多重耐药对中国腹腔感染患者总医疗费用的影响

中国腹腔感染患者多重耐药与总医疗费用关系的回顾性电子病历数据,含101例患者费用和临床信息。

NIAID Data Ecosystem
浏览 5
表格IAIChina Background Multiple drugintra-abdominal infectionslaboratory test resultsTMCMDR pathogens37 non-MDR patientscombination antimicrobial therapy
Effect of multiple drug resistance on total medical costs among patients with intra-abdominal infections in China

基本信息

模态
表格
大小
0.000028913 GB
许可
CC BY 4.0
创建/更新时间
2026-10-10
版本
v1

资源简介

多重耐药对中国腹腔感染患者总医疗费用的影响

【一句话概览】

本数据集是 figshare 公开的结构化表格数据集,收录 2 个文件、合计 28.91 KB,主题涵盖 IAI、China Background Multiple drug、intra-abdominal infections、laboratory test results、TMC,可用于统计建模、特征工程与队列分析,CC BY 4.0 许可开放获取。

【数据集背景】

本数据集源站标题为《Effect of multiple drug resistance on total medical costs among patients with intra-abdominal infections in China》。配套论文《Effect of multiple drug resistance on total medical costs among patients with intra-abdominal infections in China》发表于 PLOS ONE(2018),DOI:10.1371/journal.pone.0193977。源站首次发布:2018-03-28。

【数据内容】

源站原始描述:Background Multiple drug resistant (MDR) intra-abdominal infections (IAIs) are associated with notable direct and societal costs. As previous studies have not considered the impact of MDR on the total medical costs (TMCs) of IAIs, the present one examines this, as well as further estimates the additional costs at a national level. Methods This is a retrospective study. Firstly, we randomly selected a sample of 40% of all inpatients discharged between 2014 and 2015 from a teaching hospital, due t…

【数据结构与技术规格】

文件数 2 个,合计 28.91 KB。S1 Table.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,14.59 KB。S2 Table.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,14.33 KB。数据集 DOI:10.1371/journal.pone.0193977。

【主题与分类】

源站学科分类:Medicine、Biotechnology、Ecology、Cancer、Infectious Diseases、Virology。主题标签:IAI、China Background Multiple drug、intra-abdominal infections、laboratory test results、TMC、MDR pathogens、37 non-MDR patients、combination antimicrobial therapy。

【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/Effect_of_multiple_drug_resistance_on_total_medical_costs_among_patients_with_intra-abdominal_infections_in_China/6054989

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Zhen, Xuemei; Li, Yuanyuan; Chen, Yixi; Dong, Peng; Liu, Stephanie; Dong, Hengjin (2018). Effect of multiple drug resistance on total medical costs among patients with intra-abdominal infections in China. 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。

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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)

命令行下载

curl -L -o "S1 Table.docx" "https://ndownloader.figshare.com/files/10907798"
curl -L -o "S2 Table.docx" "https://ndownloader.figshare.com/files/10907804"

文件清单

  • S1 Table.docx(14.59 KB)
  • S2 Table.docx(14.33 KB)

文件总体积 28.91 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

Background
Multiple drug resistant (MDR) intra-abdominal infections (IAIs) are associated with notable direct and societal costs. As previous studies have not considered the impact of MDR on the total medical costs (TMCs) of IAIs, the present one examines this, as well as further estimates the additional costs at a national level.
Methods
This is a retrospective study. Firstly, we randomly selected a sample of 40% of all inpatients discharged between 2014 and 2015 from a teaching hospital, due to limits in budget and the large number of patients. Then, we manually selected 254 patients with IAIs according to the International Classification of Disease, 10th revision, using electronic medical records. Eventually, 101 patients with IAIs (64 MDR patients and 37 non-MDR patients) were included after excluding cases without laboratory test results, any pathogens detected, or antimicrobial resistant pathogens. Univariate analysis and a generalized linear model were applied to assess the parameters associated with TMCs.
Results
Compared to non-MDR patients, those with MDR pathogens were significantly associated with higher TMCs, higher antimicrobial costs, higher antimicrobial usage, larger number of pathogens, and longer length of stay and were more likely to have insurance and combination antimicrobial therapy. In addition, the average TMC among patients with MDR pathogens was ¥ 131801, which is ¥ 90201 higher than those without MDR pathogens. If our results are applied to the whole country, the sum of all attributable TMCs was ¥ 37 billion. The societal costs, furthermore, were ¥111 billion in 2015.
Conclusion
Our results provide information that should lead to increased efforts to reduce inappropriate antimicrobial therapy, in order to decrease the emergence of MDR pathogens and to reduce their economic burden.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0193977(source: https://plos.figshare.com/articles/dataset/Effect_of_multiple_drug_resistance_on_total_medical_costs_among_patients_with_intra-abdominal_infections_in_China/6054989)。

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