抗菌药物短缺期间抗菌药物管理项目数据集

日本大学附属医院抗菌药物短缺期间抗菌药物管理项目的单中心回顾性观察数据集,纳入24,601名住院患者,含用药、微生物、结局和成本指标。

NIAID Data Ecosystem
浏览 5
表格/时间序列staphylococcus aureus </series analysis adjustedpseudomonas aeruginosa </infectious disease specialistsinfectious disease specialistformal consultation servicecarbapenems per patientbecoming common owingbayesian structural timelimited antimicrobial supplyantimicrobial stewardship programspectrum antibiotic use
Antimicrobial Stewardship Program Dataset during Antimicrobial Shortages

基本信息

模态
表格/时间序列
许可
CC BY 4.0
创建/更新时间
2026-10-17
版本
v1

资源简介

抗菌药物短缺期间抗菌药物管理项目数据集

【一句话概览】

本数据集是 figshare 公开的结构化表格数据集,收录 1 个文件、合计 32.08 KB,主题涵盖 series analysis adjusted、infectious disease specialists、infectious disease specialist、formal consultation service、carbapenems per patient,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《Dataset.》。源站首次发布:2026-02-02。

【数据内容】

源站原始描述:Since antimicrobial shortages are becoming common owing to manufacturing issues and sudden demand, individualized antimicrobial optimization by infectious disease specialists is essential. We evaluated the effects of a 12-month antimicrobial stewardship program at a university-affiliated hospital in Japan during antimicrobial shortages. In this single-center retrospective observational study, from April 1, 2023, to March 31, 2025, we compared the pre-intervention (antimicrobial stewardship progr…

【数据结构与技术规格】

文件数 1 个,合计 32.08 KB。pone.0340599.s002.xlsx:application/vnd.openxmlformats-officedocument.spreadsheetml.sheet,32.08 KB。数据集 DOI:10.1371/journal.pone.0340599.s002。

【主题与分类】

源站学科分类:Medicine、Environmental Sciences not elsewhere classified、Biological Sciences not elsewhere classified、Infectious Diseases、Virology、Computational Biology。主题标签:series analysis adjusted、infectious disease specialists、infectious disease specialist、formal consultation service、carbapenems per patient、becoming common owing、bayesian structural time、limited antimicrobial supply、antimicrobial stewardship program、spectrum antibiotic use。

【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/_p_Dataset_p_/31234006

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

规范引用:Itoh, Naoya; Okumura, Nobumasa; Akazawa-Kai, Nana; Wachino, Chiharu; Kuriki, Shunsuke; Kawabata, Takanori (2026). Dataset.. PLOS ONE. Dataset

官方服务

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陕川双基地 × 超十家三甲医院直连

从合规授权、采集治理、专业标注到数据集交付,我们提供全链路闭环服务,让高质量临床数据即拿即用。

⚡️ 需要原始数据或标注支持?联系我们获取定制方案。

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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 "pone.0340599.s002.xlsx" "https://ndownloader.figshare.com/files/61583395"

文件清单

  • pone.0340599.s002.xlsx(32.08 KB)

文件总体积 32.08 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

Since antimicrobial shortages are becoming common owing to manufacturing issues and sudden demand, individualized antimicrobial optimization by infectious disease specialists is essential. We evaluated the effects of a 12-month antimicrobial stewardship program at a university-affiliated hospital in Japan during antimicrobial shortages. In this single-center retrospective observational study, from April 1, 2023, to March 31, 2025, we compared the pre-intervention (antimicrobial stewardship program without infectious disease specialists) and post-intervention (antimicrobial stewardship program with infectious disease specialists and formal consultation service) periods. The evaluated outcomes included antimicrobial use, microbiological indicators (number of culture specimens submitted and hospital-acquired resistant organisms), patient outcomes (in-hospital mortality and length of hospital stay), and antimicrobial costs. A Bayesian structural time-series analysis adjusted for seasonality was used to assess intervention effects. In total, 24,601 inpatients were included (11,782 before intervention and 12,819 after). Shortages affected nine intravenous and two oral antibiotics. The antimicrobial stewardship program team provided 1110 feedback instances (acceptance rate, 74.1%) and conducted 172 infectious disease consultations in the post-intervention period. Carbapenem use, antipseudomonal agent use, incidence of carbapenem-resistant Pseudomonas aeruginosa, and the cost of carbapenems per patient-day significantly decreased. Narrow-spectrum antibiotic use, anti-methicillin-resistant Staphylococcus aureus agent use, all intravenous antimicrobial use, total intravenous and oral antimicrobials, and the number of inpatient specimens were significantly increased. All antimicrobial costs, in-hospital mortality, and length of hospital stay remained unchanged. Antimicrobial stewardship program supported by infectious disease specialists/consultants significantly reduced carbapenem and antipseudomonal agent use without negatively affecting patient outcomes. These findings highlight infectious disease specialists’ critical role in supporting effective antimicrobial stewards

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0340599.s002(source: https://plos.figshare.com/articles/dataset/_p_Dataset_p_/31234006)。

数据缺失?

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