Screening For Atrial Fibrillation Research Articles

Design of the Dutch multicentre study on opportunistic screening of geriatric patients for atrial fibrillation using asmartphone PPG app: the Dutch-GERAF study.

Screening of high-risk patients is advocated to achieve early detection and treatment of clinical atrial fibrillation (AF). The Dutch-GERAF study will address two major issues. Firstly, the effectiveness and feasibility of an opportunistic screening strategy for clinical AF will be assessed in frail older patients and, secondly, observational data will be gathered regarding the efficacy and safety of oral anticoagulation (OAC). This is amulticentre study on opportunistic screening of geriatric patients for clinical AF using asmartphone photoplethysmography (PPG) application. Inclusion criteria are age ≥ 65years and the ability to perform at least three PPG recordings within 6months. Exclusion criteria are the presence of acardiac implantable device, advanced dementia or asevere tremor. The PPG application records patients' pulse at their fingertip and determines the likelihood of clinical AF. If clinical AF is suspected after apositive PPG recording, aconfirmatory electrocardiogram is performed. Patients undergo acomprehensive geriatric assessment and afrailty index is calculated. Risk scores for major bleeding (MB) are applied. Standard laboratory testing and additional laboratory analyses are performed to determine the ABC-bleeding risk score. Follow-up data will be collected at 6months, 12months and 3years on the incidence of AF, MB, hospitalisation, stroke, progression of cognitive disorders and mortality. The Dutch-GERAF study will focus on frail older patients, who are underrepresented in randomised clinical trials. It will provide insight into the effectiveness of screening for clinical AF and the efficacy and safety of OAC in this high-risk population. NCT05337202.

Deep learning evaluation of echocardiograms to identify occult atrial fibrillation

Atrial fibrillation (AF) often escapes detection, given its frequent paroxysmal and asymptomatic presentation. Deep learning of transthoracic echocardiograms (TTEs), which have structural information, could help identify occult AF. We created a two-stage deep learning algorithm using a video-based convolutional neural network model that (1) distinguished whether TTEs were in sinus rhythm or AF and then (2) predicted which of the TTEs in sinus rhythm were in patients who had experienced AF within 90 days. Our model, trained on 111,319 TTE videos, distinguished TTEs in AF from those in sinus rhythm with high accuracy in a held-out test cohort (AUC 0.96 (0.95–0.96), AUPRC 0.91 (0.90–0.92)). Among TTEs in sinus rhythm, the model predicted the presence of concurrent paroxysmal AF (AUC 0.74 (0.71–0.77), AUPRC 0.19 (0.16–0.23)). Model discrimination remained similar in an external cohort of 10,203 TTEs (AUC of 0.69 (0.67–0.70), AUPRC 0.34 (0.31–0.36)). Performance held across patients who were women (AUC 0.76 (0.72–0.81)), older than 65 years (0.73 (0.69–0.76)), or had a CHA2DS2VASc ≥2 (0.73 (0.79–0.77)). The model performed better than using clinical risk factors (AUC 0.64 (0.62–0.67)), TTE measurements (0.64 (0.62–0.67)), left atrial size (0.63 (0.62–0.64)), or CHA2DS2VASc (0.61 (0.60–0.62)). An ensemble model in a cohort subset combining the TTE model with an electrocardiogram (ECGs) deep learning model performed better than using the ECG model alone (AUC 0.81 vs. 0.79, p = 0.01). Deep learning using TTEs can predict patients with active or occult AF and could be used for opportunistic AF screening that could lead to earlier treatment.

Atrial Fibrillation Screening During Routine Automated Office, Home, and Ambulatory Blood Pressure Measurement: A Diagnostic Test Accuracy Systematic Review and Meta-Analysis.

Atrial fibrillation (AF) is often asymptomatic and undiagnosed. As AF and hypertension often coexist, opportunistic AF detection during routine automated blood pressure (BP) measurement appears to be an attractive screening method. A systematic literature search was conducted to identify studies assessing the diagnostic test accuracy of office, home, or 24-hour ambulatory BP measuring devices with AF detection algorithms versus reference electrocardiography. Analyses were performed per participant (AF status based on several BP readings; most office/home devices) or per reading (AF status based on individual readings; all ambulatory devices). A meta-analysis stratified by device type (office/home/ambulatory) was conducted to calculate pooled measures of diagnostic accuracy. Sensitivity/meta-regression analyses were also performed. Among 3096 records initially retrieved, 23 diagnostic test accuracy studies were included. Data derived from 11 093 individuals (weighted age 69 years, males 56%, hypertensives 79%, diabetics 24%, and AF prevalence 17%) indicated a pooled sensitivity 0.97 (95% CI, 0.92-0.99), specificity 0.93 (95% CI, 0.90-0.95), and accuracy 0.93 (95% CI, 0.89-0.95), with generally consistent results using office, home, or ambulatory BP devices (slightly lower specificity with the latter). The positive and negative predictive values were 0.70 (95% CI, 0.60-0.80) and 0.99 (95% CI, 0.98-1.00), respectively. Sensitivity analyses indicated lower specificity in studies implementing reading versus participant analyses. Most studies presented a low risk of bias and minor applicability concerns. There is considerable and consistent evidence suggesting high diagnostic accuracy of AF detection algorithms implemented in automated BP monitors during routine BP measurements in and out of the office. AF diagnosis requires verification (electrocardiography) before treatment is administered.

Large variations in atrial fibrillation screening practice after ischemic stroke and transient ischemic attack in Sweden: a survey study

BackgroundAtrial fibrillation (AF) screening after ischemic stroke or transient ischemic attack (TIA) is given high priority in clinical guidelines. However, patient selection, electrocardiogram (ECG) modality and screening duration remains undecided and current recommendations vary.MethodsThe aim of this study was to investigate the clinical practice of AF screening after ischemic stroke or TIA at Swedish stroke units. In collaboration with the stakeholders of the Swedish Stroke Register (Riksstroke) a digital survey was drafted, then tested and revised by three stroke consultants. The survey consisted of 17 multiple choice/ free text questions and was sent by e-mail to the medical directors at all stroke units in Sweden.ResultsAll 72 stroke units in Sweden responded to the survey. Most stroke units reported that ≥ 75% of ischemic stroke (69/72 stroke units) or TIA patients (67/72 stroke units), without previously known AF, were screened for AF. Inpatient telemetry ECG was the method of first-choice in 81% of the units, but 7% reported lack of access. A variety of standard monitoring durations were used for inpatient telemetry ECG. The second most common choice was Holter ECG (17%), also with considerable variations in monitoring duration. Other AF screening modalities were used as a first-choice method (handheld and patch ECG) but less frequently.ConclusionsClinical practice for AF screening after ischemic stroke or TIA differed between Swedish stroke units, both in choice of AF screening methods as well as in monitoring durations. There is an urgent need for evidence and evidence-based recommendations in this field.Trial registrationNot applicable.

Wearables in cardiology—Knowledge from current digital atrial fibrillation screening and management studies

Wearables in cardiology—Knowledge from current digital atrial fibrillation screening and management studies

Screening for Atrial Fibrillation by Digital Health Technology in Older People in Homecare Settings: A Feasibility Trial.

Users of homecare services are often excluded from clinical trials due to advanced age, multimorbidity, and frailty. Atrial fibrillation (AF) is a common and frequently undiagnosed arrhythmia in the elderly and is associated with severe mortality, morbidity, and healthcare costs. Timely identification prevents associated complications through evidence-based treatment. This study is aimed at assessing the feasibility of AF screening using new digital health technology in older people in a homecare setting. Users of homecare services ≥ 65 years old with at least one additional risk factor for stroke in two Norwegian municipalities were assessed for study participation by nurses. Participants performed a continuous prolonged ECG recording using a patch ECG device (ECG247 Smart Heart Sensor). A total of 144 individuals were assessed for study participation, but only 18 (13%) were included. The main reasons for noninclusion were known AF and/or anticoagulation therapy (25%), severe cognitive impairment (26%), and lack of willingness to participate (36%). The mean age of participants performing the ECG test was 81 (SD ± 7) years, and 9 (50%) were women. All ECG tests were interpretable; the mean ECG monitoring time was 104 hours (IQR 34-338 hours). AF was detected in one individual (6%). This feasibility study highlights the challenges of enrolling older people receiving homecare services in clinical trials. However, all included participants performed an interpretable and prolonged continuous ECG recording with a digital ECG patch device. This trial is registered with NCT04700865.

Biomarkers for predicting atrial fibrillation: An explorative sub-analysis of the randomised SCREEN-AF trial

Background Atrial fibrillation (AF) is a common treatable risk factor for stroke. Screening for paroxysmal AF in general practice is difficult, but biomarkers might help improve screening strategies. Objectives We investigated six blood biomarkers for predicting paroxysmal AF in general practice. Methods This was a pre-specified sub-study of the SCREEN-AF RCT done in Germany. Between 12/2017-03/2019, we enrolled ambulatory individuals aged 75 years or older with a history of hypertension but without known AF. Participants in the intervention group received active AF screening with a wearable patch, continuous ECG monitoring for 2x2 weeks and usual care in the control group. The primary endpoint was ECG-confirmed AF within six months after randomisation. High-sensitive Troponin I (hsTnI), brain natriuretic peptide (BNP), N-terminal pro-B-type natriuretic peptide (NT-pro BNP), N-terminal pro atrial natriuretic peptide (NT-ANP), mid-regional pro atrial natriuretic peptide (MR-pro ANP) and C-reactive protein (CRP) plasma levels were investigated at randomisation for predicting AF within six months after randomisation. Results Blood samples were available for 291 of 301 (96.7%) participants, including 8 with AF (3%). Five biomarkers showed higher median results in AF-patients: BNP 78 vs. 41 ng/L (p = 0.012), NT-pro BNP 273 vs. 186 ng/L (p = 0.029), NT-proANP 4.4 vs. 3.5 nmol/L (p = 0.027), MR-pro ANP 164 vs. 125 pmol/L (p = 0.016) and hsTnI 7.4 vs. 3.9 ng/L (p = 0.012). CRP levels were not different between groups (2.8 vs 1.9 mg/L, p = 0.1706). Conclusion Natriuretic peptide levels and hsTnI are higher in patients with AF than without and may help select patients for AF screening, but larger trials are needed.

Lead-Specific Performance for Atrial Fibrillation Detection in Convolutional Neural Network Models Using Sinus Rhythm Electrocardiography.

Background: We developed a convolutional neural network (CNN) model to detect atrial fibrillation (AF) using the sinus rhythm ECG (SR-ECG). However, the diagnostic performance of the CNN model based on different ECG leads remains unclear. Methods and Results: In this retrospective analysis of a single-center, prospective cohort study, we identified 616 AF cases and 3,412 SR cases for the modeling dataset among new patients (n=19,170). The modeling dataset included SR-ECGs obtained within 31 days from AF-ECGs in AF cases and SR cases with follow-up ≥1,095 days. We evaluated the CNN model's performance for AF detection using 8-lead (I, II, and V1-6), single-lead, and double-lead ECGs through 5-fold cross-validation. The CNN model achieved an area under the curve (AUC) of 0.872 (95% confidence interval (CI): 0.856-0.888) and an odds ratio of 15.24 (95% CI: 12.42-18.72) for AF detection using the eight-lead ECG. Among the single-lead and double-lead ECGs, the double-lead ECG using leads I and V1 yielded an AUC of 0.871 (95% CI: 0.856-0.886) with an odds ratio of 14.34 (95% CI: 11.64-17.67). Conclusions: We assessed the performance of a CNN model for detecting AF using eight-lead, single-lead, and double-lead SR-ECGs. The model's performance with a double-lead (I, V1) ECG was comparable to that of the 8-lead ECG, suggesting its potential as an alternative for AF screening using SR-ECG.

What Do We Really Know About the Effect of Prolonged Heart Rhythm Monitoring After Stroke?

The bulk of the current knowledge on atrial fibrillation (AF)-associated stroke risk and benefit of oral anticoagulation derives from studies on patients with clinically diagnosed AF. Subclinical AF (SCAF), defined as AF discovered during the interrogation of prolonged heart monitoring, is often asymptomatic and short-lasting, is associated with increased stroke risk compared with sinus rhythm, and may progress to clinical AF. Despite the extensive screening for and treatment of SCAF, especially in secondary stroke prevention, the net benefit of this practice is not established. Recent studies of SCAF have provided new insights: (1) SCAF is extremely common and may sometimes indicate physiological findings, (2) the stroke risk associated with SCAF is lower than that of clinically detected AF, and (3) any benefit on stroke risk may be countered by increased bleeding risk (no net benefit). How should we interpret the latest knowledge in the setting of poststroke AF screening and prevention?

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

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. 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. 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. 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.

[Screening for atrial fibrillation - what to do if the patient presents with atrial fibrillation on a smartwatch ECG?]

[Screening for atrial fibrillation - what to do if the patient presents with atrial fibrillation on a smartwatch ECG?]

Correlates and consequences of atrial fibrillation in a prospective study of 25 000 participants in the China Kadoorie Biobank

Abstract Aims The prevalence of atrial fibrillation (AF) is positively correlated with prior cardiovascular diseases (CVD) and CVD risk factors but is lower in Chinese than Europeans despite their higher burden of CVD. We examined the prevalence and prognosis of AF and other electrocardiogram (ECG) abnormalities in the China Kadoorie Biobank. Methods and results A random sample of 25 239 adults (mean age 59.5 years, 62% women) had a 12-lead ECG recorded and interpreted using a Mortara VERITAS™ algorithm in 2013–14. Participants were followed up for 5 years for incident stroke, ischaemic heart disease, heart failure (HF), and all CVD, overall and by CHA2DS2-VASc scores, age, sex, and area. Overall, 1.2% had AF, 13.6% had left ventricular hypertrophy (LVH), and 28.1% had ischaemia (two-thirds of AF cases also had ischaemia or LVH). The prevalence of AF increased with age, prior CVD, and levels of CHA₂DS₂-VASc scores (0.5%, 1.3%, 2.1%, 2.9%, and 4.4% for scores <2, 2, 3, 4, and ≥5, respectively). Atrial fibrillation was associated with two-fold higher hazard ratios (HR) for CVD (2.15; 95% CI, 1.71–2.69) and stroke (1.88; 1.44–2.47) and a four-fold higher HR for HF (3.79; 2.21–6.49). The 5-year cumulative incidence of CVD was comparable for AF, prior CVD, and CHA₂DS₂-VASc scores ≥ 2 (36.7% vs. 36.2% vs. 37.7%, respectively) but was two-fold greater than for ischaemia (19.4%), LVH (18.0%), or normal ECG (14.1%), respectively. Conclusion The findings highlight the importance of screening for AF together with estimation of CHA₂DS₂-VASc scores for prevention of CVD in Chinese adults.

Targeted screening of atrial fibrillation using automated blood pressure measurement device with atrial fibrillation detection function, in patients with type 2 diabetes mellitus in primary care setting

ObjectiveThe prevalence of atrial fibrillation (AF) in type 2 diabetes mellitus (DM) patients under primary care in Hong Kong was yet to be explored. We aimed to evaluate the prevalence of AF in patients with DM so as to provide evidence-based recommendations to incorporate AF screening as a component in regular diabetic risk and complication assessment. The performance of automated BP machine Microlife WatchBP Office AFIB as a screening tool for the detection of AF was also evaluated.MethodThis was a cross-sectional study. Patients with type 2 DM who attended the regular diabetic risk and complication assessment in the participating clinics from 24 August 2021 to 27 January 2022 were recruited. Blood pressure measurement by Microlife WatchBP Office AFIB and 12-lead ECGs were performed for AF screening.ResultsAmong 2015 DM patients in primary care, the prevalence of AF was found to be 1.9% (95% confidence interval [CI] 1.3–2.6). The prevalence of AF increased with age, from 0.5% in patients aged < 65 years, to 2.2% in patients aged 65–74 years and 4.3% in patients aged ≥ 75 years. The sensitivity and specificity of Microlife WatchBP Office AFIB to detect AF were 80% (95% Cl 61.8–92.3) and 97.9%. (95% CI 97.3–98.5), respectively. The positive and negative predictive values were 32.8% (95% CI 21.9–45.1) and 99.7% (95% CI 99.5–99.9) respectively.ConclusionsAF screening with the use of Microlife WatchBP Office AFIB is a simple procedure and can be considered as a standard assessment in the regular comprehensive diabetic risk and complication assessment in primary care setting.

The feasibility of population screening for paroxysmal atrial fibrillation using hand-held electrocardiogram devices.

There are few data on the feasibility of population screening for paroxysmal atrial fibrillation (AF) using hand-held electrocardiogram (ECG) devices outside a specialist setting or in people over the age of 75. We investigated the feasibility of screening when conducted without face-to-face contact ('remote') or via in-person appointments in primary care and explored impact of age on screening outcomes. People aged ≥65 years from 13 general practices in England participated in screening during 2019-20. This involved attending a practice nurse appointment (10 practices) or receiving an ECG device by post (three practices). Participants were asked to use a hand-held ECG for 1-4 weeks. Screening outcomes included uptake, quality of ECGs, AF detection rates, and uptake of anticoagulation if AF was detected. Screening was carried out by 2141 (87.5%) of people invited to practice nurse-led screening and by 288 (90.0%) invited to remote screening. At least 56 interpretable ECGs were provided by 98.0% of participants who participated for 3 weeks, with no significant differences by setting or age, except people aged 85 or over (91.1%). Overall, 2.6% (64/2429) screened participants had AF, with detection rising with age (9.2% in people aged 85 or over). A total of 53/64 (82.8%) people with AF commenced anticoagulation. Uptake of anticoagulation did not vary by age. Population screening for paroxysmal AF is feasible in general practice and without face-to-face contact for all ages over 64 years, including people aged 85 and over.

Supermarket/hypermarket opportunistic screening for atrial fibrillation (SHOPS-AF) using sensors embedded in the handles of supermarket trolleys: A feasibility study

BackgroundAtrial fibrillation (AF) increases the risk of death, stroke, heart failure, cognitive decline, and healthcare costs but is often asymptomatic and undiagnosed. There is currently no national screening programme for AF. The advent of validated hand-held devices allows AF to be detected in non-healthcare settings, enabling screening to be undertaken within the community. Method and ResultsIn this novel observational study, we embedded a MyDiagnostick single lead ECG sensor into the handles of shopping trolleys in four supermarkets in the Northwest of England: 2155 participants were recruited. Of these, 231 participants either activated the sensor or had an irregular pulse, suggesting AF. Some participants agreed to use the sensor but refused to provide their contact details, or consent to pulse assessment. In addition, some data were missing, resulting in 203 participants being included in the final analyses. Fifty-nine participants (mean age 73.6 years, 43% female) were confirmed or suspected of having AF; 20 were known to have AF and 39 were previously undiagnosed. There was no evidence of AF in 115 participants and the remaining 46 recordings were non-diagnostic, mainly due to artefact. Men and older participants were significantly more likely to have newly diagnosed AF. Due to the number of non-diagnostic ECGs (n=46), we completed three levels of analyses, excluding all non-diagnostic ECGs, assuming all non-diagnostic ECGs were masking AF, and assuming all non-diagnostic ECGs were not AF. Based on the results of the three analyses, the sensor's sensitivity (95% CI) ranged from 0.70 - 0.93; specificity from 0.15 - 0.97; positive predictive values (PPV) and negative predictive values (NPV) ranged from 0.24 - 0.56 and 0.55-1.00, respectively. These values should be interpreted with caution, as the ideal reference standard on 1934 participants was imperfect. ConclusionThe study demonstrates that the public will engage with AF screening undertaken as part of their daily routines using hand-held devices. Sensors can play a key role in identifying asymptomatic patients in this way, but the technology must be further developed to reduce the quantity of non-diagnostic ECGs.

The ABC-Stroke Risk Score and Effects of Atrial Fibrillation Screening on Stroke Prevention: Results From the Randomized LOOP Study.

The ABC-stroke score is a risk scheme for prediction of stroke or systemic embolism (SE) in atrial fibrillation (AF). This study sought to examine whether the score could be useful in predicting stroke in AF-naïve individuals and risk stratifying for AF screening. The LOOP (Atrial Fibrillation Detected by Continuous ECG Monitoring Using Implantable Loop Recorder to Prevent Stroke in High-Risk Individuals) study randomized 6004 AF-naïve individuals aged 70 to 90 years with stroke risk factors to either screening with an implantable loop recorder and anticoagulation upon detection of new-onset AF episodes ≥6 minutes, or usual care. A total of 5781 participants had available ABC-stroke score at baseline and were included in this secondary analysis: 4170 (72.1%) with an estimated stroke/SE risk ≤1%/year versus 1611 (27.9%) with an estimated stroke/SE risk >1%/year. Having an annual ABC-stroke risk >1% was associated with stroke/SE, stroke/SE/cardiovascular death, and all-cause death (hazard ratio, 1.82 [95% CI, 1.44-2.21], 2.17 [95% CI, 1.80-2.62], and 2.19 [95% CI, 1.87-2.56], respectively). For screening with implantable loop recorder versus usual care, no significant reduction in these study outcomes was obtained in any ABC-stroke risk groups (P>0.0500 for all), with no signal toward interaction (Pinteraction>0.2500 for all). Similar findings were yielded when assessing theABC-stroke score as a continuous variable. In an elderly, AF-naïve population with additional stroke risk factors, a higher ABC-stroke score could identify individuals with increased stroke risk. However, this risk score may not be useful in pinpointing those more likely to benefit from AF screening and subsequent preventive treatment. These findings should be considered as hypothesis generating and warrant further study. URL: https://www.clinicaltrials.gov; unique identifier: NCT02036450.

Incidental Arrhythmias During Atrial Fibrillation Screening With Repeat 7-Day Holter ECGs in a Hospital-Based Patient Population.

Screening for atrial fibrillation (AF) may reveal incidental arrhythmias of relevance. The aim of this study was to describe incidental arrhythmias detected during screening for AF in the STAR-FIB (Predicting SilenT AtRial FIBrillation in Patients at High Thrombembolic Risk) cohort study. In the STAR-FIB cohort study, we screened hospitalized patients for AF with 3 repeat 7-day Holter ECGs. We analyzed all Holter ECGs for the presence of the following incidental arrhythmias: (1) sinus node dysfunction, defined as sinus pause of ≥3 seconds' duration; (2) second-degree (including Wenckebach) or higher-degree atrioventricular block (AVB); (3) sustained supraventricular tachycardia of ≥30 seconds' duration; and (4) sustained ventricular tachycardia of ≥30 seconds' duration. We furthermore report treatment decisions because of incidental arrhythmias. A total of 2077 Holter ECGs were performed in 794 patients (mean age, 74.7 years; 49% women), resulting in a mean cumulative duration of analyzable ECG signal of 414±136 hours/patient. We found incidental arrhythmias in 94 patients (11.8%). Among these were sinus node dysfunction in 14 patients (1.8%), AVB in 41 (5.2%), supraventricular tachycardia in 42 (5.3%), and ventricular tachycardia in 2 (0.3%). Second-degree AVB was found in 23 patients (2.9%), 2:1 AVB in 10 (1.3%), and complete AVB in 8 (1%). Subsequently, 8 patients underwent pacemaker implantation, 1 for sinus node dysfunction (post-AF conversion pause of 9 seconds) and 7 for advanced AVB. One patient had an implantable cardioverter-defibrillator implanted for syncopal ventricular tachycardia. Incidental arrhythmias were frequently detected during screening for AF in the STAR-FIB study and resulted in device therapy in 1.1% of our cohort patients.

Diagnosis and management of atrial fibrillation in primary care: a case study

This critically reflective case study will look at a 65-year-old male presenting with dyspnoea and an incidental diagnosis of atrial fibrillation (AF) in a primary care setting. The article critically analyses the diagnosis and management of the patient, considers potential differential diagnoses, current guidelines, and areas for service improvement. The author, a trainee advanced clinical practitioner (ACP) prescriber with a paramedic background, discusses the complexity of managing AF and the need for collaboration with a general practitioner. AF is a common cardiac arrhythmia associated with a significantly increased risk of stroke. The primary focus of AF management is stroke prevention. This article delves into the pathophysiology of AF, discussing its various causes and classifications, emphasising the role of left atrial appendage (LAA) in stroke risk. The limitations of AF screening methods, especially for paroxysmal AF, are also discussed. Recent advancements in opportunistic screening, including the use of artificial intelligence (AI) and smartwatches, show promise but require further research and validation. This article explores stroke risk assessment tools like CHA2DS2VASc and ATRIA, bleeding risk assessment using HAS-BLED and ORBIT scores, as well as rhythm control in newly diagnosed AF cases. Finally, the importance of lifestyle modifications and regular patient follow-up are underscored. AF diagnosis and management are multifaceted, involving stroke prevention, rate or rhythm control, and lifestyle modifications. Technological advancements hold promise in improving early AF detection. Collaborative efforts between healthcare providers and adherence to current guidelines are crucial in achieving optimal patient outcomes, while future practice may benefit from enhanced diagnostic screening and treatment options as further research unfolds.

Wearable dynamic electrocardiogram monitor-based screening for atrial fibrillation in the community-dwelling elderly population

BackgroundAtrial fibrillation (AF) is a major public health problem with high rates of morbidity, disability and mortality, especially in the elderly population. This study explored the diagnosis and treatment status of AF in adults aged ≥65 years in the community through wearable dynamic electrocardiogram (ECG) monitoring. MethodsWe conducted a cross-sectional study in 4 random communities within the Qingpu district of Shanghai, China. Between January 1, 2020 and June 30, 2022, the ECGs of 3852 adults aged 65 years or older were examined through wearable dynamic ECG monitoring. Data from 3839 participants were ultimately analyzed. Multivariate logistic regression was used to determine the independent predictors of AF. ResultsWearable dynamic ECG monitoring detected AF in 360 elderly people, 78 of whom were diagnosed with AF for the first time. Multivariate logistic regression analysis revealed that snoring, renal dysfunction, coronary heart disease and high CHA2DS2-VASc score were independent risk factors for AF. Among patients with unknown AF, 68 (87.20 %) met the criteria for anticoagulant therapy based on the CHA2DS2-VASc score. Only 4 (5.88 %) patients were taking anticoagulants. Of the patients with a clear history of AF, 249 (84.98 %) needed an anticoagulant strategy, but only 18 (7.23 %) took oral anticoagulants. ConclusionMany elderly people have silent AF, and wearable dynamic ECG monitoring can be used to screen for AF effectively.

Prevalence of frequent premature ventricular contractions and nonsustained ventricular tachycardia in older women screened for atrial fibrillation in the Women’s Health Initiative

BackgroundFrequent premature ventricular contractions (PVCs) and nonsustained ventricular tachycardia (NSVT) have been associated with cardiovascular disease and mortality. Their prevalence, especially in ambulatory populations, is understudied and limited by few female participants and the use of short-duration (24- to 48-hour) monitoring. ObjectiveThe objective of this study was to report the prevalence of frequent PVCs and NSVT in a community-based population of women likely to undergo electrocardiogram (ECG) screening by sequential patch monitoring. MethodsParticipants from the Women’s Health Initiative Strong and Healthy (WHISH) trial with no history of atrial fibrillation (AF) but 5-year predicted risk of incident AF ≥5% by CHARGE-AF score were randomly selected to undergo screening with 7-day ECG patch monitors at baseline, 6 months, and 12 months. Recordings were reviewed for PVCs and NSVT (>5 beats); data were analyzed with multivariate regression models. ResultsThere were 1067 participants who underwent ECG screening at baseline, 866 at 6 months, and 777 at 12 months. Frequent PVCs were found on at least 1 patch from 4.3% of participants, and 1 or more episodes of NSVT were found in 12 (1.1%) women. PVC frequency directly correlated with CHARGE-AF score and NSVT on any patch. Detection of frequent PVCs increased with sequential monitoring. ConclusionIn postmenopausal women at high risk for AF, frequent PVCs were relatively common (4.3%) and correlated with higher CHARGE-AF score. As strategies for AF screening continue to evolve, particularly in those individuals at high risk of AF, the prevalence of incidental ventricular arrhythmias is an important benchmark to guide clinical decision-making.