透明抗菌敷料在重症监护室中心静脉和动脉导管管理中的成本效益分析
基于多中心RCT数据的成本效益分析模型数据集,评估抗菌敷料在ICU中预防导管相关血流感染的经济效果。

基本信息
资源简介
透明抗菌敷料在重症监护室中心静脉和动脉导管管理中的成本效益分析
【数据集背景】
本数据集源站标题为《Cost-Effectiveness Analysis of a Transparent Antimicrobial Dressing for Managing Central Venous and Arterial Catheters in Intensive Care Units》。配套论文《Cost-Effectiveness Analysis of a Transparent Antimicrobial Dressing for Managing Central Venous and Arterial Catheters in Intensive Care Units》发表于 PLOS ONE(2015),DOI:10.1371/journal.pone.0130439。源站首次发布:2015-06-18。
【数据内容】
源站原始描述:Objective To model the cost-effectiveness impact of routine use of an antimicrobial chlorhexidine gluconate-containing securement dressing compared to non-antimicrobial transparent dressings for the protection of central vascular lines in intensive care unit patients. Design This study uses a novel health economic model to estimate the cost-effectiveness of using the chlorhexidine gluconate dressing versus transparent dressings in a French intensive care unit scenario. The 30-day time non-homoge…
【数据结构与技术规格】
文件数 2 个,合计 39.67 KB。S1_Table.xlsx:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet,19.76 KB。S2_Table.xlsx:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet,19.91 KB。数据集 DOI:10.1371/journal.pone.0130439。
【主题与分类】
源站学科分类:Biological Sciences、Science Policy。主题标签:source randomized、intravascular catheterization、estimated.Patients 1000 patients、French multicentre study、Intensive Care Units ObjectiveTo model、cost difference、dressing strategy、Transparent Antimicrobial Dressing、care unit patients.DesignThis study、novel health。
【适用方向】
结构化表格数据可直接用于统计建模、特征工程与队列分析。
【获取与许可】
源站页面:https://plos.figshare.com/articles/dataset/_Cost_Effectiveness_Analysis_of_a_Transparent_Antimicrobial_Dressing_for_Managing_Central_Venous_and_Arterial_Catheters_in_Intensive_Care_Units_/1453835
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Maunoury, Franck; Motrunich, Anastasiia; Palka-Santini, Maria; F. Bernatchez, Stéphanie; Ruckly, Stéphane; Timsit, Jean-François (2016). Cost-Effectiveness Analysis of a Transparent Antimicrobial Dressing for Managing Central Venous and Arterial Catheters in Intensive Care Units. PLOS ONE. Dataset
【使用注意】
· 源站最后修改于 2023-05-30,引用时请注意版本时效。
下载信息
注册下载
需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。
暂未开放公开下载
无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。
免登录有偿下载
公开数据集受托下载与技术交付服务。
提供高速下载与技术交付服务(收技术服务费,非数据销售)
暂未开放当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。
使用方式
数据集获取(Figshare)
- 源站标题:Cost-Effectiveness Analysis of a Transparent Antimicrobial Dressing for Managing Central Venous and Arterial Catheters in Intensive Care Units
- DOI:10.1371/journal.pone.0130439
- 发布日期:2015-06-18
- 文件数:2 个
- 文件总体积:39.67 KB
- 源站页面:https://plos.figshare.com/articles/dataset/_Cost_Effectiveness_Analysis_of_a_Transparent_Antimicrobial_Dressing_for_Managing_Central_Venous_and_Arterial_Catheters_in_Intensive_Care_Units_/1453835
命令行下载
curl -L -o "S1_Table.xlsx" "https://ndownloader.figshare.com/files/2125490"
curl -L -o "S2_Table.xlsx" "https://ndownloader.figshare.com/files/2125491"
文件清单
S1_Table.xlsx(19.76 KB)S2_Table.xlsx(19.91 KB)
文件总体积 39.67 KB(源站 API 实测)。
数据加载示例(图像类)
from PIL import Image
import glob, os
files = (glob.glob(os.path.join(path, "**", "*.png"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.jpg"), recursive=True)
+ glob.glob(os.path.join(path, "**", "*.tif"), recursive=True))
print("图像文件数:", len(files))
img = Image.open(files[0]); print("尺寸/模式:", img.size, img.mode)
# torchvision Dataset 方式:
# from torchvision import datasets
# ds = datasets.ImageFolder(path) # 要求 子目录=类别
目录组织与标注格式以源站说明和下载后实际文件为准。
数据说明
Objective
To model the cost-effectiveness impact of routine use of an antimicrobial chlorhexidine gluconate-containing securement dressing compared to non-antimicrobial transparent dressings for the protection of central vascular lines in intensive care unit patients.
Design
This study uses a novel health economic model to estimate the cost-effectiveness of using the chlorhexidine gluconate dressing versus transparent dressings in a French intensive care unit scenario. The 30-day time non-homogeneous markovian model comprises eight health states. The probabilities of events derive from a multicentre (12 French intensive care units) randomized controlled trial. 1,000 Monte Carlo simulations of 1,000 patients per dressing strategy are used for probabilistic sensitivity analysis and 95% confidence intervals calculations. The outcome is the number of catheter-related bloodstream infections avoided. Costs of intensive care unit stay are based on a recent French multicentre study and the cost-effectiveness criterion is the cost per catheter-related bloodstream infections avoided. The incremental net monetary benefit per patient is also estimated.
Patients
1000 patients per group simulated based on the source randomized controlled trial involving 1,879 adults expected to require intravascular catheterization for 48 hours.
Intervention
Chlorhexidine Gluconate-containing securement dressing compared to non-antimicrobial transparent dressings.
Results
The chlorhexidine gluconate dressing prevents 11.8 infections /1,000 patients (95% confidence interval: [3.85; 19.64]) with a number needed to treat of 85 patients. The mean cost difference per patient of €141 is not statistically significant (95% confidence interval: [€-975; €1,258]). The incremental cost-effectiveness ratio is of €12,046 per catheter-related bloodstream infection prevented, and the incremental net monetary benefit per patient is of €344.88.
Conclusions
According to the base case scenario, the chlorhexidine gluconate dressing is more cost-effective than the reference dressing.
Trial Registration
This model is based on the data from the RCT registered with www.clinicaltrials.gov (NCT01189682).
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0130439(source: https://plos.figshare.com/articles/dataset/_Cost_Effectiveness_Analysis_of_a_Transparent_Antimicrobial_Dressing_for_Managing_Central_Venous_and_Arterial_Catheters_in_Intensive_Care_Units_/1453835)。
数据缺失?
依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。
⚡️ 需要数据支持或标注服务?立即联系我们获取专业方案。




