Deep learning evaluation of echocardiograms to identify occult atrial fibrillation.

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

Sex Differences in High-Cost Users of Healthcare for Atrial Fibrillation.

Background: Healthcare resource use for atrial fibrillation (AF) is high, but it may not be equivalent across all patients. We examined whether sex differences exist for AF high-cost users (HCUs), who account for the top 10% of total acute care costs. Methods: All patients aged ≥ 20 years who presented to the emergency department (ED) or were hospitalized with AF were identified in Alberta, Canada, between 2011 and 2015. The cohort was categorized by sex into HCUs and non-HCUs. Healthcare utilization was defined as ED, hospital, and physician visits, and costs included those for hospitalization, ambulatory care, physician billing, and drugs. All costs were inflated to 2022 Canadian dollars (CAD$). Results: Among 48,030 AF patients, 45.1% were female. Of these, 31.8% were HCUs, and the proportions of female and male patients were equal (31.9% vs 31.7%). Female HCUs were older, more likely to have hypertension and heart failure, and had a higher stroke risk than male HCUs. Mean healthcare utilization did not differ among HCUs by sex, except for number of ED visits, which was higher in male patients (12.7% vs 9.2%, P < 0.0001). Overall, HCUs accounted for 65.8% of the total costs (CAD$3.4 billion). Almost half of total HCU costs were attributable to female HCUs (CAD$966.1 million). Significant differences were present in the distributions of HCU-related costs (male patients: 74.6% hospitalization, 9.5% ambulatory care, 12.4% physician billing, 3.5% drugs; female patients: 77.7% hospitalization, 7.4% ambulatory care, 11.5% physician billing, 3.5% drugs, P < 0.0001). Conclusions: Despite having a lower AF prevalence, female patients represent an equal proportion of HCUs, and account for almost half the total HCU costs. Interventions targeted at reducing the number of AF HCU are needed, particularly for female patients.

Contexte: L'utilisation des ressources en santé est élevée pour la fibrillation auriculaire (FA), mais elle n'est pas forcément équivalente pour tous les patients. Nous avons examiné s'il existait des différences entre les sexes pour ce qui est des cas très coûteux de FA, qui représentent les 10 % supérieurs des coûts totaux de soins de courte durée. Méthodologie: Tous les patients âgés de 20 ans et plus qui se sont présentés au service des urgences ou qui ont été hospitalisés pour une FA ont été répertoriés en Alberta, au Canada, entre 2011 et 2015. La cohorte a été divisée par sexe en fonction des utilisateurs très coûteux et des autres utilisateurs. L'utilisation des soins de santé était définie comme des consultations aux urgences, à l'hôpital ou chez le médecin, et les coûts comprenaient les hospitalisations, les soins ambulatoires, les honoraires des médecins et les médicaments. Tous les coûts ont été convertis en dollars canadiens ($ CA) de 2022. Résultats: Parmi les 48 030 patients atteints de FA, 45,1 % étaient des femmes et 31,8 % étaient des utilisateurs très coûteux, en proportions égales entre les femmes et les hommes (31,9 % vs 31,7 %). Parmi les utilisateurs très coûteux, les femmes étaient plus âgées, plus susceptibles de présenter de l'hypertension et une insuffisance cardiaque, et leur risque d'AVC était plus élevé comparativement aux hommes. L'utilisation moyenne des soins de santé n'affichait pas de différences chez les utilisateurs très coûteux selon le sexe, à l'exception des consultations aux urgences, qui étaient plus fréquentes chez les hommes (12,7 % vs 9,2 %, p < 0,0001). Dans l'ensemble, les utilisateurs très coûteux représentaient 65,8 % des coûts totaux, qui étaient de 3,4 milliards de dollars canadiens. Les femmes représentaient par ailleurs près de la moitié du total des utilisations très coûteuses (966,1 millions de dollars canadiens). Des différences significatives ont été observées quant à la répartition des coûts liés aux utilisateurs très coûteux (hommes : hospitalisations [74,6 %], soins ambulatoires [9,5 %], honoraires des médecins [12,4 %], médicaments [3,5 %]; femmes : hospitalisations [77,7 %], soins ambulatoires [7,4 %], honoraires des médecins [11,5 %], médicaments [3,5 %], p < 0,0001). Conclusions: Bien que la FA soit moins fréquente chez les femmes que chez les hommes, celles-ci représentent une proportion tout aussi importante des utilisations très coûteuses et comptent pour presque la moitié des coûts totaux attribuables aux utilisateurs très coûteux. Des interventions visant à réduire les utilisations très coûteuses pour la FA sont donc nécessaires, particulièrement chez les femmes.

Electrocardiographic deep learning for predicting post-procedural mortality: a model development and validation study.

BACKGROUND: Preoperative risk assessments used in clinical practice are insufficient in their ability to identify risk for postoperative mortality. Deep-learning analysis of electrocardiography can identify hidden risk markers that can help to prognosticate postoperative mortality. We aimed to develop a prognostic model that accurately predicts postoperative mortality in patients undergoing medical procedures and who had received preoperative electrocardiographic diagnostic testing. METHODS: In a derivation cohort of preoperative patients with available electrocardiograms (ECGs) from Cedars-Sinai Medical Center (Los Angeles, CA, USA) between Jan 1, 2015 and Dec 31, 2019, a deep-learning algorithm was developed to leverage waveform signals to discriminate postoperative mortality. We randomly split patients (8:1:1) into subsets for training, internal validation, and final algorithm test analyses. Model performance was assessed using area under the receiver operating characteristic curve (AUC) values in the hold-out test dataset and in two external hospital cohorts and compared with the established Revised Cardiac Risk Index (RCRI) score. The primary outcome was post-procedural mortality across three health-care systems. FINDINGS: 45 969 patients had a complete ECG waveform image available for at least one 12-lead ECG performed within the 30 days before the procedure date (59 975 inpatient procedures and 112 794 ECGs): 36 839 patients in the training dataset, 4549 in the internal validation dataset, and 4581 in the internal test dataset. In the held-out internal test cohort, the algorithm discriminates mortality with an AUC value of 0·83 (95% CI 0·79-0·87), surpassing the discrimination of the RCRI score with an AUC of 0·67 (0·61-0·72). The algorithm similarly discriminated risk for mortality in two independent US health-care systems, with AUCs of 0·79 (0·75-0·83) and 0·75 (0·74-0·76), respectively. Patients determined to be high risk by the deep-learning model had an unadjusted odds ratio (OR) of 8·83 (5·57-13·20) for postoperative mortality compared with an unadjusted OR of 2·08 (0·77-3·50) for postoperative mortality for RCRI scores of more than 2. The deep-learning algorithm performed similarly for patients undergoing cardiac surgery (AUC 0·85 [0·77-0·92]), non-cardiac surgery (AUC 0·83 [0·79-0·88]), and catheterisation or endoscopy suite procedures (AUC 0·76 [0·72-0·81]). INTERPRETATION: A deep-learning algorithm interpreting preoperative ECGs can improve discrimination of postoperative mortality. The deep-learning algorithm worked equally well for risk stratification of cardiac surgeries, non-cardiac surgeries, and catheterisation laboratory procedures, and was validated in three independent health-care systems. This algorithm can provide additional information to clinicians making the decision to perform medical procedures and stratify the risk of future complications. FUNDING: National Heart, Lung, and Blood Institute.

Risk Factors for the Development of New-Onset Persistent Atrial Fibrillation: Subanalysis of the VITAL Study.

BACKGROUND: Sustained forms of atrial fibrillation (AF) are associated with lower treatment success rates and poorer prognosis compared with paroxysmal AF. Yet, little is known about risk factors that predispose to persistent AF on initial presentation. Our objective was to define risk factors associated with new-onset persistent AF. METHODS: We prospectively examined the differential associations between lifestyle, clinical, and socioeconomic risk factors and AF pattern (persistent versus paroxysmal) at the time of diagnosis among 25 119 participants without a history of cardiovascular disease, AF, or cancer in the VITAL rhythm study (Vitamin D and Omega-3). RESULTS: During a median follow-up of 5.3 years, 900 participants developed AF and 346 (38.4%) were classified as persistent at the time of diagnosis. In multivariable competing risk models, increasing age, male sex, White race, height, weight, body mass index ≥30 kg/m2, hypertension, current or past smoking, alcohol intake ≥2 drinks/day, postcollege education, and randomized treatment with vitamin D were significantly associated with incident persistent AF. Compared with paroxysmal AF, increasing age, male sex, weight, body mass index ≥30 kg/m2, and postcollege education were more strongly associated with persistent AF in multivariable models regardless of whether interim cardiovascular disease and heart failure events were censored. CONCLUSIONS: In a prospective cohort without baseline AF or cardiovascular disease, over one-third of AF at the time of diagnosis is persistent. Older age, male sex, postcollege education, and obesity were preferentially associated with persistent AF and represent a high-risk AF subset for population-based intervention.

Rationale and Design of the Randomized Bayesian Multicenter COME-TAVI Trial in Patients With a New Onset Left Bundle Branch Block.

Patients with new-onset left bundle branch block (LBBB) after transcatheter aortic valve implantation (TAVI) are at risk of developing delayed high-degree atrioventricular block. Management of new-onset LBBB post-TAVI remains controversial. In the Comparison of a Clinical Monitoring Strategy Versus Electrophysiology-Guided Algorithmic Approach in Patients With a New LBBB After TAVI (COME-TAVI) trial, consenting patients with new-onset LBBB that persists on day 2 after TAVI, meeting exclusion/inclusion criteria, are randomized to an electrophysiological study (EPS)-guided approach or 30-day electrocardiographic monitoring. In the EPS-guided approach, patients with a His to ventricle (HV) interval ≥ 65 ms undergo permanent pacemaker implantation. Patients randomized to noninvasive monitoring receive a wearable continuous electrocardiographic recording and transmitting device for 30 days. Follow-up will be performed at 3, 6, and 12 months. The primary endpoint is a composite outcome designed to capture net clinical benefit. The endpoint incorporates major consequences of both strategies in patients with new-onset LBBB after TAVI, as follows: (i) sudden cardiac death; (ii) syncope; (iii) atrioventricular conduction disorder requiring a pacemaker (for a class I or IIa indication); and (iv) complications related to the pacemaker or EPS. The trial incorporates a Bayesian design with a noninformative prior, outcome-adaptive randomization (initially 1:1), and 2 prespecified interim analyses once 25% and 50% of the anticipated number of primary endpoints are reached. The trial is event-driven, with an anticipated upper limit of 452 patients required to reach 77 primary outcome events over 12 months of follow-up. In summary, the aim of this Bayesian multicentre randomized trial is to compare 2 management strategies in patients with new-onset LBBB post-TAVI-an EPS-guided approach vs noninvasive 30-day monitoring. Trial registration number: NCT03303612.

Les patients chez qui un bloc de branche gauche (BBG) est récemment apparu à la suite de l'implantation valvulaire aortique par cathéter (IVAC) présentent un risque de bloc auriculoventriculaire de haut degré tardif. La prise en charge d'un BBG récemment apparu après une IVAC demeure controversée. Dans le cadre de l'essai COME-TAVI (Comparison of a ClinicalMonitoring Strategy VersusElectrophysiology-Guided Algorithmic Approach in Patients With a New LBBB AfterTAVI, ou comparaison d'une stratégie de surveillance clinique, par rapport à une approche guidée par étude électrophysiologique et fondée sur un algorithme, chez des patients présentant un BBG d'apparition récente à la suite d'une IVAC), des patients qui présentent un BBG d'apparition récente persistant le 2e jour après une IVAC, qui répondent aux critères d'admissibilité et qui ont donné leur consentement sont répartis aléatoirement pour être suivis à l'aide d'une approche guidée par une étude électrophysiologique (EEP) ou faire l'objet d'une surveillance électrocardiographique d'une durée de 30 jours. Un stimulateur cardiaque est implanté chez les patients du groupe de l'EEP dont l'intervalle HV (temps de conduction dans le tronc du faisceau de His jusqu'aux ventricules) est ≥ 65 ms. Les patients du groupe de surveillance non invasive reçoivent un dispositif portable d'enregistrement et de transmission continue de données électrocardiographiques pour une période de 30 jours. Le suivi sera réalisé aux 3e, 6e et 12e mois. Le critère d'évaluation principal est un paramètre composite conçu afin de saisir le bienfait clinique net. Il comprend les conséquences majeures des deux stratégies chez les patients présentant un BBG d'apparition récente après une IVAC, comme suit : (i) mort subite d'origine cardiaque; (ii) syncope; (iii) trouble de la conduction auriculoventriculaire nécessitant la pose d'un stimulateur cardiaque (pour une indication de classe I ou IIa); et (iv) complications relatives au stimulateur cardiaque ou à l'EEP. L'essai intègre une conception bayésienne avec une répartition aléatoire (dans un rapport initial de 1:1) antérieure non informative adaptée aux résultats et deux analyses intermédiaires définies au préalable lorsque 25 % et 50 % du nombre anticipé des critères d'évaluation principaux seront atteints. L'essai est axé sur les événements, et la limite supérieure anticipée pour atteindre 77 événements relatifs aux critères d'évaluation principaux sur 12 mois de suivi est de 452 patients. En résumé, l'objectif de cet essai bayésien multicentrique à répartition aléatoire est de comparer deux stratégies de prise en charge de patients présentant un BBG d'apparition récente après une IVAC, soit une approche guidée par une EEP, par rapport à une surveillance non invasive de 30 jours. Trial registration number: NCT03303612.

Relationship between baseline electrocardiographic measurements and outcomes in patients with high-risk heart failure: Insights from the VerICiguaT Global Study in Subjects with Heart Failure with Reduced Ejection Fraction (VICTORIA) trial.

AIMS: Whether electrocardiographic (ECG) measurements predict mortality in chronic heart failure with reduced ejection fraction (HFrEF) is unknown. METHODS AND RESULTS: We studied 4880 patients from the Vericiguat Global Study in Subjects with Heart Failure with Reduced Ejection Fraction (VICTORIA) trial with a baseline 12-lead ECG. Associations between ECG measurements and mortality were estimated as hazard ratios (HR) and adjusted for the Meta-Analysis Global Group in Chronic Heart Failure (MAGGIC) risk score, N-terminal pro-B-type natriuretic peptide, and index event. Select interactions between ECG measurements, patient characteristics and mortality were examined. Over a median of 10.8 months, there were 824 cardiovascular (CV) deaths (214 sudden) and 1005 all-cause deaths. Median age was 68 years (interquartile range [IQR] 60-76), 24% were women, median ejection fraction was 30% (IQR 23-35), 41% had New York Heart Association class III/IV, and median MAGGIC score was 24 (IQR 19-28). After multivariable adjustment, significant associations existed between heart rate (per 5 bpm: HR 1.02), QRS duration (per 10 ms: HR 1.02), absence of left ventricular hypertrophy (HR 0.64) and CV death, and similarly so with all-cause death (HR 1.02; HR 1.02; HR 0.61, respectively). Contiguous pathologic Q waves were significantly associated with sudden death (HR 1.46), and right ventricular hypertrophy with all-cause death (HR 1.44). The only sex-based interaction observed was for pathologic Q waves on CV (men: HR 1.05; women: HR 1.64, pinteraction = 0.024) and all-cause death (men: HR 0.99; women: HR 1.57; pinteraction = 0.010). Whereas sudden death doubled in females, it did not differ among males (male: HR 1.25, 95% confidence interval [CI] 0.87-1.79; female: HR 2.50, 95% CI 1.23-5.06; pinteraction = 0.141). CONCLUSION: Routine ECG measurements provide additional prognostication of mortality in high-risk HFrEF patients, particularly in women with contiguous pathologic Q waves.

Kidney function monitoring and trajectories in patients with atrial fibrillation.

BACKGROUND: Atrial fibrillation (AF) and chronic kidney disease (CKD) frequently co-exist. The frequency of kidney monitoring and range of kidney function in patients with AF in clinical practice are uncertain. METHODS: All adult Albertans with AF between 2008 and 2017 were identified using ICD-9 and -10 codes 427.3 and I48. Kidney Disease Improving Global Outcomes (KDIGO) risk categories were defined using eGFR by the Chronic Kidney Disease Epidemiology Collaborative equation and albuminuria results within 6 months of eGFR measurement. eGFR trajectories were compared from baseline to maximum value within the following year. RESULTS: Among 105,946 patients with AF, 16.0% were KDIGO category G1 (eGFR ≥ 90), 49.0% G2 (60-89.9), 19.8% G3a (45-59.9), 11.4% G3b (30-44.9), and G4 3.8% (15-29.9). Albuminuria was normal/mild 83.4%, moderate 11.7%, and severe 4.9%. Kidney monitoring was more common among people with lower eGFR and worse albuminuria, from approximately twice annually for G1-2/A1-2 to 8 times annually in stage G4A3. Approximately 60-80% of patients received guideline-recommended monitoring, consistent across KDIGO stages. With lower baseline eGFR, annual change in eGFR decreased while the relative proportion of patients who worsened compared to improved increased: for baseline eGFR 60-89.9, 16.7% worsened vs 6.7% improved, but for eGFR 30-44.9, 8.8% worsened but only 1.0% improved. CONCLUSION: The frequency of kidney function monitoring in patients with AF increased with worsening KDIGO risk category and adhered to KDIGO guidelines in approximately three quarters of patients. A minority of patients had moderate to severe eGFR impairment, of whom most remained stable over 1 year.

Deep learning-based electrocardiographic screening for chronic kidney disease.

BACKGROUND: Undiagnosed chronic kidney disease (CKD) is a common and usually asymptomatic disorder that causes a high burden of morbidity and early mortality worldwide. We developed a deep learning model for CKD screening from routinely acquired ECGs. METHODS: We collected data from a primary cohort with 111,370 patients which had 247,655 ECGs between 2005 and 2019. Using this data, we developed, trained, validated, and tested a deep learning model to predict whether an ECG was taken within one year of the patient receiving a CKD diagnosis. The model was additionally validated using an external cohort from another healthcare system which had 312,145 patients with 896,620 ECGs between 2005 and 2018. RESULTS: Using 12-lead ECG waveforms, our deep learning algorithm achieves discrimination for CKD of any stage with an AUC of 0.767 (95% CI 0.760-0.773) in a held-out test set and an AUC of 0.709 (0.708-0.710) in the external cohort. Our 12-lead ECG-based model performance is consistent across the severity of CKD, with an AUC of 0.753 (0.735-0.770) for mild CKD, AUC of 0.759 (0.750-0.767) for moderate-severe CKD, and an AUC of 0.783 (0.773-0.793) for ESRD. In patients under 60 years old, our model achieves high performance in detecting any stage CKD with both 12-lead (AUC 0.843 [0.836-0.852]) and 1-lead ECG waveform (0.824 [0.815-0.832]). CONCLUSIONS: Our deep learning algorithm is able to detect CKD using ECG waveforms, with stronger performance in younger patients and more severe CKD stages. This ECG algorithm has the potential to augment screening for CKD.

Chronic kidney disease (CKD) is a common condition involving loss of kidney function over time and results in a substantial number of deaths. However, CKD often has no symptoms during its early stages. To detect CKD earlier, we developed a computational approach for CKD screening using routinely acquired electrocardiograms (ECGs), a cheap, rapid, non-invasive, and commonly obtained test of the heart's electrical activity. Our model achieved good accuracy in identifying any stage of CKD, with especially high accuracy in younger patients and more severe stages of CKD. Given the high global burden of undiagnosed CKD, novel and accessible CKD screening strategies have the potential to help prevent disease progression and reduce premature deaths related to CKD.

The Seventh Prevention of Syncope Trial (POST VII)-A randomized clinical trial of atomoxetine for the prevention of vasovagal syncope: Rationale and study design.

BACKGROUND: Vasovagal syncope (VVS) is common, recurs, and is associated with markedly reduced quality of life, anxiety, and frequent injuries. The few pharmacological therapies for VVS proven to have a moderate benefit in reducing recurrences are limited to patients without coexisting conditions such as hypertension or heart failure. Although there is some data to suggest Atomoxetine, a norepinephrine reuptake transport inhibitor (NET), may be a promising treatment option, an adequately powered randomized placebo-controlled trial is needed. STUDY DESIGN: POST VII is a multicenter, randomized, double-blind, placebo-controlled, crossover study that will randomize 180 patients with VVS and at least 2 syncopal spells in the preceding year to a target daily dose of atomoxetine 80 mg daily or to a matching placebo, with an observation period of 6 months in each phase and with a 1-week washout period between phases. The primary end point will be the proportion of patients with at least one syncope recurrence in each arm analyzed with an intention-to-treat approach. The secondary end points include total syncope burden, quality of life, cost, and cost-effectiveness. POWER CALCULATIONS: Assuming a 33% relative risk reduction in syncope recurrence with atomoxetine, and a dropout rate of 16%, the enrollment of 180 patients will give an 85% power of reaching a positive conclusion about atomoxetine, with P = .05. CONCLUSIONS: This will be the first adequately powered trial to determine whether atomoxetine is effective in preventing VVS. If proven effective, atomoxetine might become the first-line pharmacological treatment for recurrent VVS.

Towards artificial intelligence-based learning health system for population-level mortality prediction using electrocardiograms.

The feasibility and value of linking electrocardiogram (ECG) data to longitudinal population-level administrative health data to facilitate the development of a learning healthcare system has not been fully explored. We developed ECG-based machine learning models to predict risk of mortality among patients presenting to an emergency department or hospital for any reason. Using the 12-lead ECG traces and measurements from 1,605,268 ECGs from 748,773 healthcare episodes of 244,077 patients (2007-2020) in Alberta, Canada, we developed and validated ResNet-based Deep Learning (DL) and gradient boosting-based XGBoost (XGB) models to predict 30-day, 1-year, and 5-year mortality. The models for 30-day, 1-year, and 5-year mortality were trained on 146,173, 141,072, and 111,020 patients and evaluated on 97,144, 89,379, and 55,650 patients, respectively. In the evaluation cohort, 7.6%, 17.3%, and 32.9% patients died by 30-days, 1-year, and 5-years, respectively. ResNet models based on ECG traces alone had good-to-excellent performance with area under receiver operating characteristic curve (AUROC) of 0.843 (95% CI: 0.838-0.848), 0.812 (0.808-0.816), and 0.798 (0.792-0.803) for 30-day, 1-year and 5-year prediction, respectively; and were superior to XGB models based on ECG measurements with AUROC of 0.782 (0.776-0.789), 0.784 (0.780-0.788), and 0.746 (0.740-0.751). This study demonstrates the validity of ECG-based DL mortality prediction models at the population-level that can be leveraged for prognostication at point of care.

Atomoxetine for suppression of vasovagal syncope.

OBJECTIVE: Vasovagal syncope (VVS) is a common clinical condition with few effective medical therapies. The study aimed to evaluate the effectiveness of atomoxetine in suppressing syncope in patients with recurrent VVS. METHODS: This was a retrospective, open-label, observational case series of 12 patients taking atomoxetine for suppression of recurrent vasovagal syncope. We compared syncope frequency in the 1 year before atomoxetine and while subjects were taking atomoxetine. We used novel applications of the Poisson distribution to describe the results as a collection of n = 1 studies. RESULTS: There were 12 subjects, eight female, with a mean age 47 ± 22 years and a mean Calgary Syncope Symptom Score of 2 (diagnostic of vasovagal syncope). The patients received a mean dose of atomoxetine of 66 ± 16 mg (1.06 ± 0.21 mg/kg). The mean follow-up period was 1.21 ± 1.01 years. While taking atomoxetine, 11/12 patients appeared to improve and 7/12 had no syncope in follow-up (p = 0.0046). The annualized syncope frequency decreased from a median 5.5 (IQR 4, 6.75) syncope per year to 0 (IQR 0, 0.88) syncope per year (p = 0.002, Wilcoxon rank-sum test). According to the Poisson distribution, 7/12 subjects significantly improved with p values of < 0.0001 to 0.0235, 3/12 did not faint but had too brief follow-up times to detect significance, and 2/12 did not improve significantly. CONCLUSIONS: In this case series, atomoxetine was a promising oral agent for the prevention of vasovagal syncope. The Poisson distribution permits individual patient-level assessment of improvement and detects insufficient follow-up despite apparent improvement.

Polygenic Risk Score Predicts Sudden Death in Patients With Coronary Disease and Preserved Systolic Function.

BACKGROUND: A familial predisposition to sudden and/or arrhythmic death (SAD) in the setting of coronary artery disease (CAD) exists; however, the genetic basis is poorly understood. OBJECTIVES: The purpose of this study was to determine whether a genome-wide polygenic score for coronary artery disease (GPSCAD) might have utility in SAD risk stratification in CAD patients without severe systolic dysfunction. METHODS: A previously validated GPSCAD was generated utilizing genome-wide genotyping in 4,698 PRE-DETERMINE participants of European ancestry with CAD and left ventricular ejection fraction >30%-35%. The population was dichotomized according to top GPSCAD decile as defined by the general population, and absolute, proportional, and relative risks for SAD and non-SAD were estimated using competing risk analyses. RESULTS: Over a median follow-up of 8.0 years, participants in the top GPSCAD decile were at elevated absolute SAD risk (8.0%; 95% CI: 5.1%-12.4% vs 4.8%; 95% CI: 3.3%-7.0%; P = 0.005) and proportional SAD risk (29% vs 16%; P = 0.0003) compared with the remainder. After controlling for left ventricular ejection fraction, clinical factors, and electrocardiogram parameters, the top GPSCAD decile was associated with SAD (subdistribution HR: 1.77; 95% CI: 1.23-2.54; P = 0.002) but not non-SAD (subdistribution HR: 1.00; 95% CI: 0.80-1.25; P = 0.98) (P for Δ = 0.003). The addition of the top GPSCAD decile to the multivariable model significantly improved net reclassification indexes (NRIs) (continuous NRI: 14.0%; P = 0.024; and categorical NRI: 6.6%; P = 0.005) but not the C-index (difference in C-index: 0.007; P = 0.143). CONCLUSIONS: Among CAD patients without severe systolic dysfunction, high GPSCAD specifically predicted SAD and enriched for both absolute and proportional SAD risk, identifying a population who might benefit from defibrillator therapy.

Nationwide Study of Sex Differences in Incident Heart Failure in Newly Diagnosed Nonvalvular Atrial Fibrillation.

Background: Heart failure (HF) is a leading complication of nonvalvular atrial fibrillation (NVAF), and the presence of both conditions worsens prognosis. Sex-specific associations between NVAF and outcomes focus on stroke; less is known about HF. We evaluated sex differences in incident HF in NVAF. Methods: We identified adults age ≥ 65 years hospitalized for incident NVAF without prior HF from April 2010 to March 2018 in Canada. The primary outcome was incident HF hospitalization, with a secondary composite outcome of incident HF hospitalization or all-cause mortality at 1 year. Cox proportional hazard regression models were constructed for the association between sex and outcomes, adjusting for age, comorbidities, socioeconomic status, cardioversion, and medications. Results: Of 68,909 NVAF patients, 53.8% were women. Women had a higher rate of the primary outcome (30.0% vs 25.6%, P < 0.001) and the composite outcome (39.5% vs 36.6%, P < 0.001) than men. In multivariable analysis without adjusting for medications, there was an 8% increase risk of HF (95% confidence interval [CI] 1.05-1.11, P < 0.001) for women, which was attenuated when accounting for medication (hazard ratio [HR] 1.01, 95% CI 0.98-1.04). After full adjustment, women age ≥ 75 years were at higher risk of the primary outcome (HR 1.10, 95% CI 1.06-1.13, P < 0.001) and the composite outcome (HR 1.04, 95% CI 1.01-1.07, P < 0.001), compared with men, whereas there was a significantly lower risk for those age 65-75 years. Conclusions: In this nationwide study of incident NVAF without HF, women age ≥ 75 years were more likely to develop HF or die than men. Strategies to prevent HF in older women with NVAF are needed.

Contexte: L'insuffisance cardiaque (IC) est une complication majeure de la fibrillation auriculaire non valvulaire (FANV), et la présence des deux affections assombrit le pronostic. Les associations entre la FANV et ses complications en fonction du sexe ont surtout porté sur l'AVC; on en connaît moins sur l'IC. Nous avons évalué les différences entre les sexes pour l'IC fortuite dans la FANV. Méthodologie: Nous avons identifié des adultes de ≥ 65 ans, sans antécédents d'IC, hospitalisés pour une FANV fortuite entre avril 2010 et mars 2018 au Canada. L'hospitalisation à la suite d'une IC fortuite constituait le critère d'évaluation principal, le critère d'évaluation secondaire composé comprenait les hospitalisations pour un épisode d'IC fortuite ou le décès toutes causes confondues à un an. Des modèles de régression à risques proportionnels de Cox ont servi à évaluer l'association entre le sexe et les résultats, après correction en fonction de l'âge, des comorbidités, de la situation socio-économique, de la cardioversion et de la médication. Résultats: Le groupe étudié comptait 68 909 patients atteints de FANV dont 53,8 % étaient des femmes. Les femmes étaient plus nombreuses à répondre au critère d'évaluation principal (30,0 % vs 25,6 %, p < 0,001) et au critère d'évaluation composé (39,5 % vs 36,6 %, p < 0,001). Dans une analyse multivariée ne comportant aucune correction en fonction de la médication, une augmentation de 8 % du risque d'IC (intervalle de confiance [IC] à 95 % : 1,05-1,11, p < 0,001) a été notée chez les femmes. Cette augmentation se trouvait atténuée lorsque la médication était prise en compte (rapport des risques instantanés [RRI] : 1,01, IC à 95 % : 0,98-1,04). Après correction complète, les femmes de ≥ 75 ans ont été associées à un risque plus élevé d'atteindre le critère d'évaluation principal (RRI : 1,10, IC à 95 % : 1,06-1,13, p < 0,001) et le critère d'évaluation composé (RRI : 1,04, IC à 95 % : 1,01-1,07, p < 0,001) comparativement aux hommes; en revanche, le risque était significativement plus faible chez les femmes de 65-75 ans. Conclusions: Dans cette étude nationale sur la FANV fortuite sans IC, les femmes de ≥ 75 ans étaient plus susceptibles de développer une IC ou de décéder que les hommes d'où la nécessité de mettre en place des stratégies de prévention de l'IC chez les femmes plus âgées atteintes de FANV.

The State of Heart Failure Care in Canada: Minimal Improvement in Readmissions Over Time Despite an Increased Number of Evidence-Based Therapies.

Background: An unanswered question is whether the combination of advances in medical and device therapy over the past decade has translated into improved outcomes for patients with heart failure (HF) in Canada. Methods: The Canadian Institute for Health Information (CIHI) Hospital Morbidity Database was used to identify hospitalizations for HF among patients aged 18 years and older in Canadian hospitals during fiscal years 2009/2010 and 2018/2019. We assessed interprovincial differences in age, sex, length of stay (LOS), discharge disposition, type of admitting hospital, and most responsible service, for all HF admissions. National and provincial rates of HF admissions and all-cause 30-day readmissions were calculated. Results: After adjusting for age, the rate of HF admissions in Canada was 216 per 100,000 population in 2009/2010 and 2018/2019. The majority of patients with HF were admitted to general internal medicine and community hospitals in both 2009/2010 and 2018/2019. The national, crude, all-cause 30-day readmission rate stayed constant at 20.6%, and the majority of patients were readmitted with the diagnosis of HF in both 2009/2010 (62.5%) and 2018/2019 (59.0%). Median and interquartile range of HF LOS also remained unchanged at 7 days (3-14). Conclusions: The national rate of HF admissions, 30-day readmissions, and HF LOS have remained unchanged from 2009/2010 to 2018/2019, despite advances in medical and device therapy during this timeframe.

Introduction: La question demeure de savoir si, au cours de la dernière décennie au Canada, la combinaison des avancées dans les traitements médicaux et à l'aide d'un dispositif s'est traduite par de meilleurs résultats cliniques chez les patients atteints d'insuffisance cardiaque (IC). Méthodes: Nous avons utilisé la base de données sur la morbidité hospitalière de l'Institut canadien d'information sur la santé (ICIS) pour recenser les hospitalisations de patients atteints d'IC âgés de 18 ans et plus dans les hôpitaux du Canada au cours des années financières 2009/2010 et 2018/2019. Nous avons évalué les différences interprovinciales selon l'âge, le sexe, la durée du séjour (DDS), l'état à la sortie, le type d'hôpital à l'admission et le service le plus tenu à la prise en charge du patient, de toutes les admissions liées à l'IC. Nous avons calculé les taux provinciaux et national des admissions liées à l'IC et les réadmissions toutes causes confondues dans les 30 jours. Résultats: Après ajustement en fonction de l'âge, le taux d'admissions liées à l'IC au Canada était de 216 pour 100 000 habitants en 2009/2010 et en 2018/2019. La majorité des patients atteints d'IC avaient été admis en médecine interne générale et dans les hôpitaux communautaires en 2009/2010 et en 2018/2019. Le taux national, brut, toutes causes confondues de réadmissions dans les 30 jours était resté constant à 20,6 %, et la majorité des patients avaient eu des réadmissions liées au diagnostic d'IC en 2009/2010 (62,5 %) et en 2018/2019 (59,0 %). L'écart interquartile et la médiane de la DDS liée à l'IC étaient aussi demeurés inchangés après 7 jours (3-14). Conclusions: Le taux national des admissions liées à l'IC, les réadmissions dans les 30 jours et la DDS liée à l'IC étaient demeurés inchangés de 2009/2010 à 2018/2019, malgré les avancées des traitements médicaux et à l'aide d'un dispositif durant cette période de temps.

Trends in Uptake and Adherence to Oral Anticoagulation for Patients With Incident Atrial Fibrillation at High Stroke Risk Across Health Care Settings.

Background Oral anticoagulation (OAC) therapy prevents morbidity and mortality in nonvalvular atrial fibrillation; whether location of diagnosis influences OAC uptake or adherence is unknown. Methods and Results Retrospective cohort study (2008-2019), identifying adults with incident nonvalvular atrial fibrillation across health care settings (emergency department, hospital, outpatient) at high risk of stroke. OAC uptake and adherence via proportion of days covered for direct OACs and time in therapeutic range for warfarin were measured. Proportion of days covered was categorized as low (0-39%), intermediate (40-79%), and high (80-100%). Warfarin control was defined as time in therapeutic range ≥65%. All-cause mortality was examined at a 3-year landmark. Among 75 389 patients with nonvalvular atrial fibrillation (47.0% women, mean 77.4 years), 19.7% were diagnosed in the emergency department, 59.1% in the hospital, and 21.2% in the outpatient setting. Ninety-day OAC uptake was 51.6% in the emergency department, 50.9% in the hospital, and 67.9% in the outpatient setting (P<0.0001). High direct OAC adherence increased from 64.9% to 80.3% in the emergency department, 64.3% to 81.7% in the hospital, and 70.9% to 88.6% in the outpatient setting over time (P values for trend <0.0001). Warfarin control was 40.3% overall and remained unchanged. In multivariable analysis, outpatient diagnosis compared with the hospital was associated with greater OAC uptake (odds ratio [OR], 1.79; [95% CI, 1.72-1.87]) and direct OAC (OR, 1.42; [95% CI, 1.27-1.59]) and warfarin (OR, 1.49; [95% CI, 1.36-1.63]) adherence. Varying or persistently low adherence was associated with a poor prognosis, especially for warfarin. Conclusions Locale of nonvalvular atrial fibrillation diagnosis is associated with varying OAC uptake and adherence. Interventions specific to health care settings are needed to improve stroke prevention.

Heart Rhythm Society Atrial Fibrillation Centers of Excellence Study: A survey analysis of stakeholder practices, needs, and barriers.

BACKGROUND: An integrated, coordinated, and patient-centered approach to atrial fibrillation (AF) care delivery may improve outcomes and reduce cost. OBJECTIVE: The purpose of this study was to gain a better understanding from key stakeholder groups on current practices, needs, and potential barriers to implementing optimal integrated AF care. METHODS: A series of comprehensive questionnaires were designed by the Heart Rhythm Society Atrial Fibrillation Centers of Excellence (CoE) Task Force to conduct surveys with physicians, advanced practice professionals, patients, and hospital administrators. Data collected focused on the following areas: access to care, stroke prevention, education, AF quality improvement, and AF CoE needs and barriers. Survey responses were collated and analyzed by the Task Force. RESULTS: The surveys identified 5 major unmet needs: (1) Standardized protocols, order sets, or care pathways in the emergency department or inpatient setting were uncommon (36%-42%). (2) All stakeholders agreed stroke prevention was a top priority; however, prior bleeding or risk of bleeding was the most frequent barrier for initiation. (3) Patients indicated that education on modifiable causes, AF-related complications, and lowering stroke risk is most important. (4) Less than half (43%) of the health care systems track patients with AF or treatment status. Patients reported that stroke and heart failure prevention and access to procedures were priority areas for an AF CoE. The most common barriers to implementing AF CoE identified by clinicians were administrative support (69%) and cost (52%); administrators reported physical space (43%). CONCLUSION: On the basis of the findings of this study, the Task Force identified high priority areas to develop initiatives to aid the implementation of AF CoE.