Objectives: The aim of this study was to evaluate the cost-effectiveness of exposure in vivo (EXP, a cognitive-behavioral treatment targeting pain-related fear) in Complex Regional Pain Syndrome Type I (CRPS-I), as compared to pain-contingent physical therapy (PPT).
Methods: Data from a randomized controlled trial were used to compare the cost-effectiveness of EXP versus PPT from a societal perspective. Intervention costs, other healthcare costs, costs to patient and family, and productivity losses were included. The main outcomes were changes in the SF-36 physical component scale and quality-adjusted life-years. Changes were followed until 6 months after treatment. Uncertainty was estimated using nonparametric bootstrap analysis, cost-effectiveness acceptability curves and cost-effectiveness planes. Sensitivity analyses were performed to check robustness of findings.
Results: Forty-six patients were randomized and thirty-eight completed the study. Over 6 months, EXP resulted in greater improvement in physical health-related quality of life and quality-adjusted life-years than PPT. Despite higher initial treatment costs, EXP showed a tendency to reduce all costs compared with PPT; healthcare costs were significantly reduced. Furthermore, the cost-effectiveness planes were in favor of EXP. Sensitivity analyses, for different program costs and complete cases only, confirmed robustness of these findings.
Conclusions: EXP, a cognitive-behavioral treatment, seems more cost-effective than PPT in CRPS patients with pain-related fear. The initial higher costs for EXP are offset by a long-term reduction of costs for healthcare use, and a tendency to lower work absenteeism and reduced societal costs. Due to low sample sizes, replication of findings is required to confirm results.
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http://dx.doi.org/10.1017/S0266462318000429 | DOI Listing |
Sci Rep
December 2024
Department of Production Engineering, KTH Royal Institute of Technology, 11428, Stockholm, Sweden.
This study investigates the implementation of collaborative route planning between trucks and drones within rural logistics to improve distribution efficiency and service quality. The paper commences with an analysis of the unique characteristics and challenges inherent in rural logistics, emphasizing the limitations of traditional methods while highlighting the advantages of integrating truck and drone technologies. It proceeds to review the current state of development for these two technologies and presents case studies that illustrate their application in rural logistics.
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December 2024
Division of Computational & Data Sciences, Washington University in St. Louis, St. Louis, MO, USA.
Context shapes how we perceive choices and, therefore, how we decide between them. For instance, a large body of literature on the "framing effect" demonstrates that people become more risk-seeking when choices are framed in terms of losses. Despite this research, it remains unknown how people make choices between contexts and how these choices affect subsequent decision making.
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December 2024
Consumer and Design Sciences, College of Human Science Auburn University, Auburn, Alabama, USA.
Bermuda grass (Cynodon dactylon) is a tropical grass found in all tropical and subtropical areas. It is widely found in Bangladesh and well known for its antimicrobial properties. Cotton gauze is a woven cloth which is used for wound dressing and wound cushioning.
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December 2024
Shandong University of Science and Technology, College of Transportation, Qingdao, 266590, China.
The optimization of auto parts supply chain logistics plays a decisive role in the development of the automotive industry. To reduce logistics costs and improve transportation efficiency, this paper addresses the joint optimization problem of multi-vehicle pickup and delivery transportation paths under time window constraints, coupled with the three-dimensional loading of goods. The model considers mixed time windows, three-dimensional loading constraints, cyclic pickup and delivery paths, varying vehicle loads and volumes, flow balance, and time window constraints.
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December 2024
Medical Image Analysis, Department of Biomedical Engineering, Eindhoven University of Technology, Eindhoven, The Netherlands.
Immune checkpoint inhibitor (ICI) treatment has proven successful for advanced melanoma, but is associated with potentially severe toxicity and high costs. Accurate biomarkers for response are lacking. The present work is the first to investigate the value of deep learning on CT imaging of metastatic lesions for predicting ICI treatment outcomes in advanced melanoma.
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