Does early detection of atrial fibrillation reduce the risk of thromboembolic events? Rationale and design of the Heartline study.

BACKGROUND: The impact of using direct-to-consumer wearable devices as a means to timely detect atrial fibrillation (AF) and to improve clinical outcomes is unknown. METHODS: Heartline is a pragmatic, randomized, and decentralized application-based trial of US participants aged ≥65 years. Two randomized cohorts include adults with possession of an iPhone and without a history of AF and those with a diagnosis of AF taking a direct oral anticoagulant (DOAC) for ≥30 days. Participants within each cohort are randomized (3:1) to either a core digital engagement program (CDEP) via iPhone application (Heartline application) and an Apple Watch (Apple Watch Group) or CDEP alone (iPhone-only Group). The Apple Watch Group has the watch irregular rhythm notification (IRN) feature enabled and access to the ECG application on the Apple Watch. If an IRN notification is issued for suspected AF then the study application instructs participants in the Apple Watch Group to seek medical care. All participants were "watch-naïve" at time of enrollment and have an option to either buy or loan an Apple Watch as part of this study. The primary end point is time from randomization to clinical diagnosis of AF, with confirmation by health care claims. Key secondary endpoint are claims-based incidence of a 6-component composite cardiovascular/systemic embolism/mortality event, DOAC medication use and adherence, costs/health resource utilization, and frequency of hospitalizations for bleeding. All study assessments, including patient-reported outcomes, are conducted through the study application. The target study enrollment is approximately 28,000 participants in total; at time of manuscript submission, a total of 26,485 participants have been enrolled into the study. CONCLUSION: The Heartline Study will assess if an Apple Watch with the IRN and ECG application, along with application-facilitated digital health engagement modules, improves time to AF diagnosis and cardiovascular outcomes in a real-world environment. TRIAL REGISTRATION: ClinicalTrials.gov Identifier: NCT04276441.

Comparison of thromboembolic risk scores for evaluating in-hospital events of COVID-19 patients.

Aim: To compare the effectiveness of thromboembolic risk scores in determining in-hospital events of COVID-19 patients. Methods: This retrospective study included a total of 410 consecutive COVID-19 patients. Scores including CHA2DS2-VASc-HS (congestive heart failure, hypertension, age, diabetes mellitus, stroke/transient ischemic attack, vascular disease, sex, hyperlipidemia, smoking); modified R2CHA2DS2-VASc (CHA2DS2-VASc plus renal function), m-ATRIA (modified Anticoagulation and Risk Factors in Atrial Fibrillation score), ATRIA-HSV (ATRIA plus hyperlipidemia, smoking and vascular disease) and modified ATRIA-HSV were calculated. Participants were divided by in-hospital mortality status into two groups: alive and deceased. Results: Ninety-two (22.4%) patients died. Patients in the deceased group were older, predominantly male and had comorbid conditions. CHA2DS2-VASc-HS (adjusted odds ratio [aOR]: 1.31; p = 0.011), m-R2CHA2DS2-VASc (aOR: 1.33; p = 0.007), m-ATRIA (aOR: 1.18; p = 0.026), ATRIA-HSV (aOR: 1.18; p = 0.013) and m-ATRIA-HSV (aOR: 1.24; p = 0.001) scores were all associated with in-hospital mortality. m-R2CHA2DS2-VASc and modified ATRIA-HSV had the best discriminatory performance. Conclusion: We showed that m-R2CHA2DS2-VASc and m-ATRIA-HSV scores were better than the rest in predicting mortality among COVID-19 patients.

COVID-19 continues to be a pandemic that threatens human health all over the world. The main aim of our study was to examine the relationship between risk scores routinely used to determine the probability of clot formation in various cardiovascular diseases and in-hospital deaths of COVID-19 patients. The study comprised 410 adult patients hospitalized with a confirmed diagnosis of COVID-19. The clinical and laboratory data were obtained from the hospital registry system. All risk scores in the study were significantly greater in people who died from COVID-19 than in those who survived. Moreover, scoring systems that include kidney function outperformed the rest in determining in-hospital death. As a result, we discovered that specific risk scores used to indicate a person's likelihood of developing clot formation at a routine cardiology clinic are connected to in-hospital deaths among hospitalized COVID-19 patients.

Atrial Fibrillation Occurring During Acute Hospitalization: A Scientific Statement From the American Heart Association.

Acute atrial fibrillation is defined as atrial fibrillation detected in the setting of acute care or acute illness; atrial fibrillation may be detected or managed for the first time during acute hospitalization for another condition. Atrial fibrillation after cardiothoracic surgery is a distinct type of acute atrial fibrillation. Acute atrial fibrillation is associated with high risk of long-term atrial fibrillation recurrence, warranting clinical attention during acute hospitalization and over long-term follow-up. A framework of substrates and triggers can be useful for evaluating and managing acute atrial fibrillation. Acute management requires a multipronged approach with interdisciplinary care collaboration, tailoring treatments to the patient's underlying substrate and acute condition. Key components of acute management include identification and treatment of triggers, selection and implementation of rate/rhythm control, and management of anticoagulation. Acute rate or rhythm control strategy should be individualized with consideration of the patient's capacity to tolerate rapid rates or atrioventricular dyssynchrony, and the patient's ability to tolerate the risk of the therapeutic strategy. Given the high risks of atrial fibrillation recurrence in patients with acute atrial fibrillation, clinical follow-up and heart rhythm monitoring are warranted. Long-term management is guided by patient substrate, with implications for intensity of heart rhythm monitoring, anticoagulation, and considerations for rhythm management strategies. Overall management of acute atrial fibrillation addresses substrates and triggers. The 3As of acute management are acute triggers, atrial fibrillation rate/rhythm management, and anticoagulation. The 2As and 2Ms of long-term management include monitoring of heart rhythm and modification of lifestyle and risk factors, in addition to considerations for atrial fibrillation rate/rhythm management and anticoagulation. Several gaps in knowledge related to acute atrial fibrillation exist and warrant future research.

COVID-19 pandemic and trends in new diagnosis of atrial fibrillation: A nationwide analysis of claims data.

BACKGROUND: Atrial fibrillation (AF) is associated with a five-fold increased risk of stroke and a two-fold increased risk of death. We aimed to quantify changes in new diagnoses of AF following the onset of the COVID-19 pandemic. Investigating changes in new diagnoses of AF is of relevance because delayed diagnosis interferes with timely treatment to prevent stroke, heart failure, and death. METHODS: Using De-identified Optum's Clinformatics® Data Mart, we identified 19,500,401 beneficiaries continuously enrolled for 12 months in 2016-Q3 2020 with no history of AF. The primary outcome was new AF diagnoses per 30-day interval. Secondary outcomes included AF diagnosis in the inpatient setting, AF diagnosis in the outpatient setting, and ischemic stroke as initial manifestation of AF. We constructed seasonal autoregressive integrated moving average models to quantify changes in new AF diagnoses after the onset of the COVID-19 pandemic (3/11/2020, date of pandemic declaration). We tested whether changes in the new AF diagnoses differed by race and ethnicity. RESULTS: The average age of study participants was 51.0±18.5 years, and 52% of the sample was female. During the study period, 2.7% of the study sample had newly-diagnosed AF. New AF diagnoses decreased by 35% (95% CI, 21%-48%) after the onset of the COVID-19 pandemic, from 1.14 per 1000 individuals (95% CI, 1.05-1.24) to 0.74 per 1000 (95% CI, 0.64 to 0.83, p-value<0.001). New AF diagnoses decreased by 37% (95% CI, 13%- 55%) in the outpatient setting and by 29% (95% CI, 14%-43%) in the inpatient setting. The decrease in new AF diagnoses was similar across racial and ethnic subgroups. CONCLUSION: In a nationwide cohort of 19.5 million individuals, new diagnoses of AF decreased substantially following the onset of the COVID-19 pandemic. Our findings evidence pandemic disruptions in access to care for AF, which are concerning because delayed diagnosis interferes with timely treatment to prevent complications.

Prognostic value of initial electrocardiography in predicting long-term all-cause mortality in COVID-19.

BACKGROUND: The electrocardiography (ECG) has short-term prognostic value in coronavirus disease 2019 (COVID-19), yet its ability to predict long-term mortality is unknown. This study aimed to elucidate the predictive role of initial ECG on long-term all-cause mortality in patients diagnosed with COVID-19. METHODS: In this prospective cohort study, adults with COVID-19 who underwent ECG testing within a 17-hospital health system in Northeast Ohio and Florida between 03/2020-06/2020 were identified. An expert ECG reader analyzed all studies blinded to patient status. The associations of ECG characteristics with long-term all-cause mortality and intensive care unit (ICU) admission were assessed using Cox proportional hazards regression model and multivariable logistic regression models, respectively. Status of long-term mortality was adjudicated on 01/07/2022. RESULTS: Of 837 patients (median age 65 years, 51% female, 44% Black), 683 (81.6%) were hospitalized, 281 (33.6%) required ICU admission, 67 (8.0%) died in-hospital, and 206 (24.6%) died at final follow-up after a median (IQR) of 21 (9-103) days after ECG. Overall, 179 (20.7%) patients presented with sinus tachycardia, 12 (1.4%) with atrial flutter, and 45 (5.4%) with atrial fibrillation (AF). After multivariable adjustment, sinus tachycardia (E-value for HR=3.09, lower CI=2.2) and AF (E-value for HR=3.13, lower CI=2.03) each independently predicted all-cause mortality. At final follow-up, patients with AF had 64.5% probability of death compared with 20.5% for those with normal sinus rhythm (P<.0001). CONCLUSIONS: Sinus tachycardia and AF on initial ECG strongly predict long-term all-cause mortality in COVID-19. The ECG can serve as a powerful long-term prognostic tool in COVID-19.

Atrial Fibrillation and Cardiovascular Risk Assessment among COVID-19 Patients Using Different Scores.

Since the advent of severe acute respiratory syndrome-coronavirus-2 in December 2019, millions of people have been infected and succumbed to death because of this deadly virus. Cardiovascular complications such as thromboembolism and arrhythmia are predominant causes of morbidity and mortality. Different scores previously used for atrial fibrillation (AF) identification or prediction of its complications were investigated by physicians to understand whether those scores can predict in-hospital mortality or AF among patients infected with the severe acute respiratory syndromecoronavirus-2 virus. Using such scores gives hope for early prediction of atrial arrhythmia and in-hospital mortality among coronavirus disease 2019-infected patients. We have discussed the mechanisms of AF and cardiovascular damage in coronavirus disease 2019 patients, different methods of AF prediction, and compared different scores for prediction of in-hospital mortality after this viral infection.

Impact of COVID-19 on the Prescribing Pattern of Oral Anticoagulants for Atrial Fibrillation After Cardiac Surgery.

BACKGROUND: Because of logistic challenges associated with the COVID-19 pandemic, direct oral anticoagulants (DOAC) were favored over warfarin in patients presenting postoperative atrial fibrillation (AF) after cardiac surgery in our institution. Considering the limited evidence supporting the use of DOAC in this context, we sought to evaluate the safety and efficacy of this practice change. METHODS: A retrospective study was performed with patients from the Quebec City metropolitan area who were hospitalized at the Institut universitaire de cardiologie et de pneumologie de Québec-Université Laval following cardiac surgery and who required oral anticoagulant (OAC) for postoperative AF. The primary objective was to compare the pre- and peri-COVID-19 period for OAC prescribing patterns and the incidence of thrombotic and bleeding events at 3 months post-surgery. The secondary objective was to compare DOAC to warfarin in terms of thrombotic events and bleeding events. RESULTS: A total of 233 patients were included, 142 from the pre-COVID-19 and 91 from the peri-COVID-19 period, respectively. Both groups had equivalent proportions of preoperative AF (48%) and new-onset postoperative AF (52%). The proportion of patients treated with a DOAC increased from 13% pre-COVID-19 to 82% peri-COVID-19. This change in practice was not associated with a significant difference in the incidence of thrombotic or bleeding events 3 months postoperatively. However, compared to DOAC, warfarin was associated with a higher incidence of major bleeding. Only 1 thrombotic event was reported with warfarin, and none were reported with DOAC. CONCLUSION: This study suggests that DOAC are an effective and safe alternative to warfarin to treat postoperative AF after cardiac surgery and that this practice can be safely maintained.

COVID-19 increases the risk for the onset of atrial fibrillation in hospitalized patients.

COVID-19 is associated with significant extrapulmonary symptoms. Myocardial involvement has been described for infections with SARS-CoV-2 which may lead to an increase in morbidity and mortality. The objective of our study was to investigate the association of COVID-19 and atrial fibrillation (AF) or atrial flutter (AFl) in hospitalized patients. This retrospective study used electronic medical records to detect patients with COVID-19 and their comorbidities within the Mass General Brigham hospital system. All patients ≥ 18 years who were hospitalized and received a PCR test for SARS-CoV-2 were screened for inclusion as well as patients from a pre-pandemic cohort. We matched on common risk factors for AF and then used multivariable logistic regression to estimate the odds for AF or AFl. Of 78,725 patients eligible for analysis, 11,004 COVID-19 negative patients were matched to 3,090 COVID-19 positive patients and 5005 pre-pandemic patients were matched to 2283 COVID-19 positive patients. After adjusting for demographics and comorbidities, COVID-19 positive patients had 1.19 times the odds (95% CI 1.00, 1.41) of developing AF compared to COVID-19 negative patients and 1.57 times the odds (95% CI 1.23, 2.00) of developing AF compared to pre-pandemic patients. Our study demonstrated an increased risk for AF, directing the attention for improved screening and treatment regimens for the sequelae of COVID-19. While COVID-19 continues to affect many people around the world, AF may be a significant cause for morbidity and mortality. Adequate detection and treatment of AF is essential to reduce the burden of disease.

Impact of COVID-19 on patients awaiting ablation for atrial fibrillation.

OBJECTIVE: Atrial fibrillation (AF) ablation services were significantly affected by the COVID-19 pandemic. We aimed to evaluate a symptom-based clinician prioritisation scheme for waiting list management compared with patient-completed quality of life (QoL) scores. We also sought to understand factors influencing QoL, particularly the impact of COVID-19, on patients awaiting AF ablation, via a bespoke questionnaire. METHODS: Patients awaiting AF ablation were sent two QoL questionnaires (Atrial Fibrillation Effect on QualiTy of Life (AFEQT) and EuroQol 5D (EQ5D-5L)) and the bespoke questionnaire. At a separate time point, patients were categorised as C1-urgent, C2-priority or C3-routine by their cardiologist based on review of clinic letters. RESULTS: There were 118 patients included with priority categorisation available for 86 patients. Median AFEQT scores were lower in C2 (30.4; 17.2-51.9) vs C3 patients (56.5; 32.1-74.1; p<0.01). Unplanned admission occurred in 3 patients in C3 with AFEQT scores of <40. Although 65 patients had AF symptoms during the pandemic, 43.1% did not seek help where they ordinarily would have. An exercise frequency of ≥3-4 times a week was associated with higher AFEQT (56.5; 41.2-74.1; p<0.001) and EQ5D (0.84; 0.74-0.88; p<0.0001) scores. CONCLUSION: The QoL of patients awaiting AF ablation is impaired and AFEQT helps to identify patients at risk of admission, over and above physician assessment. COVID-19 influenced patients seeking medical attention with symptomatic AF when they normally would. Regular exercise is associated with better QoL in patients awaiting AF ablation.

Exploring novel algorithms for atrial fibrillation detection by driving graduate level education in medical machine learning.

During the lockdown of universities and the COVID-Pandemic most students were restricted to their homes. Novel and instigating teaching methods were required to improve the learning experience and so recent implementations of the annual PhysioNet/Computing in Cardiology (CinC) Challenges posed as a reference. For over 20 years, the challenges have proven repeatedly to be of immense educational value, besides leading to technological advances for specific problems. In this paper, we report results from the class 'Artificial Intelligence in Medicine Challenge', which was implemented as an online project seminar at Technical University Darmstadt, Germany, and which was heavily inspired by the PhysioNet/CinC Challenge 2017 'AF Classification from a Short Single Lead ECG Recording'. Atrial fibrillation is a common cardiac disease and often remains undetected. Therefore, we selected the two most promising models of the course and give an insight into the Transformer-based DualNet architecture as well as into the CNN-LSTM-based model and finally a detailed analysis for both. In particular, we show the model performance results of our internal scoring process for all submitted models and the near state-of-the-art model performance for the two named models on the official 2017 challenge test set. Several teams were able to achieve F1scores above/close to 90% on a hidden test-set of Holter recordings. We highlight themes commonly observed among participants, and report the results from the self-assessed student evaluation. Finally, the self-assessment of the students reported a notable increase in machine learning knowledge.

Non-specific intraventricular conduction delay and ventricular pre-excitation: "Pseudo-P wave", warning for it!

Atrial fibrillation (AF) is the most common cardiac arrhythmia in adults with substantial morbidity and mortality. The diagnosis of AF is established by electrocardiogram showing heart rhythm without clear P waves with irregular RR intervals. The electrocardiographic diagnosis of AF is not always easy and can still hide pitfalls even for the most experienced cardiologist. We present the case of an 86 years old patient admitted to our hospital for Covid-19 infection affected by dilated cardiomyopathy with an electrocardiogram showing a non-specific intraventricular conduction delay mimicking sinus rhythm in the presence of AF.

Atrial Fibrillation Detection and Atrial Fibrillation Burden Estimation via Wearables.

Atrial Fibrillation (AF) is an important cardiac rhythm disorder, which if left untreated can lead to serious complications such as a stroke. AF can remain asymptomatic, and it can progressively worsen over time; it is thus a disorder that would benefit from detection and continuous monitoring with a wearable sensor. We develop an AF detection algorithm, deploy it on a smartwatch, and prospectively and comprehensively validate its performance on a real-world population that included patients diagnosed with AF. The algorithm showed a sensitivity of 87.8% and a specificity of 97.4% over every 5-minute segment of PPG evaluated. Furthermore, we introduce novel algorithm blocks and system designs to increase the time of coverage and monitor for AF even during periods of motion noise and other artifacts that would be encountered in daily-living scenarios. An average of 67.8% of the entire duration the patients wore the smartwatch produced a valid decision. Finally, we present the ability of our algorithm to function throughout the day and estimate the AF burden, a first-of-this-kind measure using a wearable sensor, showing 98% correlation with the ground truth and an average error of 6.2%.

New-Onset Atrial Fibrillation in Patients Hospitalized With COVID-19: Results From the American Heart Association COVID-19 Cardiovascular Registry.

BACKGROUND: New-onset atrial fibrillation (AF) in patients hospitalized with COVID-19 has been reported and associated with poor clinical outcomes. We aimed to understand the incidence of and outcomes associated with new-onset AF in a diverse and representative US cohort of patients hospitalized with COVID-19. METHODS: We used data from the American Heart Association COVID-19 Cardiovascular Disease Registry. Patients were stratified by the presence versus absence of new-onset AF. The primary and secondary outcomes were in-hospital mortality and major adverse cardiovascular events (MACE; cardiovascular death, myocardial infarction, stroke, cardiogenic shock, and heart failure). The association of new-onset AF and the primary and secondary outcomes was evaluated using Cox proportional-hazards models for the primary time to event analyses. RESULTS: Of the first 30 999 patients from 120 institutions across the United States hospitalized with COVID-19, 27 851 had no history of AF. One thousand five hundred seventeen (5.4%) developed new-onset AF during their index hospitalization. New-onset AF was associated with higher rates of death (45.2% versus 11.9%) and MACE (23.8% versus 6.5%). The unadjusted hazard ratio for mortality was 1.99 (95% CI, 1.81-2.18) and for MACE was 2.23 (95% CI, 1.98-2.53) for patients with versus without new-onset AF. After adjusting for demographics, clinical comorbidities, and severity of disease, the associations with death (hazard ratio, 1.10 [95% CI, 0.99-1.23]) fully attenuated and MACE (hazard ratio, 1.31 [95% CI, 1.14-1.50]) partially attenuated. CONCLUSIONS: New-onset AF was common (5.4%) among patients hospitalized with COVID-19. Almost half of patients with new-onset AF died during their index hospitalization. After multivariable adjustment for comorbidities and disease severity, new-onset AF was not statistically significantly associated with death, suggesting that new-onset AF in these patients may primarily be a marker of other adverse clinical factors rather than an independent driver of mortality. Causality between the MACE composites and AF needs to be further evaluated.

ReducinG stroke by screening for UndiAgnosed atRial fibrillation in elderly inDividuals (GUARD-AF): Rationale and design of the GUARD-AF randomized trial of screening for atrial fibrillation with a 14-day patch-based continuous ECG monitor.

BACKGROUND: Screening for atrial fibrillation (AF) is attractive because AF independently raises the risk of ischemic stroke, this risk is largely reversible by long-term oral anticoagulant therapy (OAC), and many patients with AF remain undiagnosed and untreated. Recent trials of one-time brief screening for AF have not produced a significant increase in the proportion of patients diagnosed with AF. Trials of longer-term screening have demonstrated an increase in AF diagnoses, primarily paroxysmal AF. To date, however, no trials have demonstrated that screening for AF results in lower rates of stroke. Clinical practice guidelines conflict in their level of support for screening for AF. METHODS: The GUARD-AF individually randomized trial is designed to test whether screening for AF in individuals age 70 years or greater using a 2-week single-lead electrocardiographic patch monitor can identify patients with undiagnosed AF and lead to treatment with OAC, resulting in a reduced rate of stroke in the screened population. The trial's efficacy end point is hospitalization for stroke (either ischemic or hemorrhagic) and the trial's safety end point is hospitalization for a bleeding event. End points will be ascertained via Medicare claims or electronic health records at 2.5 years after study start. Enrollment is based in primary care practices and the OAC decision for screen-detected cases is left to the patient and their physician. The initial planned target sample size was 52,000, with 26,000 allocated to either screening or to usual care. RESULTS: Trial enrollment was severely hampered by the novel coronavirus disease 2019 (COVID-19) pandemic and stopped at a total enrollment of 11,931 participants. Of 5,965 randomized to the screening arm, 5,713 patients (96%) returned monitors with analyzable results. Incidence of screen-detected and clinically detected AF and associated stroke and bleeding outcomes will be ascertained. CONCLUSIONS: GUARD-AF is the largest AF screening randomized trial using a longer-term patch-based continuous electrocardiographic monitor. The results will contribute important information on the yield of patch-based AF screening, the "burden" of AF detected (percent time in AF, longest episode), and physicians' OAC decisions as a function of AF burden. GUARD-AF's stroke and bleed results will contribute to pooled trial analyses of AF screening, thereby informing future studies and guidelines.

The left atrial appendage thrombosis of in patients with persistent atrial fibrillation after the novel coronavirus infection.

Aim      To evaluate the incidence and features of left atrial appendage (LAA) thrombosis in patients with persistent atrial fibrillation (AF) after novel coronavirus infection (COVID-19).Material and methods  Percutaneous echocardiography (pcEchoCG) was performed for 128 patients with persistent AF prepared for cardioversion, 36 (28.1 %) of whom had had COVID-19. In 3 (8.3 %) patients, the lung lesion area was 50-75 %; in 31 (86.1 %) patients, 25-50 %; in 1 (2.8 %) patient, less than 25 %. One patient had no lung lesion. Median time from the onset of COVID-19 to the patient enrollment in the study was 76.5 days. At the time of enrollment, the polymerase chain reaction test for SARS-CoV-2 was negative in all patients.Results Patients after COVID-19 and those who had not had COVID-19 were comparable by age (62.5±9.2 and 62.4±9.1 years, respectively; р=0.956), gender (men 52.8 and 59.8 %, respectively; р=0.471), and risk of stroke (score 2.19±1.28 and score 1.95±1.35, respectively; р=0.350). Duration of the last arrhythmia episode was longer for patients after COVID-19 than for the comparison group (76.5 and 45.0 days, respectively; р=0.011). All patients received oral anticoagulants. 55.6 % of COVID-19 patients received rivaroxaban, whereas 62.0% of patients who had not had COVID-19 were treated with apixaban. Median duration of the anticoagulant treatment was longer for COVID-19 patients than for the comparison group (61.5 and 32.0 days; р=0.051). LAA thrombus was detected in 7 (19.4 %) patients after COVID-19 and in 6 (6.5 %) patients of the comparison group (р=0.030). In COVID-19 patients, the thrombus adhered to LAA wall over the entire thrombus length whereas in patients who had not have COVID-19, the thrombus had a free part that formed a sharp angle with LAA walls. In the presence of LAA thrombus, the LAA blood flow velocity was considerably higher for COVID-19 patients than for the comparison group (31.0±8.9 and 18.8±4.9 cm/sec, respectively; p=0.010). At the follow-up examination performed at 24.0 days on the average, the thrombus was found to be dissolved in 80 and 50% of patients after and without COVID-19, respectively (р=0.343).Conclusion      In patients with persistent AF after the novel coronavirus infection, LAA thrombosis was detected more frequently than in patients who had never had COVID-19; it was characterized by mural localization and was not associated with a decrease in LAA blood flow velocity.