Vadim Zipunnikov

Relationship between left atrial appendage morphology and stroke in patients with atrial fibrillation

BACKGROUND Atrial fibrillation (AF) is an important cause of stroke. Given the morbidity and mortality associated with stroke, the risk stratification of patients based on left atrial appendage (LAA) characteristics is of great interest. OBJECTIVE To explore the association between LAA morphology and LAA characteristics including the extent of trabeculations, orifice diameter, and length with prevalent stroke in a large cohort of patients with drug refractory AF who underwent AF ablation to develop mechanistic insight regarding the risk of stroke. METHODS An institutional cohort of 1063 patients referred for AF ablation from 2003 to 2012 was reviewed to identify patients that underwent preprocedural cardiac computed tomography (CT). LAA morphology was characterized as chicken wing, cactus, windsock, or cauliflower by using previously reported methodology. Left atrial size and LAA trabeculations, morphology, orifice diameter, and length were compared between patients with prevalent stroke and patients without prevalent stroke. RESULTS Of 678 patients with CT images, 65 (10%) had prior stroke or transient ischemic attack. In univariate analyses, prevalent heart failure (7.7% in cases vs 2.8% in controls; P = .033), smaller LAA orifice (2.26 ± 0.52 cm vs 2.78 ± 0.71 cm ; P < .001), shorter LAA length (5.06 ± 1.17 cm vs 5.61 ± 1.17 cm; P < .001), and extensive LAA trabeculations (27.7% vs 14.4%; P = .019) were associated with stroke. LAA morphologies were unassociated with stroke risk. In multivariable analysis, smaller LAA orifice diameter and extensive LAA trabeculations remained independently associated with thromboembolic events. CONCLUSIONS The extent of LAA trabeculations and smaller LAA orifice diameter are associated with prevalent stroke and may mediate the previously described association of cauliflower LAA morphology with stroke.

Magnetic resonance image intensity ratio, a normalized measure to enable interpatient comparability of left atrial fibrosis.

BACKGROUND The measurement of late gadolinium-enhanced magnetic resonance imaging (LGE-MRI) intensity in arbitrary units limits the objectivity of thresholds for focal scar detection and interpatient comparisons of scar burden. OBJECTIVE To develop and validate a normalized measure, the image intensity ratio (IIR), for the assessment of left atrial (LA) scar on LGE-MRI. METHODS Electrocardiogram- and respiratory-gated 1.5 Tesla LGE-MRI was performed in 75 patients (75% men; 62 ± 8 years) before atrial fibrillation ablation. The local IIR was defined as LA myocardial signal intensity for each of the 20 sectors on contiguous axial image planes divided by the mean LA blood pool image intensity. Intracardiac point-by-point sampled electroanatomic map points were coregistered with the corresponding image sectors. RESULTS The average bipolar voltage for all 8153 electroanatomic map points was 0.9 ± 1.1 mV. In a mixed effects model accounting for within patient clustering, and adjusting for age, LA volume, mass, body mass index, sex, CHA2DS2-VASc score, atrial fibrillation type, history of previous ablations, and contrast delay time, each unit increase in local IIR was associated with 91.3% decrease in bipolar LA voltage (P < .001). Local IIR thresholds of >0.97 and >1.61 corresponded to bipolar voltage <0.5 and <0.1 mV, respectively. CONCLUSIONS Normalization of LGE-MRI intensity by the mean blood pool intensity results in a metric that is closely associated with intracardiac voltage as a surrogate of atrial fibrosis.

Radiofrequency Ablation Versus Antiarrhythmic Medication for Treatment of Ventricular Premature Beats From the Right Ventricular Outflow Tract Prospective Randomized Study

Background—The purpose of this study was to compare the efficacy of radiofrequency catheter ablation (RFCA) versus antiarrhythmic drugs (AADs) for treatment of patients with frequent ventricular premature beats (VPBs) originating from the right ventricular outflow tract (RVOT). Methods and Results—A total of 330 eligible patients were included in the study and were randomly assigned to RFCA or AADs group. The absolute number and the burden of VPBs on 12-lead Holter monitors were measured at baseline and at 1st, 3rd, 6th, and 12th months after randomization. Left ventricular eject fraction was evaluated by transthoracic echocardiogram at baseline and at 3 and 6 months after randomization. During the 1-year follow-up period, VPB recurrence was significantly lower in patients randomized to RFCA group (32 patients, 19.4%) versus AADs group (146 patients, 88.6%; P<0.001, log-rank test). In a Poisson generalized estimating equations (GEE) regression model, RFCA was associated with a greater decrease in the burden of VPBs (incidence rate ratio 0.105; 95% confidence intervals [0.104–0.105]; P<0.001) compared with AADs. In a liner GEE model, the left ventricular eject fraction had a tendency to increase after the treatment in both groups (coefficient, 0.584; 95% confidence intervals [0.467–0.702]; P<0.001). In a Cox proportional model, the QS morphology in lead I was the only predictor of VPB recurrence free for catheter ablation (hazards ratio, 0.154; 95% confidence intervals [0.044–0.543]; P=0.004). Conclusions—Catheter ablation is more efficacious than AADs for preventing VPB recurrence in patients with frequent VPBs originating from the RVOT. QS morphology in lead I was associated with better outcome after ablation.

Assessing the “Physical Cliff”: Detailed Quantification of Age-Related Differences in Daily Patterns of Physical Activity

BACKGROUND In spite of evidence that physical activity has beneficial effects on health and age-related functional decline, there is a scarcity of detailed and accurate information on objectively measured daily activity and patterns of such activity in older adults. METHODS Participants in the Baltimore Longitudinal Study of Aging (n = 611, 50% male, mean age 67, range 32-93) wore the Actiheart portable activity monitor for 7 days in the free-living environment. The association between activity and age was modeled using a continuous log-linear regression of activity counts on age with sex, body mass index, employment status, functional performance, and comorbid conditions as covariates. RESULTS In the fully adjusted model, continuous analyses demonstrated that overall physical activity counts were 1.3% lower for each year increase in age. Although there were no differences among morning levels of activity, there was significantly lower afternoon and evening activity in older individuals (p < .01). After adjusting for age, poor functional performance, nonworking status, and higher body mass index were independently associated with less physical activity (p < .001). CONCLUSIONS The use of accelerometers to characterize minute-by-minute intensity, cumulative physical activity counts, and daily activity patterns provides detailed data not gathered by traditional subjective methods, particularly at low levels of activity. The findings of a 1.3% decrease per year in activity from mid-to-late life, and the corresponding drop in afternoon and evening activity, provide new information that may be useful when targeting future interventions. Further, this methodology addresses essential gaps in understanding activity patterns and trends in more sedentary sectors of the population.

Association between Objectively Measured Physical Activity and Mortality in NHANES.

PURPOSE We examined total activity, light activity, and moderate-to-vigorous physical activity (MVPA) as predictors of mortality in a nationally representative sample of older adults. Then we explored the theoretical consequences of replacing sedentary time with the same duration of light activity or MVPA. METHODS Using accelerometer-measured activity, the associations between total activity, light activity (100-2019 counts per minute), and MVPA (>2019 counts per minute) counts and mortality were examined in adults age 50 to 79 yr in the National Health and Nutrition Examination Survey, 2003-2006 (n = 3029), with mortality follow-up through December 2011. Cox proportional hazard models were fitted to estimate mortality risks. An isotemporal substitution model was used to examine the theoretical consequences of replacing sedentary time with light activity or MVPA on mortality. RESULTS After adjusting for potential confounders, including age, sex, race/ethnicity, education, BMI, and the presence of comorbid conditions, those in the highest tertile of total activity counts had one fifth the risk of death of those in the lowest tertile (hazard ratio [HR] = 0.21, 95% confidence interval [CI] = 0.12-0.38), and those in the middle tertile had one third the risk of death (HR = 0.36, 95% CI = 0.30-0.44). In addition, replacing 30 min of sedentary time with light activity was associated with significant reduction in mortality risk (after 5 yr of follow-up: HR = 0.80, 95% CI = 0.75-0.85). Replacing 30 min of sedentary time with MVPA was also associated with reduction in mortality risk (HR = 0.49, 95% CI = 0.25-0.97). CONCLUSIONS Greater total activity is associated with lower all-cause mortality risk. Replacing sedentary time with light activity or MVPA may reduce mortality risk for older adults.

Association of Left Atrial Function and Left Atrial Enhancement in Patients With Atrial Fibrillation Cardiac Magnetic Resonance Study

Atrial fibrillation (AF) is associated with extensive abnormalities in atrial structure and function1-3. It is well-established that structural atrial changes precede the development of AF and progress with increased duration of sustained AF4. The changes in atrial function impair not only the booster pump function but also the atrial reservoir and conduit functions during ventricular systole and early diastole 5, 6. Progressive atrial remodeling includes fibrotic changes that promote AF maintenance7. This idea is supported by observations of increased left atrial (LA) fibrosis in patients with long-standing persistent AF 4. LA structural and functional remodeling is associated with increased incidence of AF, as well as AF recurrence after cardioversion or ablation8-11. Late gadolinium enhanced (LGE) cardiac magnetic resonance (CMR) can noninvasively quantify the extent of LA fibrosis12, 13. Atrial function is commonly evaluated by speckle-tracking echocardiography; however, the technique is limited for resolution of the thin and asymmetric LA myocardium and for the analysis of the posterior LA where most of the fibrosis is located7. In contrast, myocardial motion can be accurately tracked with CMR due to its ability to accurately define endocardial and epicardial borders14. CMR-feature tracking, a novel post–processing technique which tracks myocardial motion using cine CMR images, has recently been developed15-19. In this study, we sought to examine the association of LA fibrosis measured with LGE-CMR with phasic LA remodeling measured with feature-tracking CMR in patients with AF. We hypothesized that increased atrial LGE is associated with reduced LA function as assessed by feature tracking CMR.Background—Atrial fibrillation (AF) is associated with left atrial (LA) structural and functional changes. Cardiac magnetic resonance late gadolinium enhancement (LGE) and feature-tracking are capable of noninvasive quantification of LA fibrosis and myocardial motion, respectively. We sought to examine the association of phasic LA function with LA enhancement in patients with AF. Methods and Results—LA structure and function was measured in 90 patients with AF (age 61±10 years; 76% men) referred for ablation and 14 healthy volunteers. Peak global longitudinal LA strain, LA systolic strain rate, and early and late diastolic strain rates were measured using cine–cardiac magnetic resonance images acquired during sinus rhythm. The degree of LGE was quantified. Compared with patients with paroxysmal AF (60% of cohort), those with persistent AF had larger maximum LA volume index (56±17 versus 49±13 mL/m2; P=0.036), and increased LGE (27.1±11.7% versus 36.8±14.8%; P<0.001). Aside from LA active emptying fraction, all LA parameters (passive emptying fraction, peak global longitudinal LA strain, systolic strain rate, early diastolic strain rate, and late diastolic strain rate) were lower in patients with persistent AF (P<0.05 for all). Healthy volunteers had less LGE and higher LA functional parameters compared with patients with AF (P<0.05 for all). In multivariable analysis, increased LGE was associated with lower LA passive emptying fraction, peak global longitudinal LA strain, systolic strain rate, early diastolic strain rate, and late diastolic strain rate (P<0.05 for all). Conclusions—Increased LA enhancement is associated with decreased LA reservoir, conduit, and booster pump functions. Phasic measurement of LA function using feature-tracking cardiac magnetic resonance may add important information about the physiological importance of LA fibrosis.

Population Value Decomposition, a Framework for the Analysis of Image Populations

Images, often stored in multidimensional arrays, are fast becoming ubiquitous in medical and public health research. Analyzing populations of images is a statistical problem that raises a host of daunting challenges. The most significant challenge is the massive size of the datasets incorporating images recorded for hundreds or thousands of subjects at multiple visits. We introduce the population value decomposition (PVD), a general method for simultaneous dimensionality reduction of large populations of massive images. We show how PVD can be seamlessly incorporated into statistical modeling, leading to a new, transparent, and rapid inferential framework. Our PVD methodology was motivated by and applied to the Sleep Heart Health Study, the largest community-based cohort study of sleep containing more than 85 billion observations on thousands of subjects at two visits. This article has supplementary material online.

Multilevel Functional Principal Component Analysis for High-Dimensional Data

We propose fast and scalable statistical methods for the analysis of hundreds or thousands of high-dimensional vectors observed at multiple visits. The proposed inferential methods do not require loading the entire dataset at once in the computer memory and instead use only sequential access to data. This allows deployment of our methodology on low-resource computers where computations can be done in minutes on extremely large datasets. Our methods are motivated by and applied to a study where hundreds of subjects were scanned using Magnetic Resonance Imaging (MRI) at two visits roughly five years apart. The original data possess over ten billion measurements. The approach can be applied to any type of study where data can be unfolded into a long vector including densely observed functions and images. Supplemental materials are provided with source code for simulations, some technical details and proofs, and additional imaging results of the brain study.

Impact of nonischemic scar features on local ventricular electrograms and scar-related ventricular tachycardia circuits in patients with nonischemic cardiomyopathy.

Background—The association of local electrogram features with scar morphology and distribution in nonischemic cardiomyopathy has not been investigated. We aimed to quantify the association of scar on late gadolinium-enhanced cardiac magnetic resonance with local electrograms and ventricular tachycardia circuit sites in patients with nonischemic cardiomyopathy. Methods and Results—Fifteen patients with nonischemic cardiomyopathy underwent late gadolinium-enhanced cardiac magnetic resonance before ventricular tachycardia ablation. The transmural extent and intramural types (endocardial, midwall, epicardial, patchy, transmural) of scar were measured in late gadolinium-enhanced cardiac magnetic resonance short-axis planes. Electroanatomic map points were registered to late gadolinium-enhanced cardiac magnetic resonance images. Myocardial wall thickness, scar transmurality, and intramural scar types were independently associated with electrogram amplitude, duration, and deflections in linear mixed-effects multivariable models, clustered by patient. Fractionated and isolated potentials were more likely to be observed in regions with higher scar transmurality (P<0.0001 by ANOVA) and in regions with patchy scar (versus endocardial, midwall, epicardial scar; P<0.05 by ANOVA). Most ventricular tachycardia circuit sites were located in scar with >25% scar transmurality. Conclusions—Electrogram features are associated with scar morphology and distribution in patients with nonischemic cardiomyopathy. Previous knowledge of electrogram image associations may optimize procedural strategies including the decision to obtain epicardial access.

Generalized multilevel function-on-scalar regression and principal component analysis.

This manuscript considers regression models for generalized, multilevel functional responses: functions are generalized in that they follow an exponential family distribution and multilevel in that they are clustered within groups or subjects. This data structure is increasingly common across scientific domains and is exemplified by our motivating example, in which binary curves indicating physical activity or inactivity are observed for nearly 600 subjects over 5 days. We use a generalized linear model to incorporate scalar covariates into the mean structure, and decompose subject-specific and subject-day-specific deviations using multilevel functional principal components analysis. Thus, functional fixed effects are estimated while accounting for within-function and within-subject correlations, and major directions of variability within and between subjects are identified. Fixed effect coefficient functions and principal component basis functions are estimated using penalized splines; model parameters are estimated in a Bayesian framework using Stan, a programming language that implements a Hamiltonian Monte Carlo sampler. Simulations designed to mimic the application have good estimation and inferential properties with reasonable computation times for moderate datasets, in both cross-sectional and multilevel scenarios; code is publicly available. In the application we identify effects of age and BMI on the time-specific change in probability of being active over a 24-hour period; in addition, the principal components analysis identifies the patterns of activity that distinguish subjects and days within subjects.