Risk calculator for incident atrial fibrillation across a range of prediction horizons.

BACKGROUND: The increasing burden of atrial fibrillation (AF) emphasizes the need to identify high-risk individuals for enrolment in clinical trials of AF screening and primary prevention. We aimed to develop prediction models to identify individuals at high-risk of AF across prediction horizons from 6-months to 10-years. METHODS: We used secondary-care linked primary care electronic health record data from individuals aged ≥30 years without known AF in the UK Clinical Practice Research Datalink-GOLD dataset between January 2, 1998 and November 30, 2018; randomly divided into derivation (80%) and validation (20%) datasets. Models were derived using logistic regression from known AF risk factors for incident AF in prediction periods of 6 months, 1-year, 2-years, 5-years, and 10-years. Performance was evaluated using in the validation dataset with bootstrap validation with 200 samples, and compared against the CHA2DS2-VASc and C2HEST scores. RESULTS: Of 2,081,139 individuals in the cohort (1,664,911 in the development dataset, 416,228 in the validation dataset), the mean age was 49.9 (SD 15.4), 50.7% were women, and 86.7% were white. New cases of AF were 7,386 (0.4%) within 6 months, 15,349 (0.7%) in 1 year, 38,487 (1.8%) in 5 years, and 79,997 (3.8%) by 10 years. Valvular heart disease and heart failure were the strongest predictors, and association of hypertension with AF increased at longer prediction horizons. The optimal risk models incorporated age, sex, ethnicity, and 8 comorbidities. The models demonstrated good-to-excellent discrimination and strong calibration across prediction horizons (AUROC, 95%CI, calibration slope: 6-months, 0.803, 0.789-0.821, 0.952; 1-year, 0.807, 0.794-0.819, 0.962; 2-years, 0.815, 0.807-0.823, 0.973; 5-years, 0.807, 0.803-0.812, 1.000; 10-years 0.780, 0.777-0.784, 1.010), and superior to the CHA2DS2-VASc and C2HEST scores. The models are available as a web-based FIND-AF calculator. CONCLUSIONS: The FIND-AF models demonstrate high discrimination and calibration across short- and long-term prediction horizons in 2 million individuals. Their utility to inform trial enrolment and clinical decisions for AF screening and primary prevention requires further study.

Temporal trends of cause-specific mortality after diagnosis of atrial fibrillation.

BACKGROUND AND AIMS: Reports of outcomes after atrial fibrillation (AF) diagnosis are conflicting. The aim of this study was to investigate mortality and hospitalization rates following AF diagnosis over time, by cause and by patient features. METHODS: Individuals aged ≥16 years with a first diagnosis of AF were identified from the UK Clinical Practice Research Datalink-GOLD dataset from 1 January 2001, to 31 December 2017. The primary outcomes were all-cause and cause-specific mortality and hospitalization at 1 year following diagnosis. Poisson regression was used to calculate rate ratios (RRs) for mortality and incidence RRs (IRRs) for hospitalization and 95% confidence intervals (CIs) comparing 2001/02 and 2016/17, adjusted for age, sex, region, socio-economic status, and 18 major comorbidities. RESULTS: Of 72 412 participants, mean (standard deviation) age was 75.6 (12.4) years, and 44 762 (61.8%) had ≥3 comorbidities. All-cause mortality declined (RR 2016/17 vs. 2001/02 0.72; 95% CI 0.65-0.80), with large declines for cardiovascular (RR 0.46; 95% CI 0.37-0.58) and cerebrovascular mortality (RR 0.41; 95% CI 0.29-0.60) but not for non-cardio/cerebrovascular causes of death (RR 0.91; 95% CI 0.80-1.04). In 2016/17, deaths caused from dementia (67, 8.0%), outstripped deaths from acute myocardial infarction, heart failure, and acute stroke combined (56, 6.7%, P < .001). Overall hospitalization rates increased (IRR 2016/17 vs. 2001/02 1.17; 95% CI, 1.13-1.22), especially for non-cardio/cerebrovascular causes (IRR 1.42; 95% CI 1.39-1.45). Older, more deprived, and hospital-diagnosed AF patients experienced higher event rates. CONCLUSIONS: After AF diagnosis, cardio/cerebrovascular mortality and hospitalization has declined, whilst hospitalization for non-cardio/cerebrovascular disease has increased.

A 10 year study of hospitalized atrial fibrillation-related stroke in England and its association with uptake of oral anticoagulation.

Aims: To determine whether changing patterns of anticoagulant use in atrial fibrillation (AF) have impacted on stroke rates in England. Methods and results: English national databases, 2006-2016, were interrogated to assess stroke admissions and oral anticoagulant use. The number of patients with known AF increased linearly from 692 054 to 983 254 (prevalence 1.29% vs. 1.71%). Hospital episodes of AF-related stroke/100 000 AF patients increased from 80/week in 2006 to 98/week in 2011 and declined to 86/week in 2016 (2006-2011 difference 18.0, 95% confidence interval (CI) 17.9-18.1, 2011-2016 difference -12.0, 95% CI -12.1 to -11.9). Anticoagulant use amongst patients with CHA2DS2-VASc ≥2 increased from 48.0% to 78.6% and anti-platelet use declined from 42.9% to 16.1%; the greatest rate of change occurred in the second 5 year period (for anticoagulants 2006-2011 difference 4.8%, 95% CI 4.5-5.1%, 2011-2016 difference 25.8%, 95% CI 25.5-26.1%). After adjustment for AF prevalence, a 1% increase in anticoagulant use was associated with a 0.8% decrease in the weekly rate of AF-related stroke (incidence rate ratio 0.992, 95% CI 0.989-0.994). Had the use of anticoagulants remained at 2009 levels, 4068 (95% CI 4046-4089) more strokes would have been predicted in 2015/2016. Conclusion: Between 2006 and 2016, AF prevalence and anticoagulant use in England increased. From 2011, hospitalized AF-related stroke rates declined and were significantly associated with increased anticoagulant uptake.

Risk of atrial fibrillation and association with other diseases: protocol of the derivation and international external validation of a prediction model using nationwide population-based electronic health records.

INTRODUCTION: Atrial fibrillation (AF) is a major public health issue and there is rationale for the early diagnosis of AF before the first complication occurs. Previous AF screening research is limited by low yields of new cases and strokes prevented in the screened populations. For AF screening to be clinically and cost-effective, the efficiency of identification of newly diagnosed AF needs to be improved and the intervention offered may have to extend beyond oral anticoagulation for stroke prophylaxis. Previous prediction models for incident AF have been limited by their data sources and methodologies. METHODS AND ANALYSIS: We will investigate the application of random forest and multivariable logistic regression to predict incident AF within a 6-month prediction horizon, that is, a time-window consistent with conducting investigation for AF. The Clinical Practice Research Datalink (CPRD)-GOLD dataset will be used for derivation, and the Clalit Health Services (CHS) dataset will be used for international external geographical validation. Analyses will include metrics of prediction performance and clinical utility. We will create Kaplan-Meier plots for individuals identified as higher and lower predicted risk of AF and derive the cumulative incidence rate for non-AF cardio-renal-metabolic diseases and death over the longer term to establish how predicted AF risk is associated with a range of new non-AF disease states. ETHICS AND DISSEMINATION: Permission for CPRD-GOLD was obtained from CPRD (ref no: 19_076). The CPRD ethical approval committee approved the study. CHS Helsinki committee approval 21-0169 and data usage committee approval 901. The results will be submitted as a research paper for publication to a peer-reviewed journal and presented at peer-reviewed conferences. TRIAL REGISTRATION NUMBER: A systematic review to guide the overall project was registered on PROSPERO (registration number CRD42021245093). The study was registered on ClinicalTrials.gov (NCT05837364).

Clinical and budget impacts of changes in oral anticoagulation prescribing for atrial fibrillation.

OBJECTIVE: To assess temporal clinical and budget impacts of changes in atrial fibrillation (AF)-related prescribing in England. METHODS: Data on AF prevalence, AF-related stroke incidence and prescribing for all National Health Service general practices, hospitals and registered patients with hospitalised AF-related stroke in England were obtained from national databases. Stroke care costs were based on published data. We compared changes in oral anticoagulation prescribing (warfarin or direct oral anticoagulants (DOACs)), incidence of hospitalised AF-related stroke, and associated overall and per-patient costs in the periods January 2011-June 2014 and July 2014-December 2017. RESULTS: Between 2011-2014 and 2014-2017, recipients of oral anticoagulation for AF increased by 86.5% from 1 381 170 to 2 575 669. The number of patients prescribed warfarin grew by 16.1% from 1 313 544 to 1 525 674 and those taking DOACs by 1452.7% from 67 626 to 1 049 995. Prescribed items increased by 5.9% for warfarin (95% CI 2.9% to 8.9%) but by 2004.8% for DOACs (95% CI 1848.8% to 2160.7%). Oral anticoagulation prescription cost rose overall by 781.2%, from £87 313 310 to £769 444 028, (£733,466,204 with warfarin monitoring) and per patient by 50.7%, from £293 to £442, giving an incremental cost of £149. Nevertheless, as AF-related stroke incidence fell by 11.3% (95% CI -11.5% to -11.1%) from 86 467 in 2011-2014 to 76 730 in 2014-2017 with adjustment for AF prevalence, the overall per-patient cost reduced from £1129 to £840, giving an incremental per-patient saving of £289. CONCLUSIONS: Despite nearly one million additional DOAC prescriptions and substantial associated spending in the latter part of this study, the decline in AF-related stroke led to incremental savings at the national level.

Implantable cardioverter-defibrillator therapy in adult patients with tetralogy of Fallot.

AIMS: Adults with repaired tetralogy of Fallot (TOF) are at risk of sudden cardiac death (SCD). ESC and AHA guidelines suggest the use of implantable cardioverter defibrillators (ICDs) to protect from this. Few data are available on the benefits of these devices in this population, and there are no randomized studies. METHODS AND RESULTS: We analysed outcomes with respect to death, ICD therapy delivery, and complications for 20 patients with repaired TOF and 39 dilated cardiomyopathy (DCM) patients followed up at a UK teaching hospital. All TOF patients had clinical ventricular tachycardia (VT), electrophysiological study-inducible VT, or previous arrest due to tachyarrhythmia and received dual-chamber devices with individualized atrial detection algorithms. Tetralogy of Fallot patients were younger than DCM patients, but follow-up duration was not different between the groups. Tetralogy of Fallot patients were more likely to have experienced oversensing (45 vs. 13%; P < 0.02), inappropriate anti-tachycardia pacing delivery (20 vs. 2%; P < 0.05), and inappropriate cardioversion (25 vs. 4%; P = 0.06) than DCM patients and less likely to receive appropriate therapies than DCM patients. The death rate in TOF patients was significantly lower than that in DCM patients (5 vs. 21%; P < 0.05). CONCLUSION: Tetralogy of Fallot patients have a higher risk of inappropriate therapies and other complications yet a lower incidence of appropriate therapies from their ICD than DCM patients. Further research into identification of factors predicting SCD in TOF and the benefits of ICD implantation is essential given the potential complications of ICD implantation in young congenital heart disease patients.