Direct Comparison of Outcomes After Transcatheter Aortic Valve Replacement in Veterans and Non-Veterans Using the Transcatheter Valve Therapy Registry.

OBJECTIVES: This study aims to compare veterans and non-veterans undergoing transcatheter aortic valve replacement (TAVR) using data from the Society for Thoracic Surgeons/American College of Cardiology Transcatheter Valve Therapy (STS/ACC TVT) registry. METHODS: Patients undergoing TAVR at George Washington University (GWU) and veterans treated at Washington DC Veterans Affairs Medical Center (VAMC) who underwent TAVR at GWU from 2014-2020 were included. All patients were reported in the TVT registry. Emergency and valve-in-valve TAVR were excluded. Cohorts were divided based on veteran status. Operators were the same for both groups. Outcomes were compared at 30 days and 1 year. The primary outcome was mortality and secondary outcomes were morbidity metrics. RESULTS: A total of 299 patients (91 veterans, 208 non-veterans) were included. Veterans had higher rates of hypertension (87.9% vs 77.9%; P=.04), diabetes (46.7% vs 28.9%; P<.01), and lung disease (2.4% vs 11.0%; P<.001). Outcomes were not significantly different between veterans and non-veterans, including 30-day mortality (0% vs 2.9%, respectively; P=.18), 1-year mortality (9.8% vs 10.7%, respectively; P=.61), stroke incidence (0% vs 2.5%, respectively; P=.73), median intensive care unit stay (24 hours in both groups), and overall hospital stay (2 days in both groups). CONCLUSIONS: The affiliation between a VAMC and an academic medical center allowed for direct comparison between veterans and non-veterans undergoing TAVR by the same operators using the TVT registry. Despite significantly higher rates of comorbidities, veterans had equivalent outcomes compared with non-veterans. This may be in part due to the comprehensive care that veterans receive in the VAMC and this institution's integrated heart center team.

Multi-parametric approach to predict prosthetic valve size using CMR and clinical data: insights from SAVR.

The purpose of this investigation was to characterize the CMR and clinical parameters that correlate to prosthetic valve size (PVS) determined at SAVR and develop a multi-parametric model to predict PVS. Sixty-two subjects were included. Linear/area measurements of the aortic annulus were performed on cine CMR images in systole/diastole on long/short axis (SAX) views. Clinical parameters (age, habitus, valve lesion, valve morphology) were recorded. PVS determined intraoperatively was the reference value. Data were analyzed using Spearman correlation. A prediction model combining imaging and clinical parameters was generated. Imaging parameters had moderate to moderately strong correlation to PVS with the highest correlations from systolic SAX mean diameter (r = 0.73, p < 0.0001) and diastolic SAX area (r = 0.73, p < 0.0001). Age was negatively correlated to PVS (r = - 0.47, p = 0.0001). Weight was weakly correlated to PVS (r = 0.27, p = 0.032). AI and bicuspid valve were not predictors of PVS. A model combining clinical and imaging parameters had high accuracy in predicting PVS (R2 = 0.61). Model predicted mean PVS was 23.3 mm (SD 1.1); actual mean PVS was 23.3 mm (SD 1.3). The Spearman r of the model (0.80, 95% CI 0.683-0.874) was significantly higher than systolic SAX area (0.68, 95% CI 0.516-0.795). Clinical parameters like age and habitus impact PVS; valve lesion/morphology do not. A multi-parametric model demonstrated high accuracy in predicting PVS and was superior to a single imaging parameter. A multi-parametric approach to device sizing may have future application in TAVR.

The Avalanche Hypothesis and Compression of Morbidity: Testing Assumptions through Cohort-Sequential Analysis.

BACKGROUND: The compression of morbidity model posits a breakpoint in the adult lifespan that separates an initial period of relative health from a subsequent period of ever increasing morbidity. Researchers often assume that such a breakpoint exists; however, this assumption is hitherto untested. PURPOSE: To test the assumption that a breakpoint exists--which we term a morbidity tipping point--separating a period of relative health from a subsequent deterioration in health status. An analogous tipping point for healthcare costs was also investigated. METHODS: Four years of adults' (N = 55,550) morbidity and costs data were retrospectively analyzed. Data were collected in Pittsburgh, PA between 2006 and 2009; analyses were performed in Rochester, NY and Ann Arbor, MI in 2012 and 2013. Cohort-sequential and hockey stick regression models were used to characterize long-term trajectories and tipping points, respectively, for both morbidity and costs. RESULTS: Morbidity increased exponentially with age (P<.001). A morbidity tipping point was observed at age 45.5 (95% CI, 41.3-49.7). An exponential trajectory was also observed for costs (P<.001), with a costs tipping point occurring at age 39.5 (95% CI, 32.4-46.6). Following their respective tipping points, both morbidity and costs increased substantially (Ps<.001). CONCLUSIONS: Findings support the existence of a morbidity tipping point, confirming an important but untested assumption. This tipping point, however, may occur earlier in the lifespan than is widely assumed. An "avalanche of morbidity" occurred after the morbidity tipping point-an ever increasing rate of morbidity progression. For costs, an analogous tipping point and "avalanche" were observed. The time point at which costs began to increase substantially occurred approximately 6 years before health status began to deteriorate.

Using cardiac magnetic resonance imaging to evaluate cardiac function and predict outcomes in patients with valvular heart disease.

OBJECTIVE: In valvular heart disease, elevated left atrial and pulmonary pressures contribute to right ventricular strain and, ultimately, right ventricle failure. Elevated pulmonary artery (PAP) and left ventricular end diastolic pressures are used as markers of right ventricle dysfunction and correlate with poor outcomes. Using cardiac magnetic resonance imaging (CMR), it is possible to directly quantify both left and right ventricular ejection function (LVEF and RVEF), and here, we compare CMR with traditional markers as outcome predictors. METHODS: A retrospective review of prospectively collected data was performed for patients from January 2004 to February 2008 at a single center (n = 103). Patients were divided into those receiving CMR (n = 56) and those receiving only catheterization (n = 47). Univariate and multivariate logistic regression models were applied to determine predictors of mortality. Finally, predictive models for mortality using PAP, mean PAP, and left ventricular end diastolic pressure were compared to models using LVEF and RVEF obtained from CMR. RESULTS: Preoperative average CMR LVEF and RVEF were 57% and 46%, respectively. Only age emerged as an isolated predictor of mortality (P = 0.01) within the univariate models. Stepwise regression models were created using the catheterization or CMR data. When compared, the CMR model has a slightly better R, c (prediction accuracy), and sensitivity/specificity (0.22 vs 0.28, 0.77 vs 0.82, and 0.63/0.62 vs 0.69/0.64, respectively). CONCLUSIONS: Within our population, LVEF and RVEF predict mortality as least as well as traditional catheterization values. Additionally, CMR may identify of elevated PAPs caused by right ventricle dysfunction and those due to other causes, allowing these other causes to be addressed preoperatively.

Estimation and inference concerning ordered means in analysis of covariance models with interactions.

When interactions are identified in analysis of covariance models it becomes important to identify values of the covariates for which there are significant differences or, more generally, significant contrasts among the group mean responses. Inferential procedures that incorporate a priori order restrictions among the group mean responses would be expected to be superior to those that ignore this information. In this paper we focus on analysis of covariance models with pre-specified order restrictions on the mean response across the levels of a grouping variable when the grouping variable may interact with model covariates. In order for the restrictions to hold in the presence of interactions, it is necessary to impose the requirement that the restrictions hold over all levels of interacting categorical covariates and across pre-specified ranges of interacting continuous covariates. The parameter estimation procedure involves solving a quadratic programming minimization problem with a carefully specified constraint matrix. Simultaneous confidence intervals for treatment group contrasts and tests for equality of the ordered group mean responses are determined by exploiting previously unconnected literature. The proposed methods are motivated by a clinical trial of the dopamine agonist pramipexole for the treatment of early-stage Parkinson's disease.

The triterpenoid CDDO-Me inhibits bleomycin-induced lung inflammation and fibrosis.

Pulmonary Fibrosis (PF) is a devastating progressive disease in which normal lung structure and function is compromised by scarring. Lung fibrosis can be caused by thoracic radiation, injury from chemotherapy and systemic diseases such as rheumatoid arthritis that involve inflammatory responses. CDDO-Me (Methyl 2-cyano-3,12-dioxooleana-1,9(11)dien-28-oate, Bardoxolone methyl) is a novel triterpenoid with anti-fibrotic and anti-inflammatory properties as shown by our in vitro studies. Based on this evidence, we hypothesized that CDDO-Me would reduce lung inflammation, fibrosis and lung function impairment in a bleomycin model of lung injury and fibrosis. To test this hypothesis, mice received bleomycin via oropharyngeal aspiration (OA) on day zero and CDDO-Me during the inflammatory phase from days -1 to 9 every other day. Bronchoalveolar lavage fluid (BALF) and lung tissue were harvested on day 7 to evaluate inflammation, while fibrosis and lung function were evaluated on day 21. On day 7, CDDO-Me reduced total BALF protein by 50%, alveolar macrophage infiltration by 40%, neutrophil infiltration by 90% (p≤0.01), inhibited production of the inflammatory cytokines KC and IL-6 by over 90% (p≤0.001), and excess production of the pro-fibrotic cytokine TGFß by 50%. CDDO-Me also inhibited α-smooth muscle actin and fibronectin mRNA by 50% (p≤0.05). On day 21, CDDO-Me treatment reduced histological fibrosis, collagen deposition and αSMA production. Lung function was significantly improved at day 21 by treatment with CDDO-Me, as demonstrated by respiratory rate and dynamic compliance. These new findings reveal that CDDO-Me exhibits potent anti-fibrotic and anti-inflammatory properties in vivo. CDDO-Me is a potential new class of drugs to arrest inflammation and ameliorate fibrosis in patients who are predisposed to lung injury and fibrosis incited by cancer treatments (e.g. chemotherapy and radiation) and by systemic autoimmune diseases.