Citations

Introduction: Medicines don’t work in those who don’t take them. Although novel oral anticoagulants (NOACs) are more convenient than warfarin due to fewer drug-drug interactions and less need for laboratory monitoring, their considerable costs and lack of regular interactions with the healthcare system may also contribute to poor adherence. Little is known about the persistence and adherence in the era of NOACs, nor how such behaviors are associated with the risk of ischemic stroke and transient ischemic attack (TIA) among patients of varying baseline risk. Methods: We conducted a retrospective analysis using a large U.S. commercial insurance database, and identified 61,646 patients with atrial fibrillation who initiated one of OACs (warfarin, dabigatran, rivaroxaban and apixaban) between October 2010 and September 2014. We defined discontinuation as being off OACs for at least 3 months and adherence as the proportion of days covered of at least 80%. Cox proportional hazard models was used to examine whether the time that patients were off OACs, including both the gaps between medication fills and the time of discontinuation, increased the risk of ischemic stroke and TIA. Results: Approximately 1 in 3 patients discontinued OACs within one year after initiation and 1 in 10 switched to another OAC. The estimated likelihood of adherence was 0.77 during the time when patients were on their first-line medications. Apixaban had the highest continuation rate (65% at 1 year), while rivaroxaban had the best adherence (predicted probability of adherence 0.83). The event rate of stroke was 1.6 per 100 person years. Patients with high baseline risk (CHA2DS2-VASc ≥2) were more likely to have a stroke when they were off OACs for 1-3 months (HR=1.47, p<0.01), 3-6 months (HR=1.78, p<0.001) and ≥6 months (HR=2.16, p<0.001), compared to off OACs for less than a week. No significant effect was found among low-risk patients (CHA2DS2-VASc 0 or 1). Switching to another OAC was related to 22% increased risk of stroke (p=0.05). Conclusions: Despite their greater convenience relative to warfarin, discontinuation and nonadherence to NOACs is high. Lack of persistence and adherence was associated with increased risk of ischemic stroke and TIA among patients with elevated baseline risk.

Introduction: Exercise improves outcomes across a broad spectrum of cardiovascular disease. The optimal design, safety, and effectiveness of exercise-based interventions in ICD and CRT patients remain poorly understood. Methods: We performed a Pubmed search for clinical studies using the following search terms: “implantable cardioverter-defibrillators”; “ICD”; “cardiac resynchronization therapy”; “CRT”; and any one of the following: “activity”; “exercise”; “training”; or “rehabilitation”; from 1/1/2000 - 10/1/2015. Eligible studies were evaluated for study design features, measured endpoints, and reports of ICD shock rates. Results: From 649 articles, 75 abstracts met initial criteria from which 16 studies remained after full-text review: 56% randomized trials, 31% single-arm trials, 13% observational studies. A total of 2114 patients (median 52, range, 8 - 1053) were included. Exercise interventions varied widely in character and duration (mean days 82.6, range 23 - 168). VO2 max and other physiologic exercise performance measures were the most common primary endpoints (81%), with few studies evaluating clinical outcomes. Most studies (75%) showed statistically significant improvement in primary physiologic endpoints. ICD shocks were uncommon during active exercise intervention with only 7 shocks in 1248 patients. ICD shocks in follow-up were less common in patients receiving exercise intervention (16.9% v 25.6%, Figure). Conclusion: Exercise training in patients with ICDs and CRT appears safe and effective based on a small literature. Lack of consensus on design and both physiologic and clinical endpoints limit broader application to an important patient population.

Abstract Objective The study sought to conduct an informatics analysis on the National Evaluation System for Health Technology Coordinating Center test case of cardiac ablation catheters and to demonstrate the role of informatics approaches in the feasibility assessment of capturing real-world data using unique device identifiers (UDIs) that are fit for purpose for label extensions for 2 cardiac ablation catheters from the electronic health records and other health information technology systems in a multicenter evaluation. Materials and Methods We focused on data capture and transformation and data quality maturity model specified in the National Evaluation System for Health Technology Coordinating Center data quality framework. The informatics analysis included 4 elements: the use of UDIs for identifying device exposure data, the use of standardized codes for defining computable phenotypes, the use of natural language processing for capturing unstructured data elements from clinical data systems, and the use of common data models for standardizing data collection and analyses. Results We found that, with the UDI implementation at 3 health systems, the target device exposure data could be effectively identified, particularly for brand-specific devices. Computable phenotypes for study outcomes could be defined using codes; however, ablation registries, natural language processing tools, and chart reviews were required for validating data quality of the phenotypes. The common data model implementation status varied across sites. The maturity level of the key informatics technologies was highly aligned with the data quality maturity model. Conclusions We demonstrated that the informatics approaches can be feasibly used to capture safety and effectiveness outcomes in real-world data for use in medical device studies supporting label extensions.

Background: Multimorbidity is common in patients with atrial fibrillation (AF), yet comorbidity patterns are not well documented. Methods: The prevalence of 18 chronic conditions was obtained in patients with AF from 2013-2017 from a 27-county region in the Midwest. All patients had AF documented on an electrocardiogram or Holter monitor. To compare comorbidity patterns between patients with and without AF, controls were matched 1:1 on age (± 5 years) and sex. For AF patients and controls separately, the Somers’ D statistic was used to quantify the non-random concordance of each pair of chronic conditions beyond chance (ranging from -1 [perfect disagreement] to 1 [perfect agreement]; 0 indicating coincidental agreement by chance alone). Significance of the Somers’ D statistic was evaluated using a permutation approach with the Benjamini-Hochberg procedure for controlling the false discovery rate at 0.1%. Results: Among the 16,543 patients with AF (median age 76 years, 57% men), the most common conditions were hypertension (70%), hyperlipidemia (61%), arthritis (41%), and diabetes (40%). Many pairs of chronic conditions co-occurred more frequently than expected. However, no material differences were observed in the co-occurrence of conditions in patients with AF compared to controls (data not shown). Among patients with AF, the co-occurrence of conditions differed by age (Figure). In those ≤65 years, the strongest co-occurrence of conditions was depression/anxiety, although several condition pairs had Somers’ D statistics of >0.4. In those aged 65-74 years, hypertension/hyperlipidemia and depression/anxiety had the strongest co-occurrence, whereas hypertension/hyperlipidemia was strongest for those aged ≥75 years. Conclusion: Although differences in the co-occurrence of conditions did not exist between AF and community controls, among the patients with AF, the patterns of co-existing conditions differed by age. A better understanding of the clinical consequences of multimorbidity in AF patients is needed.

Introduction: Recent studies showed post-operative atrial fibrillation (POAF) is associated with increased stroke risk - even approaching that of unprovoked AF. This raises the question of whether patients with POAF should receive anticoagulation. We aim to compare different anticoagulation strategies in patients with POAF after cardiac and non-cardiac surgeries. Methods: Using a large national administrative database (OptumLabs Data Warehouse), we identified 33,981 patients with POAF between 1/1/2013-9/30/2019. Patients were divided to four groups based on the initial treatment within 30 days of POAF: (1) no anticoagulation (N=28,807) (2) apixaban (N=2178) (3) rivaroxaban (N=1320) (4) warfarin (N=1676). Follow up started at the 30 th day after POAF to exclude patients who died shortly after surgery and minimize immortal time bias. The follow up continued until patients changed treatment strategies, insurance, or died. 1:1 propensity score matching was performed between each anticoagulant to no treatment to balance on 86 baseline characteristics. Results: The mean age was 71.1±11.2 yr; mean CHA 2 DS 2 -VASc was 4.1±1.8; 29.1% received cardiac surgeries; 15.2% received anticoagulation within 30 days of POAF. The event rate per 100 person years was 1.58 for stroke in no-anticoagulation group, and 1.29 for anticoagulation group; 2.86 for major bleeding in no-anticoagulation group and 4.50 for anticoagulation group. After matching, apixaban and rivaroxaban were associated with a lower risk of stroke, but a higher risk of major bleeding; warfarin was not associated with a lower risk of stroke, but a higher risk of major bleeding (Figure). The effect was consistent across subgroups, e.g., age and surgery type. Conclusions: In patients with POAF, the stroke rate was lower than what was typically observed in clinical AF. Treatment with apixaban and rivaroxaban immediately after POAF was associated with a reduced risk of stroke but an increased risk of major bleeding.

Introduction: Watchman has been increasingly used in AF patients who have difficulties taking anticoagulation, but the RCTs only compared Watchman to warfarin. There was also a signal of increased ischemic stroke with Watchman in comparison to warfarin in RCTs, which made some clinicians question the fundamental premise that Watchman can reduce stroke. We aimed to compare Watchman to no anticoagulation in a large national cohort of patients in the US. Methods: We identified AF patients treated with Watchman (N=7,309) or no anticoagulation (N=1,234,543) between 2015-2017 from the OptumLabs Data Warehouse, which is the first to link private insurance, Medicare Advantage, and Medicare Fee-for-Service records at patient level longitudinally. One-to-one propensity score matching was used to balance patients on demographics and medical history. The primary outcomes were ischemic stroke or systemic embolism (hereafter referred to as stroke) and major bleeding. Secondary outcomes included all-cause mortality and intracranial bleeding. Results: In the unmatched cohort, the mean age was 76.6±6.4 yr in the Watchman group and 76.6 ±8.5 yr in the no anticoagulation group, but Watchman patients were more likely to have a history of bleeding (44.9% vs 13.7%) and intracranial bleeding (9.5% vs 2.6%). After matching, the two groups were similar on 18 baseline characteristics. Watchman was associated with a lower risk of stroke and mortality, but a higher risk of major bleeding and a similar risk of intracranial bleeding. The associations were largely consistent across subgroups, including those with relative contraindications to anticoagulation (Figure). Conclusions: In AF patients who had difficulties taking anticoagulation, Watchman offers an alternative approach to reduce stroke and mortality. The results provide important evidence to inform clinical decision making in the absence of RCTs, since 40% of AF patients in routine practice are not on anticoagulation.

Introduction: An artificial intelligence (AI) algorithm applied to electrocardiography (ECG) during normal sinus rhythm (NSR) has been shown to predict concomitant atrial fibrillation (AF). We sought to characterize the value of AI-ECG as a predictor of future AF and assess its performance compared to other clinical prediction scores in a population-based sample. Methods: We calculated the AI-ECG probability during NSR in patients who enrolled in the population-based Mayo Clinic Study of Aging with at least one ECG in NSR within two years prior and no history of AF at the time of the baseline study visit. The cumulative incidence of AF was estimated for strata defined by AI-ECG probability and CHARGE-AF score. Cox proportional hazards were fit to assess the independent prognostic value and interaction of AI-ECG probability and CHARGE-AF score. Concordance (c) statistics were calculated for AI-ECG probability, CHARGE-AF score and combined AI-ECG and CHARGE-AF score. Results: A total of 1,936 patients with a median age 75.8 (quartile range [QR] 70.4, 81.8) years, median CHARGE-AF score 14.0 (QR 13.2, 14.7) and median CHADS2VASC score 3 (QR 2, 4) were included in the analysis. The cumulative incidence of AF increased in a stepwise fashion across quartiles of AI-ECG probability and CHARGE-AF score (Figure 1). When compared in the same model, both AI-ECG probability (hazard ratio [HR] 1.76, 95% confidence interval [CI] 1.51-2.04) and CHARGE-AF score (HR 1.90, 95% CI 1.58-2.28) independently predicted AF without significant interaction (p=0.54). C statistics were 0.69 (95% CI 0.66-0.72) for AI-ECG probability, 0.69 (95% CI 0.66-0.71) for CHARGE-AF and 0.72 (95% CI 0.69-0.75) for combined AI-ECG and CHARGE-AF score. Conclusions: In the Mayo Clinic Study of Aging, both the AI-ECG probability and CHARGE-AF score independently predicted time to AF. The AI-ECG may offer a means to assess risk with a single test without requiring manual or automated clinical data abstraction.

Background and Purpose: Cerebral microbleeds (CMBs) are represented by small areas of hemosiderin deposition, detected on brain magnetic resonance imaging (MRI), and found in ≈23% of the cognitively normal population over age of 60 years. CMBs predict risk of hemorrhagic and ischemic stroke. They correlate with increased cardiovascular mortality. In this article, we sought to determine in a population-based study whether antithrombotic medications correlate with CMBs and, if present, whether the association was direct or mediated by another variable. Methods: The study consisted of 1253 participants from the population-based Mayo Clinic Study of Aging who underwent T2* gradient-recalled echo magnetic resonance imaging. We tested the relationship between antithrombotic medications and CMB presence and location, using multivariable logistic-regression models. Ordinal logistic models tested the relationship between antithrombotics and CMB frequency. Using structural equation models, we assessed the effect of antithrombotic medications on presence/absence of CMBs and count of CMBs in the CMB-positive group, after considering the effects of age, sex, vascular risk factors, amyloid load by positron emission tomography, and apoE. Results: Two hundred ninety-five participants (26.3%) had CMBs. Among 678 participants taking only antiplatelet medications, 185 (27.3%) had CMBs. Among 95 participants taking only an anticoagulant, 43 (45.3%) had CMBs. Among 44 participants taking an anticoagulant and antiplatelet therapy, 21 (48.8%) had CMBs. Anticoagulants correlated with the presence and frequency of CMBs, whereas antiplatelet agents were not. Structural equation models showed that predictors for presence/absence of CMBs included older age at magnetic resonance imaging, male sex, and anticoagulant use. Predictors of CMB count in the CMB-positive group were male sex and amyloid load. Conclusions: Anticoagulant use correlated with presence of CMBs in the general population. Amyloid positron emission tomography correlated with the count of CMBs in the CMB-positive group.