the gold standard confirmatory test of hepatitis C virus (HCV) infection is detection of HCV RNA by PCR. We assessed the utility of HCV core antigen testing to identify active infection among those positive for anti-HCV antibodies, when introduced to routine testing. We identified serum samples that were tested at a single laboratory in Scotland from June 2011to December 2017. Serum samples testing positive for HCV antibodies (HCV Ab positive) followed by reflex HCV core antigen (Ag) testing during the study period were identified. Those patients for whom a PCR test was requested on the baseline sample were also identified. For this group, the sensitivity and specificity of HCV Ag as a diagnostic tool were assessed using HCV PCR as gold standard. In our cohort of 744 patients, we demonstrated a sensitivity of 82.1% (95% CI 77.1%-86.2%) and a specificity of 99.8% (95% CI 98.6%-100%). Genotype 3 was associated with increased odds of a false-negative result (OR = 3.59, 95% CI: 1.32-9.71), and reduced odds of a false negative were associated with older age (odds ratio (OR)=0.92, 95% CI: 0.88-0.97 per year) and viral load (OR = 0.10, 95% CI: 0.05-0.21 per log10 IU/ml). While the implementation of HCV core antigen testing for diagnosis could lead to significant cost savings in national screening programmes, our data suggest that a significant proportion of HCV-infected individuals may be missed. These findings have implications for HCV diagnosis and determination of viral clearance after treatment, particularly in low- and middle-income regions, where genotype 3 is prevalent.

Application of a machine learning algorithm for detection of atrial fibrillation in secondary care.

Atrial fibrillation (AF) is the most common sustained heart arrhythmia and significantly increases risk of stroke. Opportunistic AF testing in high-risk patients typically requires frequent electrocardiogram tests to capture the arrhythmia. Risk-prediction algorithms may help to more accurately identify people with undiagnosed AF and machine learning (ML) may aid in the diagnosis of AF. Here, we applied an AF-risk prediction algorithm to secondary care data linked to primary care data in the DISCOVER database in order to evaluate changes in model performance, and identify patients not previously detected in primary care. We identified an additional 5,444 patients who had an AF diagnosis only in secondary care during the data extraction period. 2,696 (49.5%) were accepted by the algorithm and the algorithm correctly assigned 2,637 (97.8%) patients to the AF cohort. Using a risk threshold of 7.4% in patients aged ≥ 30 years, algorithm sensitivity and specificity was 38% and 95%, respectively. Approximately 15% of AF patients assigned to the AF cohort by the algorithm had a secondary care diagnosis with no record of AF in primary care. These additional patients did not substantially alter algorithm performance. The additional detection of previously undiagnosed AF patients in secondary care highlights unexpected potential utility of this ML algorithm.

Baseline HPV prevalence in rectal swabs from men attending a sexual health clinic in Scotland: assessing the potential impact of a selective HPV vaccination programme for men who have sex with men.

OBJECTIVES: A human papillomavirus (HPV) vaccination programme targeted towards men who have sex with men who are disproportionately affected by HPV anogenital infection and related disease was established in Scotland in July 2017. We aimed to establish a baseline HPV prevalence to assess the potential impact of the programme. METHODS: Residual rectal swabs taken in a sexual health clinic (n=1 248) were tested for the presence of HPV and HPV-type prevalence was collated and stratified by age. Prevalence of HPV types included in the quadrivalent and nonavalent vaccines was specifically assessed. RESULTS: 72.8% (95% CI 70.2% to 75.3%) of swabs were positive for HPV with 59.1% (95% CI 56.3% to 61.9%) of samples positive for at least one high-risk type. A least one of HPV 6, 11, 16 and 18 was detected in approximately half of the swabs. HPV prevalence generally increased with age but did not significantly differ between older age groups. The presence of more than one HPV type increased with age and over half of samples had multiple types present. CONCLUSIONS: While HPV prevalence in this population is high, the potential impact of the vaccination programme is substantial given that 50% are not infected with a vaccine type. Defining a preimmunisation baseline in this group will be important for longitudinal monitoring of impact.