Background: We aimed to characterise the impact of Down syndrome on myocardial performance and loading conditions in infants with Down syndrome and CHD over the peri-operative period by comparing them with infants matched for cardiac lesion with a normal microarray.
Methods: Left ventricular global longitudinal strain, right ventricular free wall longitudinal strain, left ventricular end-systolic wall stress, and right ventricular systolic pressure were measured in the two groups over the peri-operative period.
Results: Fifty-five infants had a diagnosis of Down syndrome and these were compared with 29 control infants. Left ventricular global longitudinal strain decreased in both groups post-operatively with the Down syndrome group demonstrating some recovery pre-discharge (18 ± 3 versus 16 ± 3 %, p = 0.01). Right ventricular longitudinal strain significantly decreased in both groups post-operatively with the control group demonstrating better recovery by hospital discharge (14 ± 4 versus 18 ± 6 %, p < 0.01). End-systolic wall stress was lower and right ventricular systolic pressure was higher in the Down syndrome group throughout the study period (all p < 0.05). Down syndrome was an independent predictor of the duration of ventilation, post-operative use of inotropes, and intensive care stay. Right ventricular longitudinal strain was an independent predictor of duration of intensive care stay.
Conclusion: This study demonstrates the difference between the two groups in relation to left and right ventricular function, particularly prior to discharge, and outlines the additional impact a diagnosis of Down syndrome has on myocardial performance during the peri-operative period.
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http://dx.doi.org/10.1017/S1047951121003449 | DOI Listing |
Circ Cardiovasc Imaging
January 2025
Division of Cardiology, Department of Medicine, University of California, San Francisco (L.C., S.D., D.B., J.J.T., Q.F., L.T., A.H.R., R.J., S.H., H.H.H., Z.H.T., N.B.S., F.N.D.).
Background: A subset of patients with mitral valve prolapse (MVP), a highly heritable condition, experience sudden cardiac arrest (SCA) or sudden cardiac death (SCD). However, the inheritance of phenotypic imaging features of arrhythmic MVP remains unknown.
Methods: We recruited 23 MVP probands, including 9 with SCA/SCD and 14 with frequent/complex ventricular ectopy.
Background: Diagnosis of cardiac amyloidosis (CA) is often missed or delayed due to confusion with other causes of increased left ventricular wall thickness. Conventional transthoracic echocardiographic measurements like global longitudinal strain (GLS) has shown promise in distinguishing CA, but with limited specificity. We conducted a study to investigate the performance of a computer vision detection algorithm in across multiple international sites.
View Article and Find Full Text PDFACS Nano
January 2025
Department of Biomedical Engineering, National Cheng Kung University, Tainan 70101, Taiwan.
Detection of biomarkers associated with physiological conditions provides critical insights into healthcare and disease management. However, challenges in sampling and analysis complicate the detection and quantification of protein biomarkers within the epidermal layer of the skin and in viscous liquid biopsy samples. Here, we present the "Lab-on-the-Needles" concept, utilizing a microneedle patch-based sensing box (MNP-based SenBox) for mobile healthcare applications.
View Article and Find Full Text PDFBMC Cardiovasc Disord
January 2025
Department of Ultrasonography, Affiliated Hospital of Hangzhou Normal University, Hangzhou, China.
Background: Long-term endurance training is associated with structural, functional, and biochemical markers of cardiac dysfunction in highly trained athletes. Many studies have focused on structural changes in the right ventricle (RV) and few have examined functional adaptation of the right ventricle. This meta-analysis aims to compare the changes in right ventricular systolic function between endurance athletes and controls before and after exercise using speckle tracking echocardiography (STE).
View Article and Find Full Text PDFBMJ Open
January 2025
Department of Mathematical Modelling and Artificial Intelligence, National Aerospace University Kharkiv Aviation Institute, Kharkiv, Ukraine.
Objective: To identify the early predictors of a self-reported persistence of long COVID syndrome (LCS) at 12 months after hospitalisation and to propose the prognostic model of its development.
Design: A combined cross-sectional and prospective observational study.
Setting: A tertiary care hospital.
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