Costs of COPD Exacerbations in a General Population.

Cited 5|Views69

Abstract

Background: Studies on costs of COPD exacerbations from general populations are scarce. Objectives: To compare direct costs (treatment-related) and indirect costs (productivity-related) associated with COPD in population based and hospital-recruited samples, and to estimate the components related to moderate and severe exacerbations. Methods: We performed 4 telephone interviews with 81 COPD cases and 132 controls from a population-based survey and 205 hospital-recruited COPD-patients. A moderate exacerbation was defined by use of antibiotics or corticosteroids due to respiratory disease, and severe exacerbations by hospitalisation due to respiratory disease. The sum of direct and indirect costs gave the total costs. Initial analyses compared costs across the three groups, and multivariate quantile regression estimated the costs attributed to exacerbations. Results: The crude, annual mean total disease-related costs were €26518, €15021, and €6740 per person for the patients, cases, and controls (p<0.001), respectively. In multivariate analyses exacerbations explained a majority of both direct and indirect costs of COPD. Severe exacerbations accounted for €28329 (95% CI 11467, 45192) of the total costs of population based COPD. For hospital-recruited COPD patients, both moderate and severe exacerbations were significant cost drivers accounting for €3034 (467, 5600) and €8527 (3912, 13141) of the total costs. Among hospital-recruited COPD patients, increasing GOLD-stage was also significantly associated with elevated costs. Conclusion: The annual total health-related costs for a hospital-recruited COPD-patient were nearly twice that of a general population-based COPD-case. The most important cost driver was severe exacerbations.

Translated text

求助PDF

上传PDF

Bibtex

AI Read Science

AI Summary

AI Summary is the key point extracted automatically understanding the full text of the paper, including the background, methods, results, conclusions, icons and other key content, so that you can get the outline of the paper at a glance.

Example

Background

Key content

Introduction

Methods

Results

Related work

Fund

Key content

Pretraining has recently greatly promoted the development of natural language processing (NLP)
We show that M6 outperforms the baselines in multimodal downstream tasks, and the large M6 with 10 parameters can reach a better performance
We propose a method called M6 that is able to process information of multiple modalities and perform both single-modal and cross-modal understanding and generation
The model is scaled to large model with 10 billion parameters with sophisticated deployment, and the 10 -parameter M6-large is the largest pretrained model in Chinese
Experimental results show that our proposed M6 outperforms the baseline in a number of downstream tasks concerning both single modality and multiple modalities We will continue the pretraining of extremely large models by increasing data to explore the limit of its performance

Upload PDF to Generate Summary

Must-Reading Tree

Example

Generate MRT to find the research sequence of this paper