Objectives: To study the economic impact on payers and providers of the four main endovascular strategies for the treatment of infrainguinal peripheral artery disease.
Background: Bare metal stents (BMS), drug-eluting stents (DES), and drug-coated balloons (DCB) are associated with lower target lesion revascularization (TLR) probabilities than percutaneous transluminal angioplasty (PTA), but the economic impact is unknown.
Methods: In December 2012, PubMed and Embase were systematically searched for studies with TLR as an endpoint. The 24-month probability of TLR for each treatment was weighted by sample size. A decision-analytic Markov model was used to assess the budget impact from payers' and facility-providers' perspectives of the four index procedure strategies (BMS, DES, DCB, and PTA). Base cases were developed for U.S. Medicare and the German statutory sickness fund perspectives using current 2013 reimbursement rates.
Results: Thirteen studies with 2,406 subjects were included. The reported probability of TLR in the identified studies varied widely, particularly following treatment with PTA or BMS. The pooled 24-month probabilities were 14.3%, 19.3%, 28.1%, and 40.3% for DCB, DES, BMS, and PTA, respectively. The drug-eluting strategies had a lower projected budget impact over 24 months compared to BMS and PTA in both the U.S. Medicare (DCB: $10,214; DES: $12,904; uncoated balloons $13,114; BMS $13,802) and German public health care systems (DCB €3,619; DES €3,632; BMS €4,026; PTA €4,290).
Conclusions: DCB and DES, compared to BMS and PTA, are associated with lower probabilities of target lesion revascularization and cost savings for U.S. and German payers.
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http://dx.doi.org/10.1002/ccd.25536 | DOI Listing |
Sci Data
January 2025
Department of Earth and Environmental Engineering, Columbia University, New York, USA.
The Gravity Recovery and Climate Experiment (GRACE) and its follow-on (GRACE-FO) missions have provided estimates of Terrestrial Water Storage Anomalies (TWSA) since 2002, enabling the monitoring of global hydrological changes. However, temporal gaps within these datasets and the lack of TWSA observations prior to 2002 limit our understanding of long-term freshwater variability. In this study, we develop GRAiCE, a set of four global monthly TWSA reconstructions from 1984 to 2021 at 0.
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January 2025
Federal State Budget-Financed Educational Institution of Higher Education, The Bonch-Bruevich Saint-Petersburg State University of Telecommunications, 193232 St. Petersburg, Russia.
This study investigated the surface microbiome of the honeybee (), focusing on the diversity and functional roles of its associated microbial communities. While the significance of the microbiome to insect health and behavior is increasingly recognized, research on invertebrate surface microbiota lags behind that of vertebrates. A combined metagenomic and cultivation-based approach was employed to characterize the bacterial communities inhabiting the honeybee exoskeleton.
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January 2025
Department of Computer Science, University of Saskatchewan, Saskatoon, SK, Canada.
Introduction: Active learning can significantly decrease the labeling cost of deep learning workflows by prioritizing the limited labeling budget to high-impact data points that have the highest positive impact on model accuracy. Active learning is especially useful for semantic segmentation tasks where we can selectively label only a few high-impact regions within these high-impact images. Most established regional active learning algorithms deploy a static-budget querying strategy where a fixed percentage of regions are queried in each image.
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School of Earth Sciences, East China University of Technology, Nanchang, 330013, China.
Investigating the effects of urbanization at the county level on the balance of the carbon budget is essential for progress toward achieving "dual carbon" objectives at the county scale. Based on land use and economic data, this study elucidates the spatiotemporal evolution of urbanization and carbon budget balance ratio in 84 counties in Jiangxi Province from 1980 to 2020. Optimal geographic detectors and geographically weighted random forests were used to explore the impact of urbanization on the carbon budget balance ratio.
View Article and Find Full Text PDFJ Imaging Inform Med
January 2025
Department of Electrical and Computer Engineering, Duke University, Durham, NC, USA.
Deep neural networks (DNNs) have demonstrated exceptional performance across various image segmentation tasks. However, the process of preparing datasets for training segmentation DNNs is both labor-intensive and costly, as it typically requires pixel-level annotations for each object of interest. To mitigate this challenge, alternative approaches such as using weak labels (e.
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