医疗相关感染最小数据集

数据集获取（Figshare）

• 源站标题：Minimal data set.
• DOI：10.1371/journal.pone.0282141.s002
• 发布日期：2023-02-23
• 文件数：1 个
• 文件总体积：72.49 KB
• 源站页面：https://plos.figshare.com/articles/dataset/Minimal_data_set_/22150908

命令行下载

curl -L -o "pone.0282141.s002.dta" "https://ndownloader.figshare.com/files/39377778"

文件清单

• pone.0282141.s002.dta（72.49 KB）

文件总体积 72.49 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

Introduction
Healthcare-associated infections (HAIs) have become a serious public health problem. Despite the fact that implementing evidence-based infection control strategies could prevent HAIs and save billions of dollars, Ethiopia lacks national surveillance studies on the rate, economic, and clinical burden of HAIs.
Objective
To assess the clinical and economic burden of HAIs in hospitalized patients at Ayder comprehensive specialized hospital.
Materials and methods
A prospective cohort study design was conducted in patients with and without HAIs. A review of medical records, interviews, and patient bills was used to extract necessary information. The patients in the two arms were matched based on age, sex, Charlson comorbidity index, and ward type. Measurable factors were compared between infected and uninfected patients using the paired ttest or McNemar’s test, as appropriate. Logistic regression was used to identify predictors of in-hospital mortality. Stata 14.1 was used to conduct all analyses.
Results
A total of 408 patients, 204 with HAIs and 204 without HAIs were included in the study. In-hospital mortality was higher in patients with HAI (14.7% vs 7.8%, P = 0.028). Patients with HAI stayed an average of 8.3 days longer than controls (18.85 vs 10.59, PPConclusion
HAIs have a significant impact on in-hospital mortality, the length of extra hospital stays, and extra costs for medical care. Patients admitted to intensive care units and those with HAIs were found to be significant predictors of in-hospital mortality. Interventions must be implemented to prevent HAIs, especially in patients admitted to intensive care units.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0282141.s002（source: https://plos.figshare.com/articles/dataset/Minimal_data_set_/22150908）。