Objectives: To quantify the uncertainty in the cost-effectiveness of lifestyle intervention versus standard care in overweight and obese people in Switzerland and to determine if further research is necessary based on current information. There has been an increasing interest in using value of information analysis in medical decision-making to quantify the uncertainty in decision-making, and to identify the need for further research.
Methods: Value of information analysis was applied on a probabilistic cost-effectiveness model to evaluate the uncertainty by calculating the patient expected value of perfect information (EVPI), population EVPI, and partial EVPI. The costs were expressed in Swiss Francs (CHF), price year 2006.
Results: Overall, the EVPI was higher in overweight than in obese people. The maximum population EVPI was CHF 6.8 million in overweight people and CHF 3.2 million in moderate obese people, representing the upper limit on costs associated with decision uncertainty. The partial EVPI estimated a higher uncertainty in the model parameters such as utilities, body mass index, cardiovascular risk factors, and systolic blood pressure in overweight and moderate obese subjects.
Conclusions: The EVPI analysis indicates that there is some uncertainty regarding the choice between lifestyle intervention and standard care. The parameter EVPI suggests that if further research is commissioned, this should focus on the effectiveness of lifestyle intervention on cardiovascular risk factors and utilities.
Download full-text PDF |
Source |
|---|---|
| http://dx.doi.org/10.1111/j.1524-4733.2007.00284.x | DOI Listing |
Publication Analysis
Top Keywords
Similar Publications
Web application using machine learning to predict cardiovascular disease and hypertension in mine workers.
Sci Rep
December 2024
Department of Applied Mathematics, Faculty of Mathematical Science, Ferdowsi University of Mashhad, Mashhad, Iran.
This study presents a web application for predicting cardiovascular disease (CVD) and hypertension (HTN) among mine workers using machine learning (ML) techniques. The dataset, collected from 699 participants at the Gol-Gohar mine in Iran between 2016 and 2020, includes demographic, occupational, lifestyle, and medical information. After preprocessing and feature engineering, the Random Forest algorithm was identified as the best-performing model, achieving 99% accuracy for HTN prediction and 97% for CVD, outperforming other algorithms such as Logistic Regression and Support Vector Machines.
View Article and Find Full Text PDFApplication of green silver nano-particles as anti-bacterial and photo-catalytic degradation of azo dye in wastewater.
Sci Rep
December 2024
Sustainability Solutions Research Lab, Faculty of Engineering, University of Pannonia, Egyetem Str. 10, Veszprém, 8200, Hungary.
Ensuring everyone enjoys healthy lifestyles and well-being at all ages, Progress has been made in increasing access to clean water and sanitation facilities and reducing the spread of epidemics and diseases. The synthesis of nano-particles (NPs) by using microalgae is a new nanobiotechnology due to the use of the biomolecular (corona) of microalgae as a capping and reducing agent for NP creation. This investigation explores the capacity of a distinct indigenous microalgal strain to synthesize silver nano-particles (AgNPs), as well as its effectiveness against multi-drug resistant (MDR) bacteria and its ability to degrade Azo dye (Methyl Red) in wastewater.
View Article and Find Full Text PDFA qualitative study on facilitators and barriers to adoption and implementation of nutrition interventions in higher education settings in Flanders.
Sci Rep
December 2024
Department of Movement and Sport Sciences, Faculty of Physical Education and Physiotherapy, Vrije Universiteit Brussel, Pleinlaan 2, 1050, Brussels, Belgium.
The transition from secondary school to college or university is a well-known and well-studied risk period for weight and/or fat gain and not meeting the dietary recommendations. Higher education acts as a promising setting to implement nutrition interventions. An important condition for intervention success is that interventions are implemented as intended by the protocol and integrated in the institutional policy.
View Article and Find Full Text PDFPredicting Sarcopenia and Frailty Risk in Patients Post Heart Transplantation.
Clin Transplant
January 2025
Rehabilitation Research Center (REVAL), Faculty of Rehabilitation Sciences, Hasselt University, Diepenbeek, Belgium.
Introduction: Currently, there is little evidence on the prevalence and factors associated with sarcopenia risk or frailty risk in patients post heart transplantation (HTx). The objective of this study was to analyze the influence of sociodemographic, lifestyle, physical, and psychological factors on sarcopenia and frailty risk in patients post-HTx.
Methods: 133 patients post-HTx (59.
Teaching Preclinical Medical Students Lifestyle Counseling Skills for Patients' Health Behavior Change.
MedEdPORTAL
December 2024
Associate Professor, Department of Medical Education, and Assistant Dean, Clinical Skills Education, Wright State University Boonshoft School of Medicine.
Introduction: Physicians face barriers to counseling patients regarding lifestyle, specifically, low perceived importance of and confidence in counseling, leading to underuse. There is a dearth in the literature evaluating educational interventions for counseling skills among preclinical medical students. Closing this gap is crucial to taking advantage of critical opportunities early in training.
View Article and Find Full Text PDFWant 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!