49 research outputs found
On-treatment follow-up in real-world studies of direct oral anticoagulants in atrial fibrillation: Association with treatment effects.
Background
Numerous observational studies support the safety and effectiveness of the direct oral anticoagulants (DOAC) for stroke prevention in atrial fibrillation (AF), but these data are often limited to short duration of follow-up. We aimed to assess the length of on-treatment follow-up in the accumulated real-world evidence and the relationship between follow-up duration and estimates of DOAC effectiveness and safety.
Methods
We searched the literature for observational studies reporting comparative effectiveness and safety outcomes of DOACs versus warfarin. In random-effects meta-analyses, we assessed associations of specific DOACs vs warfarin for stroke/systematic embolism (SE) and major bleeding. In meta-regression analyses, we assessed the correlation between the reported on-treatment follow-up with the effect sizes for stroke/SE and major bleeding outcomes.
Results
In 45 eligible observational studies, the average on-treatment follow-up was <1 year for all DOACs. In meta-analyses, all DOACs showed significantly lower risks of stroke/SE, but only dabigatran and apixaban showed lower risks for major bleeding compared to warfarin. There was no correlation between follow-up duration and magnitude of stroke/SE reduction for any of the DOACs. Longer follow-up correlated with greater major bleeding reduction for dabigatran (p = 0.006) and rivaroxaban (p = 0.033) as compared to warfarin, but it correlated with smaller major bleeding reduction for apixaban (p = 0.004).
Conclusions
The numerous studies of DOAC effectiveness and safety in the routine AF practice pertain to short treatment follow-up. Study follow-up correlates significantly with DOAC-specific vs warfarin associations for major bleeding
Invasive electrophysiological testing to predict and guide permanent pacemaker implantation after transcatheter aortic valve implantation: A meta-analysis.
BACKGROUND
Atrioventricular conduction abnormalities after transcatheter aortic valve implantation (TAVI) are common. The value of electrophysiological study (EPS) for risk stratification of high-grade atrioventricular block (HG-AVB) and guidance of permanent pacemaker (PPM) implantation is poorly defined.
OBJECTIVE
The purpose of this study was to identify EPS parameters associated with HG-AVB and determine the value of EPS-guided PPM implantation after TAVI.
METHODS
We performed a systematic review and meta-analysis of studies investigating the value of EPS parameters for risk stratification of TAVI-related HG-AVB and for guidance of PPM implantation among patients with equivocal PPM indications after TAVI.
RESULTS
Eighteen studies (1230 patients) were eligible. In 7 studies, EPS was performed only after TAVI, whereas in 11 studies EPS was performed both before and after TAVI. Overall PPM implantation rate for HG-AVB was 16%. AV conduction intervals prolonged after TAVI, with the AH and HV intervals showing the largest magnitude of changes. Pre-TAVI HV >70 ms and the absolute value of the post-TAVI HV interval were associated with subsequent HG-AVB and PPM implantation with odds ratios of 2.53 (95% confidence interval [CI] 1.11-5.81; P = .04) and 1.10 (95% CI 1.03-1.17; P = .02; per 1-ms increase), respectively. In 10 studies, PPM was also implanted due to abnormal EPS findings in patients with equivocal PPM indications post-TAVI (typically new left bundle branch block or transient HG-AVB). Among them, the rate of long-term PPM dependency was 57%.
CONCLUSION
Selective EPS testing may assist in the risk stratification of post-TAVI HG-AVB and in the guidance of PPM implantation, especially in patients with equivocal PPM indications post-TAVI
Correlation between computer tomographyâderived scar topography and critical ablation sites in postinfarction ventricular tachycardia
BackgroundMyocardial wall thickness (WT) in patients with a prior myocardial infarction has been used to indicate scarring. However, the correlation of WT with sites critical to ventricular tachycardia (VT) has not been previously investigated. The purpose of this study was to correlate electroanatomic mapping data obtained during VT ablation with WT determined by cardiac computed tomography (CT).Methods and resultsCardiac CTs were performed in 15 consecutive patients (mean age 63 ± 10 years, 86% male, left ventricular ejection fraction 27 ± 12%) with a prior infarct referred for VT ablation. The CTs were registered to the electroanatomic maps obtained during the mapping procedure. Pacing was performed throughout the scar at sites with fractionated electrograms and isolated potentials. Ablation sites were identified by paceâmapping or entrainmentâmapping and these sites were correlated with WT. Bipolar and unipolar voltage amplitude and bipolar electrogram width correlated with WT (correlation coefficient: 0.63, 0.65, and 0.41, respectively, P < 0.001). Ablation target sites were identified for 58 of 113 inducible VTs. The ablation target sites were located on CTâdefined ridges (WT: 4.2 ± 1.2 mm) bordered by areas of thinning (WT: 2.6 ± 1.1 mm, P < 0.0001) in 14 of 15 patients. Ablation targets were found on ridges in 49 of 58 VTs (84%) for which target sites were identified. A total of 70 ridges were localized in the 15 patients. VT became noninducible postablation in 11 of 15 patients (73%).ConclusionWT measured by CT identifies ridges of myocardial tissue that often are critical for postinfarction VT and that can be appropriate target sites for ablation.Peer Reviewedhttps://deepblue.lib.umich.edu/bitstream/2027.42/142923/1/jce13441_am.pdfhttps://deepblue.lib.umich.edu/bitstream/2027.42/142923/2/jce13441.pd
Hypertrophic cardiomyopathy detection with artificial intelligence electrocardiography in international cohorts: an external validation study
Aims: Recently, deep learning artificial intelligence (AI) models have been trained to detect cardiovascular conditions, including hypertrophic cardiomyopathy (HCM), from the 12-lead electrocardiogram (ECG). In this external validation study, we sought to assess the performance of an AI-ECG algorithm for detecting HCM in diverse international cohorts. Methods and results: A convolutional neural network-based AI-ECG algorithm was developed previously in a single-centre North American HCM cohort (Mayo Clinic). This algorithm was applied to the raw 12-lead ECG data of patients with HCM and non-HCM controls from three external cohorts (Bern, Switzerland; Oxford, UK; and Seoul, South Korea). The algorithmâs ability to distinguish HCM vs. non-HCM status from the ECG alone was examined. A total of 773 patients with HCM and 3867 non-HCM controls were included across three sites in the merged external validation cohort. The HCM study sample comprised 54.6% East Asian, 43.2% White, and 2.2% Black patients. Median AI-ECG probabilities of HCM were 85% for patients with HCM and 0.3% for controls (P < 0.001). Overall, the AI-ECG algorithm had an area under the receiver operating characteristic curve (AUC) of 0.922 [95% confidence interval (CI) 0.910â0.934], with diagnostic accuracy 86.9%, sensitivity 82.8%, and specificity 87.7% for HCM detection. In age- and sex-matched analysis (caseâcontrol ratio 1:2), the AUC was 0.921 (95% CI 0.909â0.934) with accuracy 88.5%, sensitivity 82.8%, and specificity 90.4%. Conclusion: The AI-ECG algorithm determined HCM status from the 12-lead ECG with high accuracy in diverse international cohorts, providing evidence for external validity. The value of this algorithm in improving HCM detection in clinical practice and screening settings requires prospective evaluation
Prognostic value of positron emission tomography myocardial perfusion imaging beyond traditional cardiovascular risk factors: Systematic review and meta-analysis
Background: Despite substantive growth in utilization of positron emission tomography (PET) myocardial perfusion imaging (MPI), evidence on its prognostic value is limited. We aimed to comprehensively evaluate the prognostic literature of PET perfusion measures according to the most recent American Heart Association recommendations for assessment of novel cardiovascular biomarkers.
Methods: We searched the literature for studies reporting associations of PET MPI measures and outcomes in patients with known or suspected coronary artery disease. We documented hazard ratios (HR) and 95% confidence intervals (CI) of association effects and quantitatively synthesized them with random-effects meta-analyses. Discrimination, calibration and risk reclassification after addition of PET MPI measures to standard prognostic models were documented.
Results: We identified 20 eligible studies with median n = 551 patients. In meta-analyses, the extents of ischemic and scarred myocardium were significantly associated with cardiac death. Meta-analyses of multivariate estimates for abnormal summed stress score â„4 and myocardial perfusion reserve <2 revealed significant associations with major adverse cardiovascular events [HR (95% CI) 2.30 (1.53â3.44) and 2.11 (1.33â3.36), respectively]. Changes in model discrimination, calibration or risk reclassification were reported in 5 studies (8 prognostic evaluations). There were marginal improvements in discrimination based on C index and no improvements in model calibration. Net reclassification index ranged from 9.8% to 14.2% and risk classification was significantly improved in 4/5 prognostic evaluations.
Conclusions: PET MPI measures were strongly associated with adverse patient outcomes. Risk classification was more consistently improved than discrimination and calibration after addition of PET MPI measures, but reporting of such metrics was overall limited
Bioresorbable Scaffolds Versus Metallic Drug-Eluting Stents: Are We Getting Any Closer to a Paradigm Shift?
Evaluation and Catheter Ablation of Ventricular Arrhythmias in Cardiac Sarcoidosis
Ventricular arrhythmias are a common clinical manifestation in patients with cardiac sarcoidosis (CS) and other arrhythmogenic inflammatory cardiomyopathies (AIC). The management of sustained ventricular arrhythmias in these patients presents unique challenges. Current therapies include immunosuppressive, antiarrhythmic agents, and catheter ablation. Significant progress has been made in deciphering the importance of patient selection for ablation, systematic preablation evaluation, and optimal ablation timing, as well as ablation approaches and techniques. In this overview, we discuss the evaluation and management of ventricular arrhythmias in patients with CS, focusing on catheter ablation, which has evolved into an effective approach in reducing the burden of ventricular arrhythmias in these patients in the context of multifaceted treatment along with medical therapies
Stroke Prophylaxis in Patients with Atrial Fibrillation and End-Stage Renal Disease
Atrial fibrillation (AF) is an important comorbidity in patients with end-stage renal disease (ESRD) undergoing dialysis that portends increased health care utilization, morbidity, and mortality in this already high-risk population. Patients with ESRD have a particularly high stroke risk, which is further compounded by AF. However, the role of anticoagulation for stroke prophylaxis in ESRD and AF is debated. The ESRD population presents a unique challenge because of the combination of elevated stroke and bleeding risks. Warfarin has been traditionally used in this population, but it is associated with significant risks of minor and major bleeding, particularly intracranial, thus leading many clinicians to forgo anticoagulation altogether. When anticoagulation is prescribed, rates of adherence and persistence are poor, leaving many patients untreated. The direct oral anticoagulants (DOACs) may offer an alternative to warfarin in ESRD patients, but these agents have not been extensively studied in this population and uncertainties regarding comparative effectiveness (versus warfarin, each other, and no treatment) remain. In this review, we discuss the current evidence on the risk and benefits of anticoagulants in this challenging population and comparisons between warfarin and DOACs, and review future directions including options for non-pharmacologic stroke prevention