Fibrosing Mediastinitis Causing High Degree AV Block in a Young Female Patient.

A 30-year-old woman presented with presyncopal episodes and was found to have high degree atrioventricular block. Computed tomography imaging demonstrated pericardial thickening extending from the main pulmonary artery to the aortic cusps. Here we present a rare case of fibrosing mediastinitis causing high-degree atrioventricular block. (Level of Difficulty: Intermediate.).

Left ventricular mechanical dispersion predicts arrhythmic risk in mitral valve prolapse.

OBJECTIVE: Bileaflet mitral valve prolapse (MVP) with either focal or diffuse myocardial fibrosis has been linked to ventricular arrhythmia and/or sudden cardiac arrest. Left ventricular (LV) mechanical dispersion by speckle-tracking echocardiography (STE) is a measure of heterogeneity of ventricular contraction previously associated with myocardial fibrosis. The aim of this study is to determine whether mechanical dispersion can identify MVP at higher arrhythmic risk. METHODS: We identified 32 consecutive arrhythmic MVPs (A-MVP) with a history of complex ventricular ectopy on Holter/event monitor (n=23) or defibrillator placement (n=9) along with 27 MVPs without arrhythmic complications (NA-MVP) and 39 controls. STE was performed to calculate global longitudinal strain (GLS) as the average peak longitudinal strain from an 18-segment LV model and mechanical dispersion as the SD of the time to peak strain of each segment. RESULTS: MVPs had significantly higher mechanical dispersion compared with controls (52 vs 42 ms, p=0.005) despite similar LV ejection fraction (62% vs 63%, p=0.42) and GLS (-19.7 vs -21, p=0.045). A-MVP and NA-MVP had similar demographics, LV ejection fraction and GLS (all p>0.05). A-MVP had more bileaflet prolapse (69% vs 44%, p=0.031) with a similar degree of mitral regurgitation (mostly trace or mild in both groups) (p>0.05). A-MVP exhibited greater mechanical dispersion when compared with NA-MVP (59 vs 43 ms, p=0.0002). Mechanical dispersion was the only significant predictor of arrhythmic risk on multivariate analysis (OR 1.1, 95% CI 1.02 to 1.11, p=0.006). CONCLUSIONS: STE-derived mechanical dispersion may help identify MVP patients at higher arrhythmic risk.

Exploratory metabolomics of nascent metabolic syndrome.

INTRODUCTION: Metabolic syndrome (MetS) is a disorder defined by having three of five features: increased waist circumference (WC), hypertriglyceridemia, decreased high-density lipoprotein-cholesterol, hypertension and an elevated blood glucose (BG). Metabolic Syndrome ( MetS) affects 35% of American adults and significantly increases risk for Atherosclerotic cardiovascular disease (ASCVD) and type-2 diabetes (T2DM). An understanding of the metabolome will help elucidate the pathogenesis of MetS and lead to better management. We hypothesize that the metabolites, gamma-aminobutyric acid (GABA), d-pyroglutamic acid (PGA) and N-acetyl-d-tryptophan (NAT) will be altered in nascent MetS patients without the confounding of ASCVD or T2DM. We also correlated these metabolites with biomarkers of inflammation. PATIENTS AND METHODS: This was an exploratory study of 30 patients with nascent MetS and 20 matched controls undertaken in 2018. Metabolites were evaluated from patient's frozen early morning urine samples and were correlated with biomarkers of inflammation and adipokines. They were assayed by the NIH Western Metabolomics Center using liquid chromatography/mass spectrometry and standardized to urinary creatinine. All patients had normal hepatic and renal function. RESULTS: GABA and PGA levels were significantly increased in MetS patients compared to controls: 2.8-fold and 2.9-fold median increases respectively with p < 0.0001 and p = 0.004, possibly deriving from glutamate. NAT was significantly decreased by 90% in MetS patients compared to controls, p < 0.001. GABA correlates significantly with cardio-metabolic (CM) features including WC, blood pressure systolic (BP-S) while NAT correlated inversely with WC, BP-S, blood glucose (BG) and triglycerides (TG). GABA correlated positively with chemerin, leptin, Fetuin A and endotoxin. NAT correlated inversely with WC, BP-S, BG, TG, high sensitivity C - reactive protein (hsCRP), toll-like receptor-4 (TLR-4), lipopolysaccharide binding protein (LBP), chemerin and retinol binding protein-4 (RBP-4). CONCLUSIONS: We make the novel observation of increased GABA and PGA with decreased NAT in patients with MetS. While GABA and PGA correlates positively with CM features and biomediators of inflammation, the metabolite NAT correlated inversely. Thus, GABA and PGA could contribute to the pro-inflammatory state of MetS while NAT could mitigate this pro-inflammatory response.