Stroke as the First Manifestation of Atrial Fibrillation

Association Between the Timing of Atrial Fibrillation Detection and Functional Outcome Following Mechanical Thrombectomy

BACKGROUND

Atrial fibrillation detected after stroke (AFDAS) refers to the identification of newly diagnosed atrial fibrillation (AF) following an ischemic stroke in patients without known AF (KAF). The objective of this study was to compare the functional outcomes of patients diagnosed with AFDAS and those with KAF who underwent mechanical thrombectomy.

METHODS AND RESULTS

We conducted a retrospective analysis of patients who underwent mechanical thrombectomy and with either new AF diagnosed during hospitalization or KAF. We compared the baseline characteristics, clinical, and procedure-related variables between those with AFDAS and KAF. The primary outcome was the achievement of functional independence, defined as a modified Rankin Scale score of 0 to 2, at 3 months after stroke. Of the 252 patients, 101 (40.1%) were classified into the AFDAS group. The KAF group exhibited a higher rate of stroke history compared with the AFDAS group (32.5% versus 13.9%; P=0.001). Tandem occlusion was more common in the KAF group (13.2% versus 5.9%), while M2 occlusion was more common in the AFDAS group (11.3% versus 20.8%). The proportion of patients who achieved functional independence was higher in the AFDAS group (37.7% versus 52.5%; P=0.029). Multivariable analysis showed that AFDAS was associated with a favorable functional outcome (odds ratio, 2.67 [95% CI, 1.39-5.14]; P=0.003).

CONCLUSIONS

AFDAS demonstrated a positive association with functional independence in patients with stroke who underwent mechanical thrombectomy and were finally diagnosed to have AF during hospitalization. The observed disparities in occlusion site, intractable thrombus, and history of previous stroke may have contributed to these findings.

Contemporary Advances in Cardiac Remote Monitoring: A Comprehensive, Updated Mini-Review

Over the past decade, remote monitoring (RM) has become an increasingly popular way to improve healthcare and health outcomes. Modern cardiac implantable electronic devices (CIEDs) are capable of recording an increasing amount of data related to CIED function, arrhythmias, physiological status and hemodynamic parameters, providing in-depth and updated information on patient cardiovascular function. The extensive use of RM for patients with CIED allows for early diagnosis and rapid assessment of relevant issues, both clinical and technical, as well as replacing outpatient follow-up improving overall management without compromise safety. This approach is recommended by current guidelines for all eligible patients affected by different chronic cardiac conditions including either brady- and tachy-arrhythmias and heart failure. Beyond to clinical advantages, RM has demonstrated cost-effectiveness and is associated with elevated levels of patient satisfaction. Future perspectives include improving security, interoperability and diagnostic power as well as to engage patients with digital health technology. This review aims to update existing data concerning clinical outcomes in patients managed with RM in the wide spectrum of cardiac arrhythmias and Hear Failure (HF), disclosing also about safety, effectiveness, patient satisfaction and cost-saving.

Outcomes of mechanical thrombectomy in acute stroke patients with atrial fibrillation detected after stroke versus known atrial fibrillation

We aim to compare the outcomes in patients with atrial fibrillation detected after stroke (AFDAS) and their counterparts with known AF (KAF) presenting with large vessel occlusion (LVO) treated with mechanical thrombectomy (MT). This observational, prospective study included consecutive patients with acute LVO ischemic stroke of the anterior circulation with AFDAS, KAF and without AF. The primary study outcome was functional independence at 90 days after stroke. The secondary study outcomes were variation of the NIHSS score at 24 h, rate of successful reperfusion, death at 90 days and rate of immediate complications post-procedure. Overall, our cohort included 518 patients with acute ischemic stroke and LVO treated with MT, with 289 (56.8%) without a diagnosis of AF; 107 (21%) with AFDAS; 122 (22.2%) with KAF. There was no significant difference in terms of functional independence at 90 days after stroke between the three groups. Regarding the secondary study outcome, the rate of symptomatic intracranial haemorrhage (sICH) and/or parenchymal hematoma (PH) were significantly higher in the group of patients without AF (respectively, P = 0.030 and  < 0.010). Logistic regression analysis showed that the subtypes of AF were not statistically significantly associated with functional independence at 90 days after stroke and with the likelihood of any ICH. Our results suggest that the subtypes of AF are not associated with clinical and safety outcomes of MT in patients with acute stroke and LVO. Further studies are needed to confirm our findings.

Ischemic Stroke Temporally Associated With New-Onset Atrial Fibrillation: A Population-Based Registry-Linkage Study

BACKGROUND

Limited data exist on the temporal relationship between new-onset atrial fibrillation (AF) and ischemic stroke and its impact on patients' clinical characteristics and mortality.

METHODS

A population-based registry-linkage database includes all patients with new-onset AF in Finland from 2007 to 2018. Ischemic stroke temporally associated with AF (ISTAF) was defined as an ischemic stroke occurring within ±30 days from the first AF diagnosis. Clinical factors associated with ISTAF were studied with logistic regression and 90-day survival with Cox proportional hazards analysis.

RESULTS

Among 229 565 patients with new-onset AF (mean age, 72.7 years; 50% female), 204 774 (89.2%) experienced no ischemic stroke, 12 209 (5.3%) had past ischemic stroke >30 days before AF, and 12 582 (5.8%) had ISTAF. The annual proportion of ISTAF among patients with AF decreased from 6.0% to 4.8% from 2007 to 2018. Factors associated positively with ISTAF were higher age, lower education level, and alcohol use disorder, whereas vascular disease, heart failure, chronic kidney disease cancer, and psychiatric disorders were less probable with ISTAF. Compared with patients without ischemic stroke and those with past ischemic stroke, ISTAF was associated with ≈3-fold and 1.5-fold risks of death (adjusted hazard ratios, 2.90 [95% CI, 2.76-3.04] and 1.47 [95% CI, 1.39-1.57], respectively). The 90-day survival probability of patients with ISTAF increased from 0.79 (95% CI, 0.76-0.81) in 2007 to 0.89 (95% CI, 0.87-0.91) in 2018.

CONCLUSIONS

ISTAF depicts the prominent temporal clustering of ischemic strokes surrounding AF diagnosis. Despite having fewer comorbidities, patients with ISTAF had worse, albeit improving, survival than patients with a history of or no ischemic stroke.

REGISTRATION

URL: https://www.clinicaltrials.gov; Unique identifier: NCT04645537. URL: https://www.encepp.eu; Unique identifier: EUPAS29845.

Prediction of atrial fibrillation from at-home single-lead ECG signals without arrhythmias

Early identification of atrial fibrillation (AF) can reduce the risk of stroke, heart failure, and other serious cardiovascular outcomes. However, paroxysmal AF may not be detected even after a two-week continuous monitoring period. We developed a model to quantify the risk of near-term AF in a two-week period, based on AF-free ECG intervals of up to 24 h from 459,889 patch-based ambulatory single-lead ECG (modified lead II) recordings of up to 14 days. A deep learning model was used to integrate ECG morphology data with demographic and heart rhythm features toward AF prediction. Observing a 1-day AF-free ECG recording, the model with deep learning features produced the most accurate prediction of near-term AF with an area under the curve AUC = 0.80 (95% confidence interval, CI = 0.79-0.81), significantly improving discrimination compared to demographic metrics alone (AUC 0.67; CI = 0.66-0.68). Our model was able to predict incident AF over a two-week time frame with high discrimination, based on AF-free single-lead ECG recordings of various lengths. Application of the model may enable a digital strategy for improving diagnostic capture of AF by risk stratifying individuals with AF-negative ambulatory monitoring for prolonged or recurrent monitoring, potentially leading to more rapid initiation of treatment.

Construction and validation of a cuproptosis-related diagnostic gene signature for atrial fibrillation based on ensemble learning

BACKGROUND

Atrial fibrillation (AF) is the most common type of cardiac arrhythmia. Nonetheless, the accurate diagnosis of this condition continues to pose a challenge when relying on conventional diagnostic techniques. Cell death is a key factor in the pathogenesis of AF. Existing investigations suggest that cuproptosis may also contribute to AF. This investigation aimed to identify a novel diagnostic gene signature associated with cuproptosis for AF using ensemble learning methods and discover the connection between AF and cuproptosis.

RESULTS

Two genes connected to cuproptosis, including solute carrier family 31 member 1 (SLC31A1) and lipoic acid synthetase (LIAS), were selected by integration of random forests and eXtreme Gradient Boosting algorithms. Subsequently, a diagnostic model was constructed that includes the two genes for AF using the Light Gradient Boosting Machine (LightGBM) algorithm with good performance (the area under the curve value > 0.75). The microRNA-transcription factor-messenger RNA network revealed that homeobox A9 (HOXA9) and Tet methylcytosine dioxygenase 1 (TET1) could target SLC31A1 and LIAS in AF. Functional enrichment analysis indicated that cuproptosis might be connected to immunocyte activities. Immunocyte infiltration analysis using the CIBERSORT algorithm suggested a greater level of neutrophils in the AF group. According to the outcomes of Spearman's rank correlation analysis, there was a negative relation between SLC31A1 and resting dendritic cells and eosinophils. The study found a positive relationship between LIAS and eosinophils along with resting memory CD4+ T cells. Conversely, a negative correlation was detected between LIAS and CD8+ T cells and regulatory T cells.

CONCLUSIONS

This study successfully constructed a cuproptosis-related diagnostic model for AF based on the LightGBM algorithm and validated its diagnostic efficacy. Cuproptosis may be regulated by HOXA9 and TET1 in AF. Cuproptosis might interact with infiltrating immunocytes in AF.

Predicting ischemic stroke risk from atrial fibrillation based on multi-spectral fundus images using deep learning

Background

Ischemic stroke (IS) is one of the most common serious secondary diseases of atrial fibrillation (AF) within 1 year after its occurrence, both of which have manifestations of ischemia and hypoxia of the small vessels in the early phase of the condition. The fundus is a collection of capillaries, while the retina responds differently to light of different wavelengths. Predicting the risk of IS occurring secondary to AF, based on subtle differences in fundus images of different wavelengths, is yet to be explored. This study was conducted to predict the risk of IS occurring secondary to AF based on multi-spectrum fundus images using deep learning.

Methods

A total of 150 AF participants without suffering from IS within 1 year after discharge and 100 IS participants with persistent arrhythmia symptoms or a history of AF diagnosis in the last year (defined as patients who would develop IS within 1 year after AF, based on fundus pathological manifestations generally prior to symptoms of the brain) were recruited. Fundus images at 548, 605, and 810 nm wavelengths were collected. Three classical deep neural network (DNN) models (Inception V3, ResNet50, SE50) were trained. Sociodemographic and selected routine clinical data were obtained.

Results

The accuracy of all DNNs with the single-spectral or multi-spectral combination images at the three wavelengths as input reached above 78%. The IS detection performance of DNNs with 605 nm spectral images as input was relatively more stable than with the other wavelengths. The multi-spectral combination models acquired a higher area under the curve (AUC) scores than the single-spectral models.

Conclusions

The probability of IS secondary to AF could be predicted based on multi-spectrum fundus images using deep learning, and combinations of multi-spectrum images improved the performance of DNNs. Acquiring different spectral fundus images is advantageous for the early prevention of cardiovascular and cerebrovascular diseases. The method in this study is a beneficial preliminary and initiative exploration for diseases that are difficult to predict the onset time such as IS.

Remote photoplethysmography with consumer smartphone reveals temporal differences between glabrous and nonglabrous skin: Pilot in vivo study

Photoplethysmography (PPG) is a noninvasive optical technology, with applications including vital sign extraction and patient monitoring. The PPG acquisition skin type may be of importance. Skin is either nonglabrous (~90%) or glabrous (~10%). Clinical PPG collection is typically from glabrous (fingerpad), while proliferating wearables collecting PPG, which may perform critical functions like arrythmia detection, often acquire from atypical sites. Glabrous skin has significant differences from nonglabrous, including microcirculation, yet comparisons between their PPG signals have not been well reported. Using a smartphone-based remote/contactless PPG, a pilot dataset was collected from the hands (palmar/dorsal) of five healthy volunteers. The data shows statistically significant lead time (52 ± 36 ms) of glabrous over nonglabrous. Further, a trend of glabrous amplitude increase over nonglabrous (31%) was found. Although our study has a small number of participants, these results further the characterization of PPG skin differences, and can be used to inform development of PPG-based devices.

Association of CHA2DS2-VASc Score with Long-Term Incidence of New-Onset Atrial Fibrillation and Ischemic Stroke after Myocardial Infarction

The CHA2DS2-VASc score is a reliable tool used to estimate the risk of ischemic stroke (IS) in patients with atrial fibrillation (AF). Few tools exist for the prediction of new-onset AF (NOAF) after myocardial infarction (MI) and its relation to IS. We studied the usefulness of CHA2DS2-VASc in predicting NOAF and IS in a long-term follow-up after MI. Consecutive MI patients without baseline AF (n = 70,922; mean age: 68.2 years), discharged from 20 hospitals in Finland during 2005−2018, were retrospectively studied using national registries. The outcomes of interest after discharge were NOAF- and IS-assessed with competing risk analyses at one and ten years. The median follow-up was 4.2 years. The median baseline CHA2DS2-VASc score was 3 (IQR 2−5). The likelihood of both NOAF and NOAF-related IS increased stepwise with this score at one and ten years (all p < 0.0001). The one-year-adjusted subdistribution hazard ratio (sHR) was 4.03 (CI 3.68−4.42) for NOAF in patients with CHA2DS2-VASc scores ≥6 points. The cumulative incidence of IS was 15.2% in patients with NOAF vs. 6.2% in patients without AF at 10 years after MI (adj. sHR 2.12; CI 1.98−2.28; p < 0.0001). Coronary artery bypass surgery was associated with a higher NOAF incidence compared to percutaneous coronary intervention (adj. sHR 1.87; CI 1.65−2.13; p < 0.0001 one year after MI). The CHA2DS2-VASc score is a simple tool used to estimate the long-term risk of NOAF and IS after MI in patients without baseline AF. Coronary bypass surgery is associated with an increased NOAF incidence after MI.

Comparison of anticoagulation with left atrial appendage closure after atrial fibrillation ablation: Rationale and design of the OPTION randomized trial

BACKGROUND

For patients with symptomatic atrial fibrillation (AF), physicians typically offer AF ablation for symptom relief; however, patients often anticipate/expect a life free from anticoagulation. This belief puts patients at increased risk of stroke due to the potential for asymptomatic AF postablation if anticoagulation is ceased contrary to clinical guidelines. Although the WATCHMAN device has been FDA-approved to decrease the risk of thromboembolism from the left atrial appendage (LAA) in patients with an appropriate rationale to avoid oral anticoagulation, it has not been well-studied following AF ablation. Additionally, there are limited data comparing the WATCHMAN device to direct oral anticoagulants. The OPTION study will investigate whether LAA closure with the WATCHMAN FLX device is a reasonable alternative to oral anticoagulation following percutaneous catheter ablation for nonvalvular AF.

TRIAL DESIGN

OPTION is a multinational, multicenter, prospective randomized clinical trial. Patients with a CHA₂DS₂-VASc of ≥2 in men or ≥3 in women and who underwent a AF catheter ablation procedure between 90 and 180 days prior to randomization (sequential) or are planning to have catheter ablation within 10 days of randomization (concomitant) will be randomized in a 1:1 allocation of WATCHMAN FLX vs control. Control patients will start or continue market-approved oral anticoagulation for the duration of the trial. A total of 1600 patients were randomized from 130 global investigational sites. Follow-up for both device and control patients will occur at 3, 12, 24, and 36 months. The primary effectiveness noninferiority endpoint is stroke (ischemic or hemorrhagic), all-cause death, or systemic embolism at 36 months. The primary safety superiority endpoint is nonprocedural bleeding through 36 months (International Society on Thrombosis and Haemostasis [ISTH] major bleeding or clinically relevant nonmajor bleeding). The secondary noninferiority endpoint is ISTH major bleeding through 36 months (including procedural bleeding).

CONCLUSIONS

This trial will assess the safety and efficacy of WATCHMAN FLX in a postablation contemporary clinical AF patient population at risk of stroke.

Perspectives on the Molecular Mediators of Oxidative Stress and Antioxidant Strategies in the Context of Neuroprotection and Neurolongevity: An Extensive Review

Molecules with at least one unpaired electron in their outermost shell are known as free radicals. Free radical molecules are produced either within our bodies or by external sources such as ozone, cigarette smoking, X-rays, industrial chemicals, and air pollution. Disruption of normal cellular homeostasis by redox signaling may result in cardiovascular, neurodegenerative diseases and cancer. Although ROS (reactive oxygen species) are formed in the GI tract, little is known about how they contribute to pathophysiology and disease etiology. When reactive oxygen species and antioxidants are in imbalance in our bodies, they can cause cell structure damage, neurodegenerative diseases, diabetes, hypercholesterolemia, atherosclerosis, cancer, cardiovascular diseases, metabolic disorders, and other obesity-related disorders, as well as protein misfolding, mitochondrial dysfunction, glial cell activation, and subsequent cellular apoptosis. Neuron cells are gradually destroyed in neurodegenerative diseases. The production of inappropriately aggregated proteins is strongly linked to oxidative stress. This review's goal is to provide as much information as possible about the numerous neurodegenerative illnesses linked to oxidative stress. The possibilities of multimodal and neuroprotective therapy in human illness, using already accessible medications and demonstrating neuroprotective promise in animal models, are highlighted. Neuroprotection and neurolongevity may improve from the use of bioactive substances from medicinal herbs like Allium stadium, Celastrus paniculatus, and Centella asiatica. Many neuroprotective drugs' possible role has been addressed. Preventing neuroinflammation has been demonstrated in several animal models.

Usability of a smartwatch for atrial fibrillation detection in older adults after stroke

Background

Smartwatches can be used for atrial fibrillation (AF) detection, but little is known about how older adults at risk for AF perceive their usability.

Methods

We employed a mixed-methods study design using data from the ongoing Pulsewatch study, a randomized clinical trial (NCT03761394) examining the accuracy of a smartwatch-smartphone app dyad (Samsung/Android) compared to usual care with a patch monitor (Cardea SOLO™ ECG System) for detection of AF among older stroke survivors. To be eligible to participate in Pulsewatch, participants needed to be at least 50 years of age, have had an ischemic stroke, and have no major contraindications to anticoagulation therapy should AF be detected. After 14 days of use, usability was measured by the System Usability Scale (SUS) and investigator-generated questions. Qualitative interviews were conducted, transcribed, and coded via thematic analysis.

Results

Ninety participants in the Pulsewatch trial were randomized to use a smartwatch-smartphone app dyad for 14 days (average age: 65 years, 41% female, 87% White), and 46% found it to be highly usable (SUS ≥68). In quantitative surveys, participants who used an assistive device (eg, wheelchair) and those with history of anxiety or depression were more likely to report anxiety associated with watch use. In qualitative interviews, study participants reported wanting a streamlined system that was more focused on rhythm monitoring and a smartwatch with a longer battery life. In-person training and support greatly improved their experience, and participants overwhelmingly preferred use of a smartwatch over traditional cardiac monitoring owing to its comfort, appearance, and convenience.

Conclusion

Older adults at high risk for AF who were randomized to use a smartwatch-app dyad for AF monitoring over 14 days found it to be usable for AF detection and preferred their use to the use of a patch monitor. However, participants reported that a simpler device interface and longer smartwatch battery life would increase the system's usability.

Atrial fibrillation (AF) pilot screening programme in primary care in Ireland: an implementation study protocol

INTRODUCTION

Atrial fibrillation (AF) is a major risk factor for stroke. There is a fivefold increase in stroke risk in the presence of AF. The irregular beating of the heart enables blood stasis which allows clots to form. These can migrate to the brain causing a stroke. AF is common and its incidence increases with age. AF is often asymptomatic and early detection enables effective preventive treatment reducing stroke risk by up to two-thirds.Stroke contributes significantly to morbidity and mortality globally. In Ireland, it is the leading cause of acquired disability and second leading cause of death. The cost associated with stroke is significant. Stroke risk increases with age and is a public health priority.Internationally, there is consensus among experts that AF screening is valuable. In Ireland, the National Cardiovascular Policy recommended establishing a screening programme. However, there are many ways to screen for AF including pulse palpation, mobile ECG devices, 12-lead ECG and personal health monitoring devices.This study aims to investigate the acceptability, feasibility and impact of AF screening in primary care using a handheld mobile ECG device.

METHODS AND ANALYSIS

General practitioners (GPs) and practice nurses in the South of Ireland will opportunistically screen patients aged ≥65 years for AF at routine consultation using a handheld one-lead ECG device, KardiaMobile. This study will screen up to 4000 patients. Blood pressure and smoking status will be checked concurrently. A mixed-method evaluation will be undertaken including a partial economic evaluation. Anonymised data will be collected from participating practices and qualitative interviews will be conducted with GP, nurse and patient participants.

ETHICS AND DISSEMINATION

Ethical approval has been granted by the Clinical Research Ethics Committee in University College Cork. Dissemination will involve publication in peer-reviewed journals and presentation at national and international conferences.

Contactless facial video recording with deep learning models for the detection of atrial fibrillation

Atrial fibrillation (AF) is often asymptomatic and paroxysmal. Screening and monitoring are needed especially for people at high risk. This study sought to use camera-based remote photoplethysmography (rPPG) with a deep convolutional neural network (DCNN) learning model for AF detection. All participants were classified into groups of AF, normal sinus rhythm (NSR) and other abnormality based on 12-lead ECG. They then underwent facial video recording for 10 min with rPPG signals extracted and segmented into 30-s clips as inputs of the training of DCNN models. Using voting algorithm, the participant would be predicted as AF if > 50% of their rPPG segments were determined as AF rhythm by the model. Of the 453 participants (mean age, 69.3 ± 13.0 years, women, 46%), a total of 7320 segments (1969 AF, 1604 NSR & 3747others) were analyzed by DCNN models. The accuracy rate of rPPG with deep learning model for discriminating AF from NSR and other abnormalities was 90.0% and 97.1% in 30-s and 10-min recording, respectively. This contactless, camera-based rPPG technique with a deep-learning model achieved significantly high accuracy to discriminate AF from non-AF and may enable a feasible way for a large-scale screening or monitoring in the future.

Prevalence and characteristics of atrial fibrillation in Makassar city population: A telemedicine study

OBJECTIVE

Atrial fibrillation (AF) is one of the most commonly occurring arrhythmias and a major modifiable risk factor of stroke, especially in women. The incidence of AF in Indonesia is not well-characterized yet. This is a community-based study to determine the prevalence and characteristics of AF in the Makassar city population.

METHOD

Standard ECG recording showing atrial fibrillation obtained between January 1, 2014 and September 31, 2018 from Telemedicine Study Center in Hasanuddin University Hospital were collected in form of portable document format (pdf) and were analyzed. ECG with incomplete interpretation and/or epidemiological data were excluded. ECG interpretation and analysis were performed by the first author as an electrophysiologist (MA). Epidemiological data, heart rate, P wave amplitude, QRS axis, QRS complex duration and configuration, QRS rate (ventricular response), corrected QT interval according to Bazzett's formula, presence of QRS complex abnormalities and ST-T changes were analyzed. Data analysis were performed using SPSS 20.0 for Windows.

RESULT

A total of 19.718 ECG data were obtained, taken from the Makassar Telemedicine study data center at Hasanuddin University Hospital which cover all Public Health Center and a private clinic in Makassar city. From this population, AF was found in 189 (0.96%) ECGs. 98 (51.9%) are males' and 91 (48.1%) of which are females'. AF is increasingly prevalent with increasing ages. There was a significant difference on the QRS axis between male and female with a p value of <0.001. The duration of the QRS complex between men and women was significantly different (p=0.038). QTc value was also found to be significantly different between male and female (p=0.001). AF was accompanied by PVC in 9 males and 2 females.

CONCLUSION

The prevalence of AF in the Makassar population is 0.96%, more common in men and elderly.

Differences between Atrial Fibrillation Detected before and after Stroke and TIA: A Systematic Review and Meta-Analysis

BACKGROUND

Preliminary evidence suggests that patients with atrial fibrillation (AF) detected after stroke (AFDAS) may have a lower prevalence of cardiovascular comorbidities and lower risk of stroke recurrence than AF known before stroke (KAF).

OBJECTIVE

We performed a systematic search and meta-analysis to compare the characteristics of AFDAS and KAF.

METHODS

We searched PubMed, Scopus, and EMBASE for articles reporting differences between AFDAS and KAF until June 30, 2021. We performed random- or fixed-effects meta-analyses to evaluate differences between AFDAS and KAF in demographic factors, vascular risk factors, prevalent vascular comorbidities, structural heart disease, stroke severity, insular cortex involvement, stroke recurrence, and death.

RESULTS

In 21 studies including 22,566 patients with ischemic stroke or transient ischemic attack, the prevalence of coronary artery disease, congestive heart failure, prior myocardial infarction, and a history of cerebrovascular events was significantly lower in AFDAS than KAF. Left atrial size was smaller, and left ventricular ejection fraction was higher in AFDAS than KAF. The risk of recurrent stroke was 26% lower in AFDAS than in KAF. There were no differences in age, sex, stroke severity, or death rates between AFDAS and KAF. There were not enough studies to report differences in insular cortex involvement between AF types.

CONCLUSIONS

We found significant differences in the prevalence of vascular comorbidities, structural heart disease, and stroke recurrence rates between AFDAS and KAF, suggesting that they constitute different clinical entities within the AF spectrum. PROSPERO registration number is CRD42020202622.

Racial and Urban-Rural Difference in the Frequency of Ischemic Stroke as Initial Manifestation of Atrial Fibrillation

Objective: Atrial fibrillation (AF) may remain undiagnosed until the development of complications. We aimed to examine the epidemiology and racial/ethnic and rural/urban differences in the frequency of newly diagnosed AF manifesting as ischemic stroke in a nationally representative sample of Medicare beneficiaries.

Methods: We used a 5% random sample of Medicare claims to identify patients newly diagnosed with AF in 2016. The primary dependent variable was stroke or transient ischemic attack (TIA) in the 7 days prior to the first AF diagnosis, i.e., stroke or TIA as the initial manifestation of AF. We constructed a multivariable logistic regression to quantify the association between race/ethnicity, urban/rural residence, and the primary dependent variable.

Results: Among 39,409 patients newly diagnosed with AF (mean age 77 ± 10 years; 58% women; 7.2% Black, 87.8% White, 5.1% others), 2,819 (7.2%) had ischemic stroke or TIA in the 7 days prior to AF diagnosis. Black patients (adjusted OR [95% CI]: 1.21 [1.05, 1.40], vs. White) and urban residents (1.21 [1.08, 1.35], vs. rural) were at increased risk of stroke as the initial manifestation of AF. Racial differences were larger among patients aged ≥75 years, with adjusted ORs of 1.43 (1.19, 1.73) for Black vs. White patients, but non-significant for those aged <75 (P for interaction = 0.03).

Conclusion: We observed significant and important differences in the risk of stroke as initial manifestation of AF between White and Black patients and between rural and urban residents. Our results suggest potential disparities in the identification AF across race/ethnicity groups and urban/rural areas.

Three year clinical outcomes in a nationwide, observational, siteless clinical trial of atrial fibrillation screening-mHealth Screening to Prevent Strokes (mSToPS)

BACKGROUND

Atrial fibrillation (AF) is common, often without symptoms, and is an independent risk factor for mortality, stroke and heart failure. It is unknown if screening asymptomatic individuals for AF can improve clinical outcomes.

METHODS

mSToPS was a pragmatic, direct-to-participant trial that randomized individuals from a single US-wide health plan to either immediate or delayed screening using a continuous-recording ECG patch to be worn for two weeks and 2 occasions, ~3 months apart, to potentially detect undiagnosed AF. The 3-year outcomes component of the trial was designed to compare clinical outcomes in the combined cohort of 1718 individuals who underwent monitoring and 3371 matched observational controls. The prespecified primary outcome was the time to first event of the combined endpoint of death, stroke, systemic embolism, or myocardial infarction among individuals with a new AF diagnosis, which was hypothesized to be the same in the two cohorts but was not realized.

RESULTS

Over the 3 years following the initiation of screening (mean follow-up 29 months), AF was newly diagnosed in 11.4% (n = 196) of screened participants versus 7.7% (n = 261) of observational controls (p<0.01). Among the screened cohort with incident AF, one-third were diagnosed through screening. For all individuals whose AF was first diagnosed clinically, a clinical event was common in the 4 weeks surrounding that diagnosis: 6.6% experienced a stroke,10.2% were newly diagnosed with heart failure, 9.2% had a myocardial infarction, and 1.5% systemic emboli. Cumulatively, 42.9% were hospitalized. For those diagnosed via screening, none experienced a stroke, myocardial infarction or systemic emboli in the period surrounding their AF diagnosis, and only 1 person (2.3%) had a new diagnosis of heart failure. Incidence rate of the prespecified combined primary endpoint was 3.6 per 100 person-years among the actively monitored cohort and 4.5 per 100 person-years in the observational controls.

CONCLUSIONS

At 3 years, screening for AF was associated with a lower rate of clinical events and improved outcomes relative to a matched cohort, although the influence of earlier diagnosis of AF via screening on this finding is unclear. These observational data, including the high event rate surrounding a new clinical diagnosis of AF, support the need for randomized trials to determine whether screening for AF will yield a meaningful protection from strokes and other clinical events.

TRAIL REGISTRATION

The mHealth Screening To Prevent Strokes (mSToPS) Trial is registered on ClinicalTrials.gov with the identifier NCT02506244.

Atrial Fibrillation Detected by Single Timepoint Handheld ECG Screening and the Risk of Ischemic Stroke

OBJECTIVE

We evaluated stroke risk in patients with single timepoint screen-detected atrial fibrillation (AF) and the effect of oral anticoagulants (OAC).

METHODS

Consecutive patients aged ≥65 years attending medical outpatient clinics were prospectively enrolled for AF-screening using handheld single-lead ECG (AliveCor) from 12/2014 to 12/2017 (NCT02409654). Repeated screening was performed in patients with >1 visit during this period. Three cohorts were formed, screen-detected AF, clinically-diagnosed AF and no AF. Ischemic stroke risk was estimated using adjusted sub-distribution hazard ratios (aSHR) from multivariate regression and no AF as reference, and stratified according to OAC use.

RESULTS

Of 11,972 subjects enrolled, 2,238 (18.7%) had clinically-diagnosed AF at study enrollment. The yield of screen-detected AF on initial screening was 2.3% (n=223/9,734). AF was clinically-diagnosed during follow-up in 2.3% (n=216/9,440) and during subsequent screening in 71 initially screen-negative patients. Compared to no AF, patients with screen-detected AF without OAC treatment had the highest stroke risk (aSHR 2.63; 95% confidence interval 1.46-4.72), while aSHR for clinically-diagnosed AF without OAC use was 2.01 (1.54-2.62). Among screen-detected AF the risk of stroke was significantly less with OAC (no strokes in 196 person-years) compared with those not given OAC (12 strokes in 429 person-years), p=0.01.

CONCLUSION

The prognosis of single timepoint ECG screen-detected AF is not benign. The risk of stroke is high enough to warrant OAC use, and reduced by OAC.

Costs of Stroke and Incidence of First Diagnosis of Atrial Fibrillation at Time of Stroke. Neurology Ward Hospital Poznań, Poland 2018

Stroke is a major cause of morbidity in industrialized countries, representing 8% of total deaths across Europe in 2017. It is also a very costly disorder, frequently caused by atrial fibrillation. We aimed to calculate the cost of stroke hospitalization in 2018 in Poznań (Poland). We also intended to present patients with the first AF diagnosis at the time of stroke. The study was conducted from January 2019 to July 2020. Data were obtained from hospital records and from the hospital accounting department. Out of 164 patients included in the study, 41 had AF and in 18 cases AF was first diagnosed at the time of stroke. The cost of hospitalization in Poznań was EUR 139,257.21 (x¯= EUR 849.13). Among those with concomitant AF, the general cost of inpatient care was EUR 33,859.18 (x¯= EUR 825.83). Considering those who had AF first diagnosed during hospitalization the cost was EUR 16,248.97 (x¯= EUR 906.24). Stroke is associated with high costs of inpatient care, which turned out to be higher among those with AF first diagnosed at the time of stroke. The number of patients who used oral anticoagulants at the time of admission was relatively low. The most frequently used NOAC was dabigatran.

Role of digital health in detection and management of atrial fibrillation

Atrial fibrillation is a common arrhythmia associated with significant morbidity, mortality and decreased quality of life. Mobile health devices marketed directly to consumers capable of detecting atrial fibrillation through methods including photoplethysmography, single-lead ECG as well as contactless methods are becoming ubiquitous. Large-scale screening for atrial fibrillation is feasible and has been shown to detect more cases than usual care-however, controversy still exists surrounding screening even in older higher risk populations. Given widespread use of mobile health devices, consumer-driven screening is happening on a large scale in both low-risk and high-risk populations. Given that young people make up a large portion of early adopters of mobile health devices, there is the potential that many more patients with early onset atrial fibrillation will come to clinical attention requiring possible referral to genetic arrythmia clinic. Physicians need to be familiar with these technologies, and understand their risks, and limitations. In the current review, we discuss current mobile health devices used to detect atrial fibrillation, recent and upcoming trials using them for diagnosis of atrial fibrillation, practical recommendations for patients with atrial fibrillation diagnosed by a mobile health device and special consideration in young patients.

A randomized prospective multicenter trial for stroke prevention by prophylactic surgical closure of the left atrial appendage in patients undergoing bioprosthetic aortic valve surgery--LAA-CLOSURE trial protocol

Patients undergoing surgical aortic valve replacement (SAVR) are at high risk for atrial fibrillation (AF) and stroke after surgery. There is an unmet clinical need to improve stroke prevention in this patient population. The LAA-CLOSURE trial aims to assess the efficacy and safety of prophylactic surgical closure of the left atrial appendage for stroke and cardiovascular death prevention in patients undergoing bioprosthetic SAVR. This randomized, open-label, prospective multicenter trial will enroll 1,040 patients at 13 European sites. The primary endpoint is a composite of cardiovascular mortality, stroke and systemic embolism at 5 years. Secondary endpoints include cardiovascular mortality, stroke, systemic embolism, bleed fulfilling academic research consortium (BARC) criteria, hospitalization for decompensated heart failure and health economic evaluation. Sample size is based on 30% risk reduction in time to event analysis of primary endpoint. Prespecified reports include 30-day safety analysis focusing on AF occurrence and short-term outcomes and interim analyses at 1 and 3 years for primary and secondary outcomes. Additionally, substudies will be performed on the completeness of the closure using transesophageal echocardiography/cardiac computed tomography and long-term ECG recording at one year after the operation.

A Comprehensive Explanation Framework for Biomedical Time Series Classification

In this study, we propose a post-hoc explainability framework for deep learning models applied to quasi-periodic biomedical time-series classification. As a case study, we focus on the problem of atrial fibrillation (AF) detection from electrocardiography signals, which has strong clinical relevance. Starting from a state-of-the-art pretrained model, we tackle the problem from two different perspectives: global and local explanation. With global explanation, we analyze the model behavior by looking at entire classes of data, showing which regions of the input repetitive patterns have the most influence for a specific outcome of the model. Our explanation results align with the expectations of clinical experts, showing that features crucial for AF detection contribute heavily to the final decision. These features include R-R interval regularity, absence of the P-wave or presence of electrical activity in the isoelectric period. On the other hand, with local explanation, we analyze specific input signals and model outcomes. We present a comprehensive analysis of the network facing different conditions, whether the model has correctly classified the input signal or not. This enables a deeper understanding of the network's behavior, showing the most informative regions that trigger the classification decision and highlighting possible causes of misbehavior.

Digital health solutions in the screening of subclinical atrial fibrillation

Atrial fibrillation (AF) will become one of the biggest challenges in cardiovascular medicine in the near future. Attempting an improvement in future patient care calls explicitly for the screening of subclinical AF. Digital health solutions implementing communication technologies for the collection and analysis of digitally assessable data will most likely serve this need. Several new rapidly developing methods were introduced in the past decade. Although the vast majority still require scientific validation, the body of evidence is growing and several randomized controlled trials are planned. This review aims to give an overview of current technologies with a specific focus on mobile health (mHealth) and appraise their value with regard to the available scientific data.

Smoking Cessation after Diagnosis of New-Onset Atrial Fibrillation and the Risk of Stroke and Death

Limited data are available regarding the impact of smoking cessation after atrial fibrillation (AF) diagnosis on clinical outcomes. Using the Korean National Health Insurance Service database, we included patients newly diagnosed with AF and categorized them into four groups as follows: (i) never smokers, (ii) ex-smokers, (iii) smoking cessation after AF diagnosis ("quitters"), and (iv) current smokers. The primary outcomes were incident ischemic stroke and all-cause death during follow-up. Fatal ischemic stroke and death from cerebrovascular events were evaluated as secondary outcomes. Among 97,637 patients (mean age, 61 years; mean CHA₂DS₂-VASc score, 2.3), 6.9% stopped smoking after AF diagnosis. The mean follow-up duration was 3.2 ± 2.0 years. After multivariable adjustment, quitters had lower risks of ischemic stroke (hazard ratio (HR), 0.702; 95% confidence interval (CI), 0.595-0.827) and all-cause death (HR, 0.842; 95% CI, 0.748-0.948) than current smokers. Quitters after AF diagnosis were associated with lower risks of fatal ischemic stroke (HR, 0.454; 95% CI, 0.287-0.718) and death from cerebrovascular events (HR, 0.664; 95% CI, 0.465-0.949) compared with current smokers. Quitting smoking may reduce the risk of ischemic stroke, the severity of ischemic stroke, and the incidence of cerebrovascular events in patients with new-onset AF.

Impact of Mobile Health Devices for the Detection of Atrial Fibrillation: Systematic Review

Background

Atrial fibrillation (AF) is the most common arrhythmia, and its prevalence is increasing. Early diagnosis is important to reduce the risk of stroke. Mobile health (mHealth) devices, such as single-lead electrocardiogram (ECG) devices, have been introduced to the worldwide consumer market over the past decade. Recent studies have assessed the usability of these devices for detection of AF, but it remains unclear if the use of mHealth devices leads to a higher AF detection rate.

Objective

The goal of the research was to conduct a systematic review of the diagnostic detection rate of AF by mHealth devices compared with traditional outpatient follow-up. Study participants were aged 16 years or older and had an increased risk for an arrhythmia and an indication for ECG follow-up—for instance, after catheter ablation or presentation to the emergency department with palpitations or (near) syncope. The intervention was the use of an mHealth device, defined as a novel device for the diagnosis of rhythm disturbances, either a handheld electronic device or a patch-like device worn on the patient’s chest. Control was standard (traditional) outpatient care, defined as follow-up via general practitioner or regular outpatient clinic visits with a standard 12-lead ECG or Holter monitoring. The main outcome measures were the odds ratio (OR) of AF detection rates.

Methods

Two reviewers screened the search results, extracted data, and performed a risk of bias assessment. A heterogeneity analysis was performed, forest plot made to summarize the results of the individual studies, and albatross plot made to allow the P values to be interpreted in the context of the study sample size.

Results

A total of 3384 articles were identified after a database search, and 14 studies with a 4617 study participants were selected. All studies but one showed a higher AF detection rate in the mHealth group compared with the control group (OR 1.00-35.71), with all RCTs showing statistically significant increases of AF detection (OR 1.54-19.16). Statistical heterogeneity between studies was considerable, with a Q of 34.1 and an I² of 61.9, and therefore it was decided to not pool the results into a meta-analysis.

Conclusions

Although the results of 13 of 14 studies support the effectiveness of mHealth interventions compared with standard care, study results could not be pooled due to considerable clinical and statistical heterogeneity. However, smartphone-connectable ECG devices provide patients with the ability to document a rhythm disturbance more easily than with standard care, which may increase empowerment and engagement with regard to their illness. Clinicians must beware of overdiagnosis of AF, as it is not yet clear when an mHealth-detected episode of AF must be deemed significant.

Adherence to anticoagulant guideline for atrial fibrillation: A large care gap among stroke patients in a rural population

OBJECTIVE

This study aimed to investigate the prevalence and factors associated with oral anticoagulant undertreatment of atrial fibrillation (AF) among a cohort of rural patients with stroke outcomes and examine how undertreatment may influence a patient's one-year survival after stroke.

METHODS

This retrospective cohort study examined ischemic stroke patients with pre-stroke AF diagnosis from September 2003 to May 2019 and divided them into proper treatment and undertreatment group. Analysis included chi-square test, variance analysis, Kruskal-Wallis test, logistic regression, Kaplan-Meier estimator, and Cox proportional-hazards model.

RESULTS

Out of 1062 ischemic stroke patients with a pre-stroke AF diagnosis, 1015 patients had a CHA₂DS₂-VASc score ≥2, and 532 (52.4%) of those were undertreated. Median time from AF diagnosis to index stroke was significantly lower among undertreated patients (1.9 years vs. 3.6 years, p < 0.001). Other thromboembolism, excluding stroke, TIA, and myocardial infarction (OR 0.41, p < 0.001), the number of encounters per year (OR 0.90, p < 0.001), and the median time between AF diagnosis and stroke event (OR 0.86, p < 0.001) were negatively associated with undertreatment. Kaplan-Meier estimator showed no statistical difference in the one-year survival probability between groups (log-rank test, p = 0.29), while the Cox-Hazard model showed that age (HR 1.05, p < 0.001) and history of congestive heart failure (HR 1.88, p < 0.001) increased the risk of mortality.

CONCLUSIONS

More than half of our rural stroke patients with a pre-index AF diagnosis were not on guideline-recommended treatment. The study highlights a large care gap and an opportunity to improve AF management.

Single-lead ECGs (AliveCor) are a feasible, cost-effective and safer alternative to 12-lead ECGs in community diagnosis and monitoring of atrial fibrillation

BACKGROUND

Community management of atrial fibrillation (AF) often requires the use of electrocardiographic (ECG) investigation. Patients discharged following treatment of AF with fast ventricular response (fast AF) can require numerous ECGs to monitor rate and/or rhythm control. Single-lead ECGs have been proposed as a more convenient and relatively accurate alternative to 12-lead ECGs for rate/rhythm management and also diagnosis of AF. We aimed to examine the feasibility of using the AliveCor single-lead ECG monitor for diagnosis and monitoring of AF in the community setting.

METHODS

During the course of 6 months, this evaluation of a clinical service improvement pathway used the AliveCor in management of patients requiring (1) follow-up ECGs for AF with previously documented rapid ventricular rate or (2) ECG confirmation of rhythm where AF was suspected. Twelve AliveCor devices provided to the acute community medical team were used to produce 30 s ECG rhythm strips (iECG) that were electronically sent to an overreading physician.

RESULTS

Seventy-four patients (mean age 82 years) were managed on this pathway. (1) The AliveCor was successfully used to monitor the follow-up of 37 patients with fast AF, acquiring a combined total of 113 iECGs (median 1.5 ±3.75 per patient). None of these patients required a subsequent 12-lead ECG and this approach saved an estimate of up to £134.49 per patient. (2) Of 53 patients with abnormal pulses, the system helped identify 8 cases of new onset AF and 19 cases of previously known AF that had reverted from sinus back into AF.

CONCLUSIONS

We have demonstrated that the AliveCor system is a feasible, cost-effective, time-efficient and potentially safer alternative to serial 12-lead ECGs for community monitoring and diagnosis of AF.

Screening for atrial fibrillation: predicted sensitivity of short, intermittent electrocardiogram recordings in an asymptomatic at-risk population

AIMS

Screening for asymptomatic atrial fibrillation (AF) could prevent strokes and save lives, but the AF burden of those detected can impact prognosis. New technologies enable continuous monitoring or intermittent electrocardiogram (ECG) snapshots, however, the relationship between AF detection rates and the burden of AF found with intermittent strategies is unknown. We simulated the likelihood of detecting AF using real-world 2-week continuous ECG recordings and developed a generalizable model for AF detection strategies.

METHODS AND RESULTS

From 1738 asymptomatic screened individuals, ECG data of 69 individuals (mean age 76.3, median burden 1.9%) with new AF found during 14 days continuous monitoring were used to simulate 30 seconds ECG snapshots one to four times daily for 14 days. Based on this simulation, 35-66% of individuals with AF would be detected using intermittent screening. Twice-daily snapshots for 2 weeks missed 48% of those detected by continuous monitoring, but mean burden was 0.68% vs. 4% in those detected (P < 0.001). In a cohort of 6235 patients (mean age 69.2, median burden 4.6%) with paroxysmal AF during clinically indicated monitoring, simulated detection rates were 53-76%. The Markovian model of AF detection using mean episode duration and mean burden simulated actual AF detection with ≤9% error across the range of screening frequencies and durations.

CONCLUSION

Using twice-daily ECG snapshots over 2 weeks would detect only half of individuals discovered to have AF by continuous recordings, but AF burden of those missed was low. A model predicting AF detection, validated using real-world data, could assist development of optimized AF screening programmes.

Interatrial block, P terminal force or fragmented QRS do not predict new-onset atrial fibrillation in patients with severe chronic kidney disease

Background

The prevalence of left atrial enlargement (LAE) and fragmented QRS (fQRS) diagnosed using ECG criteria in patients with severe chronic kidney disease (CKD) is unknown. Furthermore, there is limited data on predicting new-onset atrial fibrillation (AF) with LAE or fQRS in this patient group.

Methods

We enrolled 165 consecutive non-dialysis patients with CKD stage 4–5 without prior AF diagnosis between 2013 and 2017 in a prospective follow-up cohort study. LAE was defined as total P-wave duration ≥120 ms in lead II ± > 1 biphasic P-waves in leads II, III or aVF; or duration of terminal negative portion of P-wave > 40 ms or depth of terminal negative portion of P-wave > 1 mm in lead V₁ from a baseline ECG, respectively. fQRS was defined as the presence of a notched R or S wave or the presence of ≥1 additional R waves (R’) or; in the presence of a wide QRS complex (> 120 ms), > 2 notches in R or S waves in two contiguous leads corresponding to a myocardial region, respectively.

Results

Mean age of the patients was 59 (SD 14) years, 56/165 (33.9%) were female and the mean estimated glomerular filtration rate was 12.8 ml/min/1.73m². Altogether 29/165 (17.6%) patients were observed with new-onset AF within median follow-up of 3 [IQR 3, range 2–6] years. At baseline, 137/165 (83.0%) and 144/165 (87.3%) patients were observed with LAE and fQRS, respectively. Furthermore, LAE and fQRS co-existed in 121/165 (73.3%) patients. Neither findings were associated with the risk of new-onset AF within follow-up.

Conclusion

The prevalence of LAE and fQRS at baseline in this study on CKD stage 4–5 patients not on dialysis was very high. However, LAE or fQRS failed to predict occurrence of new-onset AF in these patients.

Detection of Previously Unrecognized (Subclinical) Atrial Fibrillation

Atrial fibrillation (AF) has been associated with increased morbidity and mortality, even when symptoms are absent and the arrhythmia is unrecognized (e.g., subclinical AF [SCAF]). Despite substantial evidence demonstrating an association between AF and adverse outcomes, the role of mass screening for previously unrecognized SCAF, such that its individual and population risks may be reduced by prophylactic therapy, remains uncertain. Many AF screening strategies exist, from pulse palpation and single-use devices to implanted cardiac monitors; however, existing guidelines are insufficient in specifying who to screen and for how long. In general, higher age, more (and more severe) comorbidities, and longer monitoring periods are associated with greater detection of SCAF. Herein we review the significance of previously unrecognized SCAF and current status of SCAF detection methods. We then propose a clinical approach to help clinicians incorporate AF screening into their practice. In conclusion, we report that SCAF may not be rare, that inserted cardiac monitors have the highest yield of SCAF detection, that clinical concern regarding SCAF is appropriate, but that evidence for therapy mandates is still being collected.

Paroxysmal atrial fibrillation is associated with early coagulation activity regardless of risk factors for embolism

BACKGROUND

Paroxysmal atrial fibrillation (PAF) is associated with an increased incidence of embolic events, even in patients with no embologenic risk factors. This fact raises the question for the hypercoagulability in PAF as a state closely related to the arrhythmia itself, independent of other well established embologenic risk factors. The scarce data on that topic predisposed our aim that was to study coagulation activity in the early hours (up to the twenty-fourth hour) of the disease.

METHODS

Fifty-one non-anticoagulated patients (26 men, 25 women; mean age 59.84±1.60 years) and 52 controls (26 men, 26 women; mean age 59.50±1.46 years) were consequently selected for the study. Plasma coagulation activity of factor II (FII), factor V (FV) and factor X (FX) was examined.

RESULTS

In the PAF group, there was a higher activity of FII (167.81±9.12% vs. 100.43±5.77%, P<0.001), FV (198.47±10.88% vs. 121.53±4.79%, P<0.001) and FX (193.20±11.85 vs. 116.20±5.86, P<0.001). The deviations were independent of age, sex, body mass index, presence of hypertension and CHA<inf>2</inf>DS<inf>2</inf>-VASc risk score (P>0.05). PAF duration was a significant predictor of FII activity (r=0.83, P<0.001) but no correlation was established between FV and FX activity and the arrhythmia duration (r=0.10, P>0.05; r=0.11, P>0.05, respectively).

CONCLUSIONS

We established high coagulation activity during the first twenty-four hours of PAF. The observed deviations in the studied parameters give us reason to consider PAF a procoagulant state independent of the well-established prothrombotic risk factors, even in its early clinical manifestation.

Review of mobile applications for the detection and management of atrial fibrillation

BACKGROUND

Free mobile applications (apps) that use photoplethysmography (PPG) waveforms may extend atrial fibrillation (AF) detection to underserved populations, but they have not been rigorously evaluated.

OBJECTIVE

The purpose of this study was to systematically review and evaluate the quality, functionality, and adherence to self-management behaviors of existing mobile apps for AF.

METHODS

We systematically searched 3 app stores for apps that were free, available in English, and intended for use by patients to detect and manage AF. A minimum of 2 reviewers evaluated (1) app quality, using the Mobile Application Rating Scale (MARS); (2) functionality using published criteria; and (3) features that support 4 self-management behaviors (including PPG waveform monitoring) identified using evidence-based guidelines. Interrater reliability between the reviewers was calculated.

RESULTS

Of 12 included apps, 5 (42%) scored above average for quality (MARS score ≥3.0). App quality was highest for their ease of use, navigation, layout, and visual appeal (eg, functionality and aesthetics) and lowest for their behavioral change support and subjective impressions of quality. The most common app functionalities were capturing and graphically displaying user-entered data (n = 9 [75%]). Nearly all apps (n = 11 [92%]) supported PPG waveform monitoring, but only 2 (17%) supported all 4 self-management behaviors. Interrater reliability was high (0.75-0.83).

CONCLUSION

The reviewed apps had wide variability in quality, functionality, and adherence to self-management behaviors. Given the accessibility of these apps to underserved populations and the tremendous potential they hold for improving AF detection and management, high priority should be given to improving app quality and functionality.

Assessment of the manifestations of atrial fibrillation in patients with acute cerebral stroke - a single-center study based on 998 patients

Aim of the Study: Cardioembolic stroke accounts for approximately 15-25% of ischemic strokes and is characterized by a poor prognosis. Atrial fibrillation (AF) is more commonly diagnosed in the elderly.The aim of the study was the assessment of the manifestations of AF in patients hospitalized due to cerebral stroke, with particular attention paid to newly diagnosed AF.Methods: A retrospective analysis was performed on 998 cerebral stroke patients. The data were analyzed for sex, age, cerebral stroke risk factors, drugs, NIHSS, RANKIN scores and ECG recordings on admission and at discharge.Results: The mean age of disease onset was 73 ± 16 years. Women accounted for 50.8% of patients. AF prior to hospital admission was diagnosed in 20.1% of patients, while de novo AF in 26.3% of patients during hospitalization. Hypercholesterolemia, hypertriglyceridemia and smoking were more commonly reported in ischemic stroke patients without AF compared to patients with ischemic stroke and AF. Ischemic heart disease, more frequent deaths, and a worse prognosis were more frequently observed in patients with ischemic stroke and AF compared to patients without AF. The first manifestation of AF in 25% of stroke patients was related to the period of the first 10 days of hospitalization.Discussion: The above data should prompt neurologists, cardiologists and family doctors to try to detect AF as a risk factor for ischemic stroke which worsens patient prognosis, prolongs hospital stay and contributes to increase in mortality, especially when more effective drug treatment is currently possible.

Clinical factors associated with the development of postoperative atrial fibrillation in esophageal cancer patients receiving multimodality therapy before surgery

Background

The incidence of esophageal cancer (EC) is increasing in the USA. Neoadjuvant therapy for locally advanced cancers followed by surgical resection is the standard of care. The most common post-esophagectomy cardiac complication is atrial fibrillation (AF). New-onset postoperative AF can require a prolonged hospital stay and may confer an overall poorer prognosis. In this study, we seek to identify clinical factors associated with postoperative AF.

Methods

Query of an IRB approved database of 1,039 esophagectomies at our institution revealed 677 patients with EC from 1999 to 2017 who underwent esophagectomy after neoadjuvant treatment. Age, treatment location (primary vs. other), gender, neoadjuvant radiation type [2D vs. 3D vs. intensity modulated radiation therapy (IMRT)], radiation dose, surgery type (transthoracic vs. transhiatal vs. three field), smoking history, coronary artery disease (CAD), chronic obstructive pulmonary disease (COPD), operative time, blood transfusions, fluid management, and length of stay (LOS) were analyzed in relationship to the development of AF. Statistical analysis was performed with SPSS 24.

Results

The mean age of the entire cohort was 64.3 (range, 28-86 years), with a Caucasian and male preponderance (White: 94.5%; male: 83.6%). Of the 677 patients, 14.9% (n=101) developed postoperative AF. Increasing age (P<0.001), increased radiation dose (P=0.034), operative time (P=0.001), and blood transfusions (P=0.027) were associated with AF. LOS was longer in patients with AF than those without AF (10.5 vs. 10.0 days, P=0.001). On multivariate analysis, increasing age (95% CI: 1.023-1.080, P<0.001) and radiation dose (95% CI: 1.000-1.001, P=0.034) remained significant. None of the other parameters assessed were associated with the development of AF.

Conclusions

Increasing age and radiation dose were associated with the development of postoperative AF in this cohort. This study suggests that older patients or patients receiving higher radiation dose should be monitored more closely in the postoperative setting and potentially referred earlier preoperatively for cardio-oncology assessment. Future study is required to determine if modification of current radiation techniques and cardiac dose constraints in this patient population may be warranted.

Validity of daily self-pulse palpation for atrial fibrillation screening in patients 65 years and older: A cross-sectional study

BACKGROUND

The European Society of Cardiology guidelines recommend (Class IA) single-time-point screening for atrial fibrillation (AF) using pulse palpation. The role of pulse palpation for AF detection has not been validated against electrocardiogram (ECG) recordings. We aimed to study the validity of AF screening using self-pulse palpation compared with an ECG recording conducted at the same time using a handheld ECG 3 times a day for 2 weeks.

METHODS AND FINDINGS

In this cross-sectional screening study, patients 65 years of age and older attending 4 primary care centers (PCCs) outside Stockholm County were invited to take part in AF screening from July 2017 to December 2018. Patients were included irrespective of their reason for visiting the PCC. Handheld intermittent ECGs 3 times per day were offered to patients without AF for a period of 2 weeks, and patients were instructed in how to take their own pulse at the same time. A total of 1,010 patients (mean age 73 years, 61% female, with an average CHA2DS2-VASc score 2.9) participated in the study, and 27 (2.7%, 95% CI 1.8%-3.9%) new cases of AF were detected. Anticoagulants (ACs) could be initiated in 26 (96%, 95% CI 81%-100%) of these cases. A total of 53,782 simultaneous ECG recordings and pulse measurements were registered. AF was verified in 311 ECG recordings, of which the pulse was palpated as irregular in 77 recordings (25%, 95% CI 20%-30% sensitivity per measurement occasion). Of the 27 AF cases, 15 cases felt an irregular pulse on at least one occasion (56%, 95% CI 35%-75% sensitivity per individual). 187 individuals without AF felt an irregular pulse on at least one occasion. The specificity per measurement occasion and per individual was (98%, 95% CI 98%-98%) and (81%, 95% CI 78%-83%), respectively.

CONCLUSIONS

AF screening using self-pulse palpation 3 times daily for 2 weeks has lower sensitivity compared with simultaneous intermittent ECG. Thus, it may be better to screen for AF using intermittent ECG without stepwise screening using pulse palpation. A limitation of this model could be the reduced availability of handheld ECG recorders in primary care centers.

Assessment of a Machine Learning Model Applied to Harmonized Electronic Health Record Data for the Prediction of Incident Atrial Fibrillation

IMPORTANCE

Atrial fibrillation (AF) is the most common sustained cardiac arrhythmia, and its early detection could lead to significant improvements in outcomes through the appropriate prescription of anticoagulation medication. Although a variety of methods exist for screening for AF, a targeted approach, which requires an efficient method for identifying patients at risk, would be preferred.

OBJECTIVE

To examine machine learning approaches applied to electronic health record data that have been harmonized to the Observational Medical Outcomes Partnership Common Data Model for identifying risk of AF.

DESIGN, SETTING, AND PARTICIPANTS

This diagnostic study used data from 2 252 219 individuals cared for in the UCHealth hospital system, which comprises 3 large hospitals in Colorado, from January 1, 2011, to October 1, 2018. Initial analysis was performed in December 2018; follow-up analysis was performed in July 2019.

EXPOSURES

All Observational Medical Outcomes Partnership Common Data Model-harmonized electronic health record features, including diagnoses, procedures, medications, age, and sex.

MAIN OUTCOMES AND MEASURES

Classification of incident AF in designated 6-month intervals, adjudicated retrospectively, based on area under the receiver operating characteristic curve and F1 statistic.

RESULTS

Of 2 252 219 individuals (1 225 533 [54.4%] women; mean [SD] age, 42.9 [22.3] years), 28 036 (1.2%) developed incident AF during a designated 6-month interval. The machine learning model that used the 200 most common electronic health record features, including age and sex, and random oversampling with a single-layer, fully connected neural network provided the optimal prediction of 6-month incident AF, with an area under the receiver operating characteristic curve of 0.800 and an F1 score of 0.110. This model performed only slightly better than a more basic logistic regression model composed of known clinical risk factors for AF, which had an area under the receiver operating characteristic curve of 0.794 and an F1 score of 0.079.

CONCLUSIONS AND RELEVANCE

Machine learning approaches to electronic health record data offer a promising method for improving risk prediction for incident AF, but more work is needed to show improvement beyond standard risk factors.

Increasing and Evolving Role of Smart Devices in Modern Medicine

Today is an age of rapid digital integration, yet the capabilities of modern-day smartphones and smartwatches are underappreciated in daily clinical practice. Smartphones are ubiquitous, and smartwatches are very common and on the rise. This creates a wealth of information simply waiting to be accessed, studied and applied clinically, ranging from activity level to various heart rate metrics. This review considers commonly used devices, the validity and accuracy of the data they obtain and potential clinical application of the data.

Development and Validation of a Prediction Model for Atrial Fibrillation Using Electronic Health Records

OBJECTIVES

This study sought to determine whether the risk of atrial fibrillation AF can be estimated accurately by using routinely ascertained features in the electronic health record (EHR) and whether AF risk is associated with stroke.

BACKGROUND

Early diagnosis of AF and treatment with anticoagulation may prevent strokes.

METHODS

Using a multi-institutional EHR, this study identified 412,085 individuals 45 to 95 years of age without prevalent AF between 2000 and 2014. A prediction model was derived and validated for 5-year AF risk by using split-sample validation and model performance was compared with other methods of AF risk assessment.

RESULTS

Within 5 years, 14,334 individuals developed AF. In the derivation sample (7,216 AF events of 206,042 total), the optimal risk model included sex, age, race, smoking, height, weight, diastolic blood pressure, hypertension, hyperlipidemia, heart failure, coronary heart disease, valvular disease, prior stroke, peripheral arterial disease, chronic kidney disease, hypothyroidism, and quadratic terms for height, weight, and age. In the validation sample (7,118 AF events of 206,043 total) the AF risk model demonstrated good discrimination (C-statistic: 0.777; 95% confidence interval [CI:] 0.771 to 0.783) and calibration (0.99; 95% CI: 0.96 to 1.01). Model discrimination and calibration were superior to CHARGE-AF (Cohorts for Heart and Aging Research in Genomic Epidemiology AF) (C-statistic: 0.753; 95% CI: 0.747 to 0.759; calibration slope: 0.72; 95% CI: 0.71 to 0.74), C2HEST (Coronary artery disease / chronic obstructive pulmonary disease; Hypertension; Elderly [age ≥75 years]; Systolic heart failure; Thyroid disease [hyperthyroidism]) (C-statistic: 0.754; 95% CI: 0.747 to 0.762; calibration slope: 0.44; 95% CI: 0.43 to 0.45), and CHA2DS2-VASc (Congestive heart failure, Hypertension, Age ≥75 years, Diabetes mellitus, Prior stroke, transient ischemic attack [TIA], or thromboembolism, Vascular disease, Age 65-74 years, Sex category [female]) scores (C-statistic: 0.702; 95% CI: 0.693 to 0.710; calibration slope: 0.37; 95% CI: 0.36 to 0.38). AF risk discriminated incident stroke (n = 4,814; C-statistic: 0.684; 95% CI: 0.677 to 0.692) and stroke within 90 days of incident AF (n = 327; C-statistic: 0.789; 95% CI: 0.764 to 0.814).

CONCLUSIONS

A model developed from a real-world EHR database predicted AF accurately and stratified stroke risk. Incorporating AF prediction into EHRs may enable risk-guided screening for AF.

Distribution of ischemic strokes in patients with atrial fibrillation: The FibStroke Study

BACKGROUND

We aimed to determine the relative frequency of affected cerebrovascular territories in patients with atrial fibrillation (AF) suffering an ischemic stroke.

METHODS

Altogether, 1,976 patients who suffered their first-ever ischemic stroke during 2003-2012 and were diagnosed with AF either before or within 30 days after the event were included in this retrospective multicenter cohort study. Strokes were classified radiographically to be located either within the anterior or the posterior cerebrovascular territory, and the effect of the CHA₂DS₂-VASc score, oral anticoagulant (OAC) use, and timing of AF diagnosis on lesion localization was determined.

RESULTS

The median age of the patients was 78.4 (interquartile range: 71.7-84.2) years, 1,137 (57.5%) of them were women, their mean CHA₂DS₂-VASc score was 3.5 (95% confidence interval: 3.4-3.5), 656 (33.2%) were receiving OAC drugs, and altogether, 1,450 (73%) had a previous AF diagnosis. The localization of ischemic lesions between the anterior and the posterior cerebrovascular territories was not affected by the timing of AF diagnosis (p = 0.46), use of OACs (p = 0.70), or the CHA₂DS₂-VASc score (p = 0.10). Within the anterior territory, altogether 774 strokes (53.2%) were located in the left hemisphere and 3 (0.2%) were bilateral. The timing of AF diagnosis (p = 0.84), use of OACs (p = 0.90), or the CHA₂DS₂-VASc score (p = 0.21) did not affect the location of the ischemic lesion between the hemispheres.

CONCLUSIONS

The timing of AF diagnosis, use of OAC drugs, or the CHA₂DS₂-VASc score did not affect the distribution of ischemic strokes. Anterior territory strokes were slightly more often located within the left hemisphere.

Accuracy and Usability of a Novel Algorithm for Detection of Irregular Pulse Using a Smartwatch Among Older Adults: Observational Study

BACKGROUND

Atrial fibrillation (AF) is often paroxysmal and minimally symptomatic, hindering its diagnosis. Smartwatches may enhance AF care by facilitating long-term, noninvasive monitoring.

OBJECTIVE

This study aimed to examine the accuracy and usability of arrhythmia discrimination using a smartwatch.

METHODS

A total of 40 adults presenting to a cardiology clinic wore a smartwatch and Holter monitor and performed scripted movements to simulate activities of daily living (ADLs). Participants' clinical and sociodemographic characteristics were abstracted from medical records. Participants completed a questionnaire assessing different domains of the device's usability. Pulse recordings were analyzed blindly using a real-time realizable algorithm and compared with gold-standard Holter monitoring.

RESULTS

The average age of participants was 71 (SD 8) years; most participants had AF risk factors and 23% (9/39) were in AF. About half of the participants owned smartphones, but none owned smartwatches. Participants wore the smartwatch for 42 (SD 14) min while generating motion noise to simulate ADLs. The algorithm determined 53 of the 314 30-second noise-free pulse segments as consistent with AF. Compared with the gold standard, the algorithm demonstrated excellent sensitivity (98.2%), specificity (98.1%), and accuracy (98.1%) for identifying irregular pulse. Two-thirds of participants considered the smartwatch highly usable. Younger age and prior cardioversion were associated with greater overall comfort and comfort with data privacy with using a smartwatch for rhythm monitoring, respectively.

CONCLUSIONS

A real-time realizable algorithm analyzing smartwatch pulse recordings demonstrated high accuracy for identifying pulse irregularities among older participants. Despite advanced age, lack of smartwatch familiarity, and high burden of comorbidities, participants found the smartwatch to be highly acceptable.

Neuroprotective Agents in the Intensive Care Unit: -Neuroprotective Agents in ICU

Neuroprotection or prevention of neuronal loss is a complicated molecular process that is mediated by various cellular pathways. Use of different pharmacological agents as neuroprotectants has been reported especially in the last decades. These neuroprotective agents act through inhibition of inflammatory processes and apoptosis, attenuation of oxidative stress and reduction of free radicals. Control of this injurious molecular process is essential to the reduction of neuronal injuries and is associated with improved functional outcomes and recovery of the patients admitted to the intensive care unit. This study reviews neuroprotective agents and their mechanisms of action against central nervous system damages.

Detecting cerebrovascular changes in the brain caused by hypertension in atrial fibrillation group using acoustocerebrography

Acoustocerebrography is a novel, non-invasive, transcranial ultrasonic diagnostic method based on the transmission of multispectral ultrasound signals propagating through the brain tissue. Dedicated signal processing enables the estimation of absorption coefficient, frequency-dependent attenuation, speed of sound and tissue elasticity. Hypertension and atrial fibrillation are well known factors correlated with white matter lesions, intracerebral hemorrhage and cryptogenic stroke numbers. The aim of this study was to compare the acoustocerebrography signal in the brains of asymptomatic atrial fibrillation patients with and without hypertension. The study included 97 asymptomatic patients (40 female and 57 male, age 66.26 ± 6.54 years) who were clinically monitored for atrial fibrillation. The patients were divided into two groups: group I (patients with hypertension) n = 75, and group II (patients without hypertension) n = 22. Phase and amplitude of all spectral components for the received signals from the brain path were extracted and compared to the phase and amplitude of the transmitted pulse. Next, the time of flight and the attenuation of each frequency component were calculated. Additionally, a fast Fourier transformation was performed and its features were extracted. After introducing a machine learning technique, the ROC plot of differentiations between group I and group II with an AUC of 0.958 (sensitivity 0.99 and specificity 0.968) was obtained. It can be assumed that the significant difference in the acoustocerebrography signals in patients with hypertension is due to changes in the brain tissue, and it allows for the differentiating of high-risk patients with asymptomatic atrial fibrillation and hypertension.