A standardized approach to treat complex aortic valve endocarditis: a case series

Background Surgical treatment of complicated aortic valve endocarditis often is challenging, even for experienced surgeons. We aim at demonstrating a standardized surgical approach by stentless bioprostheses for the treatment of aortic valve endocarditis complicated by paravalvular abscess formation. MethodsSixteen patients presenting with aortic valve endocarditis (4 native and 12 prosthetic valves) and paravalvular abscess formation at various localizations and to different extents were treated by a standardized approach using stentless bioprostheses. The procedure consisted of thorough debridement, root replacement with reimplantation of the coronary arteries and correction of accompanying pathologies (aortoventricular and aortomitral dehiscence, septum derangements, Gerbode defect, total atrioventricular conduction block, mitral and tricuspid valve involvement).ResultsAll highly complex patients included (14 males and 2 females; median age 63 years [range 31–77]) could be successfully treated with stentless bioprostheses as aortic root replacement. Radical surgical debridement of infected tissue with anatomical recontruction was feasible. Although predicted operative mortality was high (median logarithmic EuroSCORE I of 40.7 [range 12.8–68.3]), in-hospital and 30-day mortality rates were favorable (18.8 and 12.5% respectively). ConclusionsRepair of active aortic valve endocarditis complicated by paravalvular abscess formation and destruction of the left ventricular outflow tract with stentless bioprosthesis is a valuable option for both native and prosthetic valves. It presents a standardized approach with a high success rate for complete debridement, is readily available, and yields comparable clinical outcomes to the historical gold standard, repair by homografts. Additionally, use of one type of prosthesis reduces logistical issues and purchasing costs

Gene Expression Signature in Peripheral Blood Detects Thoracic Aortic Aneurysm

BACKGROUND: Thoracic aortic aneurysm (TAA) is usually asymptomatic and associated with high mortality. Adverse clinical outcome of TAA is preventable by elective surgical repair; however, identifying at-risk individuals is difficult. We hypothesized that gene expression patterns in peripheral blood cells may correlate with TAA disease status. Our goal was to identify a distinct gene expression signature in peripheral blood that may identify individuals at risk for TAA. METHODS AND FINDINGS: Whole genome gene expression profiles from 94 peripheral blood samples (collected from 58 individuals with TAA and 36 controls) were analyzed. Significance Analysis of Microarray (SAM) identified potential signature genes characterizing TAA vs. normal, ascending vs. descending TAA, and sporadic vs. familial TAA. Using a training set containing 36 TAA patients and 25 controls, a 41-gene classification model was constructed for detecting TAA status and an overall accuracy of 78+/-6% was achieved. Testing this classifier on an independent validation set containing 22 TAA samples and 11 controls yielded an overall classification accuracy of 78%. These 41 classifier genes were further validated by TaqMan real-time PCR assays. Classification based on the TaqMan data replicated the microarray results and achieved 80% classification accuracy on the testing set. CONCLUSIONS: This study identified informative gene expression signatures in peripheral blood cells that can characterize TAA status and subtypes of TAA. Moreover, a 41-gene classifier based on expression signature can identify TAA patients with high accuracy. The transcriptional programs in peripheral blood leading to the identification of these markers also provide insights into the mechanism of development of aortic aneurysms and highlight potential targets for therapeutic intervention. The classifier genes identified in this study, and validated by TaqMan real-time PCR, define a set of promising potential diagnostic markers, setting the stage for a blood-based gene expression test to facilitate early detection of TAA

Random effects models for estimation of the probability and time to progression of a continuous biomarker

Biomarkers play a key role in the monitoring of disease progression. The time taken for an individual to reach a biomarker exceeding or lower than a meaningful threshold is often of interest. Due to the inherent variability of biomarkers, persistence criteria are sometimes included in the definitions of progression, such that only two consecutive measurements above or below the relevant threshold signal that "true" progression has occurred. In previous work, a novel approach was developed, which allowed estimation of the time to threshold using the parameters from a linear mixed model where the residual variance was assumed to be pure measurement error. In this paper, we extend this methodology so that serial correlation can be accommodated. Assuming that the Markov property holds and applying the chain rule of probabilities, we found that the probability of progression at each timepoint can be expressed simply as the product of conditional probabilities. The methodology is applied to a cohort of HIV positive individuals, where the time to reach a CD4 count threshold is estimated. The second application we present is based on a study on abdominal aortic aneurysms, where the time taken for an individual to reach a diameter exceeding 55 mm is studied. We observed that erroneously ignoring the residual correlation when it is strong may result in substantial overestimation of the time to threshold. The estimated probability of the biomarker reaching a threshold of interest, expected time to threshold, and confidence intervals are presented for selected patients in both applications

A clinical appraisal of different Z-score equations for aortic root assessment in the diagnostic evaluation of Marfan syndrome

Item does not contain fulltextPURPOSE: Aortic sinus diameter dilatation expressed as a Z-score >2.0 is diagnostic in Marfan syndrome. In addition to the classic equation (Z1) for calculating Z-scores, two new equations were recently introduced (Z2 and Z3). METHODS: We studied the effects of obesity, age, and the absolute cut point of 40 mm on these three equations in 2,674 echocardiographic measurements of 260 patients with Marfan syndrome. RESULTS: Diameters >/=40 mm were associated with Z1 scores /=25 kg/m(2) (group B), median Z1 scores differed between groups (Z1 = 3.00 in group A, Z1 = 1.78 in group B; P = 0.012), whereas Z2 (Z2 = 2.82 in group A, Z2 = 2.47 in group B; P = 0.52) and Z3 scores (Z3 = 2.72 in group A, Z2 = 3.12 in group B; P = 0.32) did not. CONCLUSION: Z1 scores are inferior to Z2 and Z3 scores in Marfan syndrome. In particular, the Z3 score, correcting aortic sinus diameter for body height, seems excellent