Search

ObjectiveSevere aortic valve stenosis (AS) develops via insidious processes and can be challenging to correctly diagnose. We sought to develop a circulating biomarker panel to identify patients with severe AS.MethodsWe enrolled study participants undergoing coronary or peripheral angiography for a variety of cardiovascular diseases at a single academic medical centre. A panel of 109 proteins were measured in blood obtained at the time of the procedure. Statistical learning methods were used to identify biomarkers and clinical parameters that associate with severe AS. A diagnostic model incorporating clinical and biomarker results was developed and evaluated using Monte Carlo cross-validation.ResultsOf 1244 subjects (age 66.4±11.5  years, 28.7% female), 80 (6.4%) had severe AS (defined as aortic valve area (AVA)

BackgroundComputed tomography (CT)-based fat and muscle measures are associated with outcome in large populations. We tested if muscle and fat characteristics are associated with long-term outcomes after TAVR.MethodsWe included 403 clinical CTs performed prior to TAVR at our center between 2008 and 2016, measuring area (cm2) and density (Hounsfield units, HU) of both psoas muscles (PM), subcutaneous adipose (SAT), and visceral adipose tissue (VAT). Area measures were indexed to height, log-transformed and both area and density were standardized for analysis. We assessed the association of each measure with all-cause mortality (adjusted for age, sex, body mass index (BMI), and the Society of Thoracic Surgeons (STS) risk score.ResultsOf the 403 individuals (83 ± 8 years; 52% female), 167 (41.4%) died during a median follow-up of 458 days (interquartile range IQR 297-840). Fat measures were feasible and rapid. Fat area was available in 242 (60%) patients with an adequate field of view. Individuals with the lowest PM area, SAT area or VAT area exhibited the highest hazard of mortality. In addition, greater SAT density was associated with a higher mortality hazard (adjusted HR per standard deviation increase in density = 1.35, 95%CI 1.10-1.67, P = 0.005).ConclusionRapid CT-based tissue characterization is feasible in patients referred for TAVR. Decreased PM area and increased SAT density are associated with long-term mortality after TAVR, even after accounting for age, sex, BMI, and STS score. Further studies are necessary to interrogate sex-specific relationships between CT tissue metrics and mortality and whether CT measures are incremental to well-established frailty metrics.

A variety of surgical procedures can be performed for the treatment of gingival recession, including the subepithelial connective tissue graft. Due to the morbidity reported by patients, alternative techniques using biomaterials has been frequently discussed. The objective of this study was to report the clinical follow-up of root coverage with coronally positioned flap associated with Mucograft® (collagen matrix) for 24 months. The fine gingival biotype tends to be delicate, possessing a small zone of keratinized mucosa. This type of thickness should be taken into special consideration since it directly influences in the aesthetics and the emergence profile. The gingival recession heights and the thickness of the tissue were measured initially and after 4, 9, and 24 months. 1 year post-operative, partial root coverage (22.5%) and gain in the thickness (100%) of the gingival tissue was observed. Although the root coverage with a coronally positioned flap associated with Mucograft® for this clinical case was not effective, a significant increase in thickness of the gingival tissue that received the collagen matrix was observed; thus, it was considered a viable treatment option and suitable for soft tissue augmentation. This clinical case, the Mucograft® was effective for the thickness of the gingival tissue; thus it is considered a viable treatment option and suitable for periodontal tissue augmentation. [ABSTRACT FROM AUTHOR]