Destination ventricular assist device therapy (DT-VAD) is well accepted in select adults with medically refractory heart failure (HF) who are not transplant candidates; however, its use in younger patients with progressive diseases is unclear. We sought to evaluate the cost-effectiveness of DT-VAD in Duchenne muscular dystrophy (DMD) patients with advanced HF. We created a Markov-state transition model (5-year horizon) to compare survival, costs, and quality of life (QOL) between medical management and DT-VAD in DMD with advanced HF. Model input parameters were derived from the literature. We used sensitivity analyses to explore uncertainty around model assumptions. DT-VAD had higher costs ($435,602 vs. $125,696), survival (3.13 vs. 0.60 years), and quality-adjusted survival (1.99 vs. 0.26 years) than medical management. The incremental cost-effectiveness ratio (ICER) for DT-VAD was $179,086 per quality-adjusted life year (QALY). In sensitivity analyses that were widely varied to account for uncertainty in model assumptions, the DT-VAD strategy generally remained more costly and effective than medical management. Only when VAD implantation costs were <$113,142 did the DT-VAD strategy fall below the $100,000/QALY willingness-to-pay threshold commonly considered to be "cost-effective." In this exploratory analysis, DT-VAD for patients with DMD and advanced HF exceeded societal expectations for cost-effectiveness but had an ICER similar to the accepted practice of DT-VAD in adult HF patients. While more experience and research in this population is needed, our analysis suggests that DT-VAD for advanced HF in DMD should not be dismissed solely based on cost.

Download full-text PDF

Source
http://dx.doi.org/10.1007/s00246-018-1889-5DOI Listing

Publication Analysis

Top Keywords

medical management
12
ventricular assist
8
assist device
8
heart failure
8
duchenne muscular
8
muscular dystrophy
8
sensitivity analyses
8
uncertainty model
8
model assumptions
8
assumptions dt-vad
8

Similar Publications

Guidelines International Network: Principles for Use of Artificial Intelligence in the Health Guideline Enterprise.

Ann Intern Med

January 2025

Clinical Epidemiology and Research Center (CERC), Department of Biomedical Sciences, Humanitas University, and IRCCS Humanitas Research Hospital, Milan, Italy, and Fraunhofer Institute for Translational Medicine and Pharmacology ITMP, Allergology and Immunology, Berlin, Germany (H.J.S.).

Description: Artificial intelligence (AI) has been defined by the High-Level Expert Group on AI of the European Commission as "systems that display intelligent behaviour by analysing their environment and taking actions-with some degree of autonomy-to achieve specific goals." Artificial intelligence has the potential to support guideline planning, development and adaptation, reporting, implementation, impact evaluation, certification, and appraisal of recommendations, which we will refer to as "guideline enterprise." Considering this potential, as well as the lack of guidance for the use of AI in guidelines, the Guidelines International Network (GIN) proposes a set of principles for the development and use of AI tools or processes to support the health guideline enterprise.

View Article and Find Full Text PDF

Background: With the increasing implementation of patient online record access (ORA), various approaches to access to minors' electronic health records have been adopted globally. In Sweden, the current regulatory framework restricts ORA for minors and their guardians when the minor is aged between 13 and 15 years. Families of adolescents with complex health care needs often desire health information to manage their child's care and involve them in their care.

View Article and Find Full Text PDF

Background: Congenital heart disease (CHD) is a birth defect of the heart that requires long-term care and often leads to additional health complications. Effective educational strategies are essential for improving health literacy and care outcomes. Despite affecting around 40,000 children annually in the United States, there is a gap in understanding children's health literacy, parental educational burdens, and the efficiency of health care providers in delivering education.

View Article and Find Full Text PDF

Background: Acute pain management is critical in postoperative care, especially in vulnerable patient populations that may be unable to self-report pain levels effectively. Current methods of pain assessment often rely on subjective patient reports or behavioral pain observation tools, which can lead to inconsistencies in pain management. Multimodal pain assessment, integrating physiological and behavioral data, presents an opportunity to create more objective and accurate pain measurement systems.

View Article and Find Full Text PDF

Enhancing Diagnostic Accuracy of Lung Nodules in Chest Computed Tomography Using Artificial Intelligence: Retrospective Analysis.

J Med Internet Res

January 2025

Department of Health Policy and Management, Bloomberg School of Public Health, Johns Hopkins University, Baltimore, MD, United States.

Background: Uncertainty in the diagnosis of lung nodules is a challenge for both patients and physicians. Artificial intelligence (AI) systems are increasingly being integrated into medical imaging to assist diagnostic procedures. However, the accuracy of AI systems in identifying and measuring lung nodules on chest computed tomography (CT) scans remains unclear, which requires further evaluation.

View Article and Find Full Text PDF

Want AI Summaries of new PubMed Abstracts delivered to your In-box?

Enter search terms and have AI summaries delivered each week - change queries or unsubscribe any time!