Single ventricular assist device (SVAD) use before and after stage I palliation (S1P) is increasing with limited data on outcomes. To address this knowledge gap, we conducted a single-center retrospective review to assess pre- and post-SVAD clinical status, complications, and outcomes. We leveraged a granular, longitudinal, local database that captures end-organ support, procedural interventions, hematologic events, laboratory data, and antithrombotic strategy. We identified 25 patients between 2013 and 2023 implanted at median age of 53 days (interquartile range [IQR] = 16-130); 80% had systemic right ventricles and underwent S1P. Median SVAD days were 54 (IQR = 29-86), and 40% were implanted directly from ECMO. Compared to preimplant, there was a significant reduction in inotrope use ( p = 0.013) and improved weight gain ( p = 0.008) post-SVAD. Complications were frequent including bleeding (80%), stroke (40%), acute kidney injury (AKI) (40%), infection (36%), and unanticipated catheterization (56%). Patients with in-hospital mortality had significantly more bleeding complications ( p = 0.02) and were more likely to have had Blalock-Thomas-Taussig shunts pre-SVAD ( p = 0.028). Survival to 1 year postexplant was 40% and included three recovered and explanted patients. At 1 year posttransplant, all survivors have technology dependence or neurologic injury. This study highlights the clinical outcomes and ongoing support required for successful SVAD use in failed single-ventricle physiology before or after S1P.
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http://dx.doi.org/10.1097/MAT.0000000000002149 | DOI Listing |
Gen Thorac Cardiovasc Surg Cases
January 2025
Osaka Metropolitan University Graduate School of Medicine, 1-4-3, Asahimachi, Abeno-Ku, Osaka, 545-8585, Japan.
Background: Repair of the regurgitant bicuspid aortic valve is an attractive alternative to valve replacement. Although good long-term outcomes have been reported, postoperative aortic stenosis remains a major late cause of repair failure in bicuspid aortic valves. Sinus plication is effective for creating a more symmetrical commissural angle, leading to a decrease in the mean transvalvular pressure gradient.
View Article and Find Full Text PDFJ Cardiovasc Imaging
January 2025
Division of Endocrinology and Metabolism, Department of Medicine, Samsung Medical Center, Sungkyunkwan University School of Medicine, Seoul, Republic of Korea.
Background: There are insufficient studies to determine whether sodium-glucose cotransporter type 2 inhibitors (SGLT2i) will help reduce early diabetic cardiomyopathy, especially in patients without documented cardiovascular disease.
Methods: We performed a single center, prospective observation study. A total of 90 patients with type 2 diabetes patients without established heart failure or atherosclerotic cardiovascular disease were enrolled.
Pediatr Nephrol
January 2025
Division of Pediatric Cardiology, Ann and Robert H. Lurie Children's Hospital of Chicago, Chicago, IL, USA.
Background: In adults with chronic kidney disease (CKD), abnormal left atrial reservoir strain (LASr) is an early, yet clinically significant, indicator of myocardial dysfunction. However, left atrial mechanics are understudied in youth with CKD. The objective of this study was to assess left atrial strain function in youth with CKD and similarly aged, healthy controls.
View Article and Find Full Text PDFNat Commun
January 2025
Department of Neurology and National Center for Neurological Disorders, Huashan Hospital, State Key Laboratory of Medical Neurobiology and MOE Frontiers Center for Brain Science, Shanghai Medical College, Fudan University, Shanghai, China.
Brain glymphatic activity, as indicated by diffusion-tensor imaging analysis along the perivascular space (ALPS) index, is involved in developmental neuropsychiatric and neurodegenerative diseases, but its genetic architecture is poorly understood. Here, we identified 17 unique genome-wide significant loci and 161 candidate genes linked to the ALPS-indexes in a discovery sample of 31,021 individuals from the UK Biobank. Seven loci were replicated in two independent datasets.
View Article and Find Full Text PDFEur Heart J
January 2025
Department of Internal Medicine, Section of Cardiovascular Medicine, Yale School of Medicine, New Haven, CT 06510, USA.
Background And Aims: Current heart failure (HF) risk stratification strategies require comprehensive clinical evaluation. In this study, artificial intelligence (AI) applied to electrocardiogram (ECG) images was examined as a strategy to predict HF risk.
Methods: Across multinational cohorts in the Yale New Haven Health System (YNHHS), UK Biobank (UKB), and Brazilian Longitudinal Study of Adult Health (ELSA-Brasil), individuals without baseline HF were followed for the first HF hospitalization.
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