Utilizing median and maximum QTc values improves prediction of breakthrough cardiac events in pediatric long QT syndrome.

INTRODUCTION: Although prior studies indicate that a QTc > 500 ms on a single baseline 12-lead electrocardiogram (ECG) is associated with significantly increased risk of arrhythmic events in long QT syndrome (LQTS), less is known about the risk of persistent QT prolongation. We sought to determine QTc persistence and its prognostic effect on breakthrough cardiac events (BCEs) among pediatric patients treated for LQTS. METHODS: We performed a retrospective analysis of 433 patients with LQTS evaluated, risk-stratified, and undergoing active guideline-based LQTS treatment between 1999 and 2019. BCEs were defined as arrhythmogenic syncope/seizure, sudden cardiac arrest (SCA), appropriate VF-terminating ICD shock, and sudden cardiac death (SCD). RESULTS: During the median follow-up of 5.5 years (interquartile range [IQR] = 3-9), 32 (7%) patients experienced a total of 129 BCEs. A maximum QTc threshold of 520 ms and median QTc threshold of 490 ms were determined to be strong predictors for BCEs. A landmark analysis controlling for age, sex, genotype, and symptomatic status demonstrated models utilizing both the median QTc and maximum QTc demonstrated the highest discriminatory value (c-statistic = 0.93-0.95). Patients in the high-risk group (median QTc > 490 ms and maximum QTc > 520 ms) had a significantly lower BCE free survival (70%-81%) when compared to patients in both medium-risk (93%-97%) and low-risk (98%-99%) groups. CONCLUSIONS: The risk of BCE among patients treated for LQTS increases not only based upon their maximum QTc, but also their median QTc (persistence of QTc prolongation). Patients with a maximum QTc > 520 ms and median QTc > 490 ms over serial 12-lead ECGs are at the highest risk of BCE while on guideline-directed medical therapy.

An intervention strategy to improve genetic testing for dilated cardiomyopathy in a heart failure clinic.

PURPOSE: Despite its clinical implications in screening and therapy, genetic testing in dilated cardiomyopathy (DCM) is underused. This study evaluated implementing a practice intervention in a heart failure clinic to automate and streamline the process of genetic testing. METHODS: Eligible patients with DCM were compared for frequency of pretest genetic education and testing during pre- and postintervention periods. The intervention comprised automated prescheduling of a cardiovascular genomics e-consult that served as a placeholder for downstream, pretest education, testing, and post-test review of genetic results. RESULTS: Patients with DCM were more likely to undergo pretest genetic education after intervention than before intervention (33.5% vs 14.8%, P < .0001). Similarly, patients with DCM were more likely to undergo genetic testing after intervention than before intervention (27.3% vs 13.0%, P = .0006). The number of patients who were diagnosed to have likely pathogenic or pathogenic genetic variants were 2 of 21 (9.5%) and 6 of 53 (11.1%) before and after intervention, respectively, and variants were present in the following genes: FLNC, TTN, DES, LMNA, PLN, and TNNT2. CONCLUSION: An intervention strategy in a heart failure clinic to increase the rates of pretest genetic education and testing in eligible patients with DCM was feasible and efficacious and may have important implications for the management of DCM.

One-year outcomes of catheter ablation for atrial fibrillation in young patients.

BACKGROUND: Atrial fibrillation (AF) is relatively less frequent in younger patients (age < 50). Recently, studies have suggested that early restoration of sinus rhythm may lead to improved outcomes compared with rate control, however the efficacy of catheter ablation for AF in young is scarce. METHODS: We included all hospitalized patients between 18 and 50 years with a diagnosis of AF from the Nationwide Readmission Database 2016-2017 from the Healthcare Cost and Utilization Project. Demographic and comorbidity data were collected and analyzed. Outcomes assessed included one-year AF readmission rates, all-cause readmission, ischemic stroke, and all-cause mortality. Subgroup analyses were performed for all demographic and comorbidity variables. RESULTS: Overall, 52,598 patients (medium age 44, interquartile range 38-48, female 25.7%) were included in the study, including 2,146 (4.0%) who underwent catheter ablation for AF. Patients who underwent catheter ablation had a significantly lower rate of readmission for AF or any cause at one year (adjusted hazard ratios (HR) of 0.52 [95% confidence interval (CI): 0.43-0.63] and HR of 0.81 [95% CI: 0.72-0.89], respectively). There was no difference in 1-year readmission for stroke or all-cause mortality between the two groups. Subgroup analyses showed a consistent reduction in the risk of AF readmission among major demographic and comorbidity subgroups. CONCLUSION: Catheter ablation in young patients with AF was associated with a reduction in 1-year AF related and all-cause readmissions. These data merit further prospective investigation for validation, through dedicated registries and multicenter collaborations to include young AF from diverse population.

A real-world experience of atrioventricular synchronous pacing with leadless ventricular pacemakers.

AIMS: The MicraTM transcatheter pacing system (TPS) (Medtronic) is the only leadless pacemaker that promotes atrioventricular (AV) synchrony via accelerometer-based atrial sensing. Data regarding the real-world experience with this novel system are scarce. We sought to characterize patients undergoing MicraTM -AV implants, describe percentage AV synchrony achieved, and analyze the causes for suboptimal AV synchrony. METHODS: In this retrospective cohort study, electronic medical records from 56 consecutive patients undergoing MicraTM -AV implants at the Mayo Clinic sites in Minnesota, Florida, and Arizona with a minimum follow-up of 3 months were reviewed. Demographic data, comorbidities, echocardiographic data, and clinical outcomes were compared among patients with and without atrial synchronous ventricular pacing (AsVP) ≥ 70%. RESULTS: Sixty-five percent of patients achieved AsVP ≥ 70%. Patients with adequate AsVP had smaller body mass indices, a lower proportion of congestive heart failure, and prior cardiac surgery. Echocardiographic parameters and procedural characteristics were similar across the two groups. Active device troubleshooting was associated with higher AsVP. The likely reasons for low AsVP were small A4-wave amplitude, high ventricular pacing burden, and inadequate device reprogramming. Importantly, in patients with low AsVP, subjective clinical worsening was not noted during follow-up. CONCLUSION: With the increasing popularity of leadless pacemakers, it is paramount for device implanting teams to be familiar with common predictors of AV synchrony and troubleshooting with MicraTM -AV devices.

Trends in reported industry payments to physicians practicing cardiac electrophysiology from 2013 to 2018 in the United States.

INTRODUCTION: The need for transparency in financial relationships in the healthcare system, has culminated in Open Payments database, managed by the Center for Medicare and Medicaid Services (CMS). Since its inception in 2013, the trend in such payments to physicians practicing cardiac electrophysiology was not examined. METHODS AND RESULTS: Payment information reported to CMS from January 2013 to December 2018 was obtained from the publicly available Open Payments data set using the online query tool. The data were analyzed by an individual provider and by state. An in-depth analysis of payments in the year 2018 payments was performed. From 2014 to 2018, there was an 18% increase in the total number of payments reported from 88 877 payments in 2014 to 105 000 in 2018. Despite the increase in the total number of payments reported, the average payment steadily decreased over time, resulting in an overall reduction in the total amount of payments from 2014 to 2018 ($34.9 million to $28.2 million). Payments to the top 5% of individual recipients have also decreased over this time. In 2018, 2888 unique providers received reportable payments, a total of 105 000 payments, with a median payment amount of $1378 (interquartile range: $165-$5781). The majority of these payments were for food and beverage (82%) and travel/lodging (10%). The top five payers include Boston Scientific, Medtronic Vascular, Abbott Laboratories, Janssen Pharmaceuticals, and Biotronik. CONCLUSION: Among cardiac electrophysiologists, there is increased reporting of payments in the Open Payments program over time, with a notable decrease in the payment amount.

Clinical Review of the Pharmacogenomics of Direct Oral Anticoagulants.

PURPOSE: There is growing interest in the use of pharmacogenomics to optimize the safety and efficacy of anticoagulation therapy. While the pharmacogenomics of warfarin have been well-studied, the pharmacogenomics of direct oral anticoagulants (DOACs) continue to be a fledgling, but growing, field of interest. We present a pertinent clinical review of the present state of research on the pharmacogenomics of DOACs. METHODS AND RESULTS: The present article is a review of pertinent clinical and scientific research on the pharmacogenomics of DOACs between January 2008 and December 2017 using MEDLINE and the United States National Institutes of Health Clinical Trials Registry. Many studies have identified single-nucleotide polymorphisms (SNPs) in genes responsible for DOAC metabolism that impacted serum DOAC concentration but had uncertain clinical significance. CONCLUSIONS: As such, there is currently no strong evidence for the use of pharmacogenomic testing in optimizing the safety and efficacy of DOAC therapy. Nonetheless, genes of interest have been identified for each DOAC that may be of potential clinical utility. Further research is currently underway to elucidate the value of pharmacogenomics in this increasingly prescribed therapy.

Use of speckle-tracking echocardiography-derived strain and systolic strain rate measurements to predict rejection in transplant hearts with preserved ejection fraction.

BACKGROUND: Noninvasive diagnosis of allograft rejection in heart transplant recipients is challenging. The utility of 2-dimensional speckle-tracking echocardiography (2D-STE) to predict severe rejection in heart transplant recipients with preserved left ventricular ejection fraction (LVEF) was evaluated. METHODS: Adult heart transplant patients with preserved LVEF (> 55%) and severe rejection by biopsy (Rejection Grade ≥ 2R) or no rejection between 1997 and 2011 at the Mayo Clinic in Rochester, Minnesota were evaluated. Transthoracic echocardiography was performed within 1 month of the biopsy. LV global longitudinal and circumferential strain and strain rates (GLS, GLSR, GCS, and GCSR) were analyzed retrospectively. RESULTS: Of 65 patients included, 25 had severe rejection and 40 were normal transplant controls without rejection. Both groups had more men than women (64 and 75%, respectively). Baseline clinical variables were similar between the groups. Both groups had normal LVEF (64.3% vs 64.5%; P = .87). All non-strain echocardiographic variables were similar between the 2 groups. Strain analysis showed significantly increased early diastolic longitudinal strain rate (P = .02) and decreased GCS (P < .001) and GCSR (P = .02) for the rejection group compared with the control group. The area under the receiver operating characteristic curve for GCS was 0.77. With a GCS cutoff of - 17.60%, the sensitivity and specificity of GCS to detect severe acute rejection were 81.8 and 68.4%, respectively. CONCLUSIONS: 2D-STE may be useful in detecting severe transplant rejection in heart transplant patients with normal LVEF.

Management of Premature Ventricular Complexes in the Outpatient Setting.

With an aging population and an explosion in ambulatory electrocardiographic monitoring, primary care clinicians will undoubtedly see an increase in patients presenting with premature ventricular complexes (PVCs), especially given how common they are in the general population. A sizable number of patients with PVCs are asymptomatic, and these PVCs have no significant clinical implications. In contrast, PVCs can predispose patients to or are a clinical marker of an underlying cardiomyopathy, heart failure, or sudden cardiac death. Such a dichotomy can create fear in dealing with PVCs in the outpatient setting, both in immediate situations and for surveillance and follow-up. In this review, we provide a comprehensive overview of the pathophysiologic basis of PVCs, appropriate diagnostic testing, management, and prognostic considerations necessary when faced with PVCs in the outpatient clinic. We also provide a simplistic approach to help guide the initial work-up of PVCs, basic treatment strategies, and indications of when to refer for cardiovascular specialty consultation to improve physician comfort and to enhance patient care.

Antiarrhythmic drugs for atrial fibrillation in the outpatient setting.

With burgeoning evidence for early rhythm control in patients with atrial fibrillation (AF), the management of AF in the outpatient setting has become more challenging. The primary care clinician often serves as the frontline in the pharmacologic management of AF. Because of drug interactions and the risk of proarrhythmia, many clinicians remain hesitant about the initiation and chronic management of antiarrhythmic drug prescriptions. However, with the likely increased use of antiarrhythmics for early rhythm control, understanding and familiarity with these medications have likewise become more important, especially since patients with AF probably have other non-cardiac medical conditions that can impact their antiarrhythmic therapy. In this comprehensive review, we provide informative, high-yield cases and edifying references that will help primary care providers become comfortable handling various clinical scenarios.

Cardiac fludeoxyglucose-18 positron emission tomography in genotype-positive arrhythmogenic cardiomyopathy.

BACKGROUND: Myocardial inflammation contributes to the pathogenesis of arrhythmogenic cardiomyopathy (ACM), a clinically and genetically heterogenous disorder. Due to phenotypic overlap, some patients with genetic ACM may be evaluated for an underlying inflammatory cardiomyopathy. However, the cardiac fludeoxyglucose (FDG) positron emission tomography (PET) findings in ACM patients have not been elucidated. METHODS: All genotype-positive patients in the Mayo Clinic ACM registry (n = 323) who received a cardiac FDG PET were included in this study. Pertinent data were extracted from the medical record. RESULTS: Collectively, 12/323 (4%; 67% female) genotype-positive ACM patients received a cardiac PET FDG scan as part of their clinical evaluation (median age at scan 49 ± 13 years). Amongst these patients, pathogenic/likely pathogenic variants were detected in LMNA (n = 7), DSP (n = 3), FLNC (n = 1) and PLN (n = 1). Of note, 6/12 (50%) had abnormal myocardial FDG uptake, including diffuse (entire myocardium) uptake in 2/6 (33%), focal (1-2 segments) uptake in 2/6 (33%) and patchy (3+ segments) in 2/6 (33%). Median myocardial standardized uptake value ratio was 2.1. Interestingly, LMNA-positive patients accounted for 3 out of 6 (50%) positive studies (diffuse uptake in 2 and focal uptake in 1). CONCLUSION: Abnormal myocardial FDG uptake is common in genetic ACM patients undergoing cardiac FDG PET. This study further supports the role of myocardial inflammation in ACM. Further investigation is needed to determine role of FDG PET in diagnosis and management of ACM and investigate the role of inflammation in ACM.

Transvenous laser lead extraction in patients with congenital complete heart block.

BACKGROUND: Data on lead management in patients with congenital complete heart block (CCHB) with cardiac implantable electronic devices are lacking. OBJECTIVE: The purpose of this study was to describe the natural history and outcomes in patients with CCHB with cardiac implantable electronic devices undergoing transvenous lead extraction (TLE). METHODS: Data on all attempted TLE procedures in patients with CCHB at 2 institutions between 2011 and 2021 were collected from a retrospective registry. RESULTS: Overall, 16 patients (mean age at transvenous device implant 13.8 ± 4.7 years) were included. Before TLE, patients underwent an average of 2.25 ± 1.3 generator changes, 3 (19%) underwent cardiac resynchronization therapy upgrade, and 7 (44%) underwent a lead revision with subsequently abandoned leads. Mean patient age at TLE was 34.4 ± 9.4 years with a mean duration of lead implant of 19.2 ± 6.9 years. Lead malfunction (n = 11 [69%]) and infection (n = 5 [31%]) were the most common indications for TLE. A total of 38 leads were removed, with complete procedural success achieved in 14 of 16 (87.5%). Two (12.5%) major complications occurred, including right ventricular laceration and superior vena cava tear requiring sternotomies. All patients survived at 1-year follow-up. CONCLUSION: Patients with CCHB represent a unique cohort highlighted by several generator changes, lead revisions, and abandoned leads at a young age, along with a long duration of lead dwelling time and a high prevalence of lead malfunction requiring TLE. There may be a high risk of major complications during TLE, suggesting TLE should be performed only in experienced centers. Larger studies are needed to confirm these findings.

Silent cerebral infarcts in patients with atrial fibrillation: Clinical implications of an imaging-adjusted CHA2DS2-VASc score.

BACKGROUND: The CHA2DS2-VASc score does not include silent infarcts on neuroimaging in stroke risk estimation for patients with atrial fibrillation (AF). The inclusion of silent infarcts into CHA2DS2-VASc scoring and its impact on stroke prophylaxis recommendations in patients with AF has not been previously studied. The present study sought to quantify the prevalence of silent infarcts in patients with AF and describe potential changes in management based on magnetic resonance imaging (MRI) findings. METHODS: Participants from the Mayo Clinic Study of Aging with AF and brain MRI were included. Silent infarcts were identified. "Standard" CHA2DS2-VASc scores were calculated for each subject based on clinical history alone and "imaging-adjusted" CHA2DS2-VASc scores based on evidence of cerebral infarction on MRI. Standard and imaging-adjusted scores were compared. RESULTS: One hundred and forty-seven participants (average age 77, 28% female) were identified with AF, MRI, and no clinical history of stroke. Overall, 41 (28%) patients had silent infarcts on MRI, corresponding with a 2-point increase in CHA2DS2-VASc score. Of these participants, only 39% (16/41) with silent infarct were on anticoagulation despite having standard CHA2DS2-VASc scores supportive of anticoagulation. After incorporating silent infarcts, 13% (19/147) would have an indication for periprocedural bridging compared to 0.6% (1/147) at baseline. CONCLUSIONS: Incorporation of silent infarcts into the CHA2DS2-VASc score may change the risk- -benefit ratio of anticoagulation. It may also increase the number of patients who would benefit from periprocedural bridging. Future research should examine whether an anticoagulation strategy based on imaging-adjusted CHA2DS2-VASc scores could result in a greater reduction of stroke and cognitive decline.

Prediction of Atrial Fibrillation Using Machine Learning: A Review.

There has been recent immense interest in the use of machine learning techniques in the prediction and screening of atrial fibrillation, a common rhythm disorder present with significant clinical implications primarily related to the risk of ischemic cerebrovascular events and heart failure. Prior to the advent of the application of artificial intelligence in clinical medicine, previous studies have enumerated multiple clinical risk factors that can predict the development of atrial fibrillation. These clinical parameters include previous diagnoses, laboratory data (e.g., cardiac and inflammatory biomarkers, etc.), imaging data (e.g., cardiac computed tomography, cardiac magnetic resonance imaging, echocardiography, etc.), and electrophysiological data. These data are readily available in the electronic health record and can be automatically queried by artificial intelligence algorithms. With the modern computational capabilities afforded by technological advancements in computing and artificial intelligence, we present the current state of machine learning methodologies in the prediction and screening of atrial fibrillation as well as the implications and future direction of this rapidly evolving field.

Antiarrhythmic Drugs for Atrial Fibrillation in the Outpatient Setting: Common Clinical Scenarios and Pearls for the Primary Care Clinician.

The management of atrial fibrillation (AF) in the outpatient setting has become more complex with the utilization of antiarrhythmic drugs (AADs) and increasing complexity of comorbid conditions. The primary care clinician is critically involved in the pharmacologic management of AF, whether it be direct prescription of AADs or managing potential drug-drug interactions with other medications. In this review, we provide instructive, high-yield clinical scenarios and quick clinical references to increase familiarity and comfort with the use of AADs.

Spectrum bias in algorithms derived by artificial intelligence: a case study in detecting aortic stenosis using electrocardiograms.

Aims: Spectrum bias can arise when a diagnostic test is derived from study populations with different disease spectra than the target population, resulting in poor generalizability. We used a real-world artificial intelligence (AI)-derived algorithm to detect severe aortic stenosis (AS) to experimentally assess the effect of spectrum bias on test performance. Methods and results: All adult patients at the Mayo Clinic between 1 January 1989 and 30 September 2019 with transthoracic echocardiograms within 180 days after electrocardiogram (ECG) were identified. Two models were developed from two distinct patient cohorts: a whole-spectrum cohort comparing severe AS to any non-severe AS and an extreme-spectrum cohort comparing severe AS to no AS at all. Model performance was assessed. Overall, 258 607 patients had valid ECG and echocardiograms pairs. The area under the receiver operator curve was 0.87 and 0.91 for the whole-spectrum and extreme-spectrum models, respectively. Sensitivity and specificity for the whole-spectrum model was 80% and 81%, respectively, while for the extreme-spectrum model it was 84% and 84%, respectively. When applying the AI-ECG derived from the extreme-spectrum cohort to patients in the whole-spectrum cohort, the sensitivity, specificity, and area under the curve dropped to 83%, 73%, and 0.86, respectively. Conclusion: While the algorithm performed robustly in identifying severe AS, this study shows that limiting datasets to clearly positive or negative labels leads to overestimation of test performance when testing an AI algorithm in the setting of classifying severe AS using ECG data. While the effect of the bias may be modest in this example, clinicians should be aware of the existence of such a bias in AI-derived algorithms.

Lower Extremity Arterial Disease as a Predictor of Incident Atrial Fibrillation and Cardiovascular Events.

OBJECTIVE: To evaluate the relationship between peripheral arterial disease (PAD) and incident atrial fibrillation (AF) and its clinical and pathophysiologic implications on ischemic stroke and all-cause mortality. PATIENTS AND METHODS: We identified all adult patients in the Mayo Clinic Health System without a previous diagnosis of AF undergoing ankle-brachial index (ABI) testing for any indication from January 1, 1996, to June 30, 2018. Retrospective extraction of ABI data and baseline echocardiographic data was performed. The primary outcome of interest was incident AF. The secondary outcomes of interest were incident ischemic stroke and all-cause mortality. RESULTS: A total of 33,734 patients were included in the study. After adjusting for demographic and comorbidity variables, compared with patients who had normal ABI (1.0 to 1.39), there was an increased risk of incident AF in patients with low ABI (<1.0) (adjusted hazard ratio, 1.14; 95% CI, 1.06 to 1.22) and elevated ABI (≥1.4) (adjusted hazard ratio, 1.18; 95% CI, 1.06 to 1.31). The risk was greater in patients with increasing severity of PAD. Patients with abnormal ABIs had an increased risk of ischemic stroke and all-cause mortality. We found that patients with PAD and incident AF have certain baseline echocardiographic abnormalities. CONCLUSION: In this large cohort of ambulatory patients undergoing ABI measurement, patients with PAD were at increased risk for incident AF, ischemic stroke, and mortality. In these high-risk patients with abnormal ABI, particularly severe PAD and cardiac structural abnormalities, routine monitoring for AF and management of cardiovascular risk factors may be warranted.

Cost Effectiveness of an Electrocardiographic Deep Learning Algorithm to Detect Asymptomatic Left Ventricular Dysfunction.

OBJECTIVE: To evaluate the cost-effectiveness of an artificial intelligence electrocardiogram (AI-ECG) algorithm under various clinical and cost scenarios when used for universal screening at age 65. PATIENTS AND METHODS: We used decision analytic modeling to perform a cost-effectiveness analysis of the use of AI-ECG to screen for asymptomatic left ventricular dysfunction (ALVD) once at age 65 compared with no screening. This screening consisted of an initial screening decision tree and subsequent construction of a Markov model. One-way sensitivity analysis on various disease and cost parameters to evaluate cost-effectiveness at both $50,000 per quality-adjusted life year (QALY) and $100,000 per QALY willingness-to-pay threshold. RESULTS: We found that for universal screening at age 65, the novel AI-ECG algorithm would cost $43,351 per QALY gained, test performance, disease characteristics, and testing cost parameters significantly affect cost-effectiveness, and screening at ages 55 and 75 would cost $48,649 and $52,072 per QALY gained, respectively. Overall, under most of the clinical scenarios modeled, coupled with its robust test performance in both testing and validation cohorts, screening with the novel AI-ECG algorithm appears to be cost-effective at a willingness-to-pay threshold of $50,000. CONCLUSION: Universal screening for ALVD with the novel AI-ECG appears to be cost-effective under most clinical scenarios with a cost of <$50,000 per QALY. Cost-effectiveness is particularly sensitive to both the probability of disease progression and the cost of screening and downstream testing. To improve cost-effectiveness modeling, further study of the natural progression and treatment of ALVD and external validation of AI-ECG should be undertaken.

Abnormal vascular physiology in the lower extremities as a risk factor for ischemic stroke and mortality.

CONTEXT: Peripheral artery disease (PAD) is highly prevalent in the general population, affecting up to 25% of patients 55 years of age or older. There is a known association with acute ischemic stroke, but limited large cohort studies exist pertaining to the relationship between PAD severity and incident ischemic stroke. OBJECTIVES: To evaluate the risk of incident ischemic stroke and mortality along the spectrum of low and elevated ankle brachial index (ABI) measurement. METHODS: We performed a retrospective extraction of ABI data of all adult patients who underwent lower extremity physiology study for any indication from January 1, 1996 to June 30, 2018 in the Mayo Clinic health system. PAD was categorized into severe, moderate, mild, and borderline based on ABI measurements and poorly compressible arteries (PCA). These were compared with normal ABI measurements. Associations of PAD/PCA with new ischemic stroke events and all cause mortality were analyzed. Hazard ratios (HR) were calculated using multivariable Cox proportional regression with 95% confidence intervals. RESULTS: A total of 39,834 unique patients were included with a median follow up duration of 4.59 years. All abnormal ABI groups, except borderline PAD, were associated with increased risk of incident ischemic stroke after multivariate regression compared to normal ABI. A severity-dependent association was observed between PAD and ischemic stroke with moderate (HR, 1.22 [95% CI, 1.10-1.35]) and severe (HR, 1.19 [95% CI, 1.02-1.40]) categories conferring similar risk in comparison to normal ABI. Patients with PCA carried the greatest ischemic stroke risk (HR, 1.30 [95% CI, 1.15-1.46]). Similarly, abnormal ABI groups were associated with a significant risk for all cause mortality in a severity-dependent manner, with severe PAD conferring the greatest risk (HR, 3.07 [95% CI, 2.88-3.27]). CONCLUSIONS: This study adds to the growing body of evidence that both PAD and PCA are independent risk factors for incident ischemic stroke and all cause mortality. The association of PAD severity and PCA with risk of ischemic stroke may help clinicians with risk stratification and determining treatment intensity.

External validation of a deep learning electrocardiogram algorithm to detect ventricular dysfunction.

OBJECTIVE: To validate a novel artificial-intelligence electrocardiogram algorithm (AI-ECG) to detect left ventricular systolic dysfunction (LVSD) in an external population. BACKGROUND: LVSD, even when asymptomatic, confers increased morbidity and mortality. We recently derived AI-ECG to detect LVSD using ECGs based on a large sample of patients treated at the Mayo Clinic. METHODS: We performed an external validation study with subjects from the Know Your Heart Study, a cross-sectional study of adults aged 35-69 years residing in two cities in Russia, who had undergone both ECG and transthoracic echocardiography. LVSD was defined as left ventricular ejection fraction ≤ 35%. We assessed the performance of the AI-ECG to identify LVSD in this distinct patient population. RESULTS: Among 4277 subjects in this external population-based validation study, 0.6% had LVSD (compared to 7.8% of the original clinical derivation study). The overall performance of the AI-ECG to detect LVSD was robust with an area under the receiver operating curve of 0.82. When using the LVSD probability cut-off of 0.256 from the original derivation study, the sensitivity, specificity, and accuracy in this population were 26.9%, 97.4%, 97.0%, respectively. Other probability cut-offs were analysed for different sensitivity values. CONCLUSIONS: The AI-ECG detected LVSD with robust test performance in a population that was very different from that used to develop the algorithm. Population-specific cut-offs may be necessary for clinical implementation. Differences in population characteristics, ECG and echocardiographic data quality may affect test performance.

Antithrombotic Therapy for Patients With Atrial Fibrillation and Acute Coronary Syndrome or Percutaneous Coronary Intervention.

1. What is the clinical question? What combination antithrombotic therapy is recommended for patients with atrial fibrillation with acute coronary syndrome or patients undergoing percutaneous coronary intervention? 2. What does the evidence say? Double therapy (DT) with clopidogrel and direct oral anticoagulants (specifically, dabigatran, rivaroxaban, and apixaban) is noninferior to warfarin-based therapies for most patients. Double therapy is noninferior to triple therapy (TT) and has less bleeding complications. 3. What is the take-home message for physicians? According to the latest guidelines by the ACC, AHA, ESC, and HRS, in patients with AF undergoing PCI, DT with DOACs (specifically dabigatran, rivaroxaban and apixaban) plus clopidogrel is acceptable. Patients undergoing PCI or with high ischemic risk may still benefit from TT for at least 1 month and up to 6 months before switching to DT. Currently, there is no specific guidance on long-term antiplatelet therapy in these patients. Duration of antiplatelet therapy, whether with DT or TT, should be based on current DAPT guidelines (depending on indication and type of intervention) and discussions with each patient's cardiologist.