A cross-sectional study on fatigue, anxiety, and symptoms of depression and their relation with medical status in adult patients with Marfan syndrome:Psychological consequences in Marfan syndrome

Marfan syndrome (MFS) is a connective tissue disorder affecting the cardiovascular, ocular, and skeletal system, which may be accompanied by psychological features. This study aimed to determine the prevalence of fatigue, anxiety, and symptoms of depression in MFS patients, and to assess the degree to which sociodemographic and clinical variables are associated with fatigue and psychological aspects. The prevalence of fatigue, anxiety, and symptoms of depression were assessed in two cohorts of MFS patients and compared with healthy controls. The checklist individual strength (CIS), and hospital anxiety and depression scale (HADS) questionnaires were utilized. Medical status was assessed (family history of MFS, aortic root dilatation >40 mm, previous aortic surgery, aortic dissection, chronic pain, skeletal involvement, and scoliosis). Severe fatigue was experienced by 37% of the total MFS cohort (n = 155). MFS patients scored significantly higher on the CIS questionnaire, concerning severe fatigue, as compared with the general Dutch population (p < 0.0001). There were no differences in HADS anxiety or depression scores. In older MFS patients, with a more severe cardiovascular phenotype, chronic pain, and a higher unemployment rate, significantly more symptoms of depression were observed, when compared with the general population (p = 0.027) or compared with younger MFS patients (p = 0.026). Multivariate analysis, showed that anxiety was associated with chronic pain (p = 0.022) and symptoms of depression with unemployment (p = 0.024). MFS patients report significantly more severe fatigue as compared with the general population. Since the cause of fatigue is unclear, more research may be needed. Psychological intervention, for example, cognitive behavioral therapy, may contribute to a reduction in psychological symptoms

Predictive added value of selected plasma lipids to a re-estimated minimal risk tool

Background: Lipidomics is emerging for biomarker discovery in cardiovascular disease, and circulating lipids are increasingly incorporated in risk models to predict cardiovascular events. Moreover, specific classes of lipids, such as sphingomyelins, ceramides, and triglycerides, have been related to coronary artery disease (CAD) severity and plaque characteristics. To avoid unnecessary testing, it is important to identify individuals at low CAD risk. The only pretest model available so far to rule out the presence of coronary atherosclerosis in patients with chest pain, but normal coronary arteries, is the minimal risk tool (MRT).Aim: Using state-of-the-art statistical methods, we aim to verify the additive predictive value of a set of lipids, derived from targeted plasma lipidomics of suspected CAD patients, to a re-estimated version of the MRT for ruling out the presence of coronary atherosclerosis assessed by coronary CT angiography (CCTA).Methods: Two hundred and fifty-six subjects with suspected stable CAD recruited from five European countries within H2020-SMARTool, undergoing CCTA and blood sampling for clinical biochemistry and lipidomics, were selected. The MRT was validated by regression methods and then re-estimated (reMRT). The reMRT was used as a baseline model in a likelihood ratio test approach to assess the added predictive value of each lipid from 13 among ceramides, triglycerides, and sphingomyelins. Except for one lipid, the analysis was carried out on more than 240 subjects for each lipid. A sensitivity analysis was carried out by considering two alternative models developed on the cohort as baseline models.Results: In 205 subjects, coronary atherosclerosis ranged from minimal lesions to overt obstructive CAD, while in 51 subjects (19.9%) the coronary arteries were intact. Four triglycerides and seven sphingomyelins were significantly (p < 0.05) and differentially expressed in the two groups and, at a lesser extent, one ceramide (p = 0.067). The probability of being at minimal risk was significantly better estimated by adding either Cer(d18:1/16:0) (p = 0.01), SM(40:2) (p = 0.04), or SM(41:1) at a lesser extent (p = 0.052) to reMRT than by applying the reMRT alone. The sensitivity analysis confirmed the relevance of these lipids. Furthermore, the addition of SM(34:1), SM(38:2), SM(41:2), and SM(42:4) improved the predictive performance of at least one of the other baseline models. None of the selected triglycerides was found to provide an added value.Conclusions: Plasma lipidomics can be a promising source of diagnostic and prognostic biomarkers in cardiovascular disease, exploitable not only to assess the risk of adverse events but also to identify subjects without coronary atherosclerosis, thus reducing unnecessary further testing in normal subjects.Cardiolog

Cardiac ¹²³I-MIBG Parameters at 4 Hours Derived from Earlier Acquisition Times

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New Insights on Carpentier I Mitral Regurgitation from Multidetector Row Computed Tomography

Cardiolog

Evaluation of sampling density on the accuracy of aortic pulse wave velocity from velocity-encoded MRI in patients with Marfan syndrome

Purpose: To evaluate the effect of spatial (ie, number of sampling locations along the aorta) and temporal sampling density on aortic pulse wave velocity (PWV) assessment from velocity-encoded MRI in patients with Marfan syndrome (MFS). Materials and Methods: Twenty-three MFS patients (12 men, mean age 36 ± 14 years) were included. Three PWV-methods were evaluated: 1) reference PWVi.p. from in-plane velocity-encoded MRI with dense temporal and spatial sampling; 2) conventional PWVt.p. from through-plane velocity-encoded MRI with dense temporal but sparse spatial sampling at three aortic locations; 3) EPI-accelerated PWVt.p. with sparse temporal but improved spatial sampling at five aortic locations with acceleration by echo-planar imaging (EPI). Results: Despite inferior temporal resolution, EPI-accelerated PWVt.p. showed stronger correlation (r = 0.92 vs. r = 0.65, P = 0.03) with reference PWVi.p. in the total aorta, with less error (8% vs. 16%) and variation (11% vs. 27%) as compared to conventional PWVt.p.. In the aortic arch, correlation was comparable for both EPI-accelerated and conventional PWVt.p. with reference PWVi.p. (r = 0.66 vs. r = 0.67, P = 0.46), albeit 92% scan-time reduction by EPI-acceleration. Conclusion: Improving spatial sampling density by adding two acquisition planes along the aorta results in more accurate PWV assessment, even when temporal resolution decreases. For regional PWV assessment in the aortic arch, EPI-accelerated and conventional PWV assessment are comparably accurate. Scan-time reduction makes EPI-accelerated PWV assessment the preferred method of choice