卒中团队与模拟训练在区域卒中网络中缩短处理时间的实施效果——一项网络前瞻性试验

数据集获取（Figshare）

• 源站标题：Implementation of stroke teams and simulation training shortened process times in a regional stroke network—A network-wide prospective trial
• DOI：10.1371/journal.pone.0188231
• 发布日期：2017-12-05
• 文件数：3 个
• 文件总体积：87.75 KB
• 源站页面：https://plos.figshare.com/articles/dataset/Implementation_of_stroke_teams_and_simulation_training_shortened_process_times_in_a_regional_stroke_network_A_network-wide_prospective_trial/5672932

命令行下载

curl -L -o "S1 File.docx" "https://ndownloader.figshare.com/files/9922339"
curl -L -o "S2 File.docx" "https://ndownloader.figshare.com/files/9922348"
curl -L -o "S3 File.docx" "https://ndownloader.figshare.com/files/9922351"

文件清单

• S1 File.docx（15.21 KB）
• S2 File.docx（34.80 KB）
• S3 File.docx（37.74 KB）

文件总体积 87.75 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
To meet the requirements imposed by the time-dependency of acute stroke therapies, it is necessary 1) to initiate structural and cultural changes in the breadth of stroke-ready hospitals and 2) to find new ways to train the personnel treating patients with acute stroke. We aimed to implement and validate a composite intervention of a stroke team algorithm and simulation-based stroke team training as an effective quality initiative in our regional interdisciplinary neurovascular network consisting of 7 stroke units.
Methods
We recorded door-to-needle times of all consecutive stroke patients receiving thrombolysis at seven stroke units for 3 months before and after a 2 month intervention which included setting up a team-based stroke workflow at each stroke unit, a train-the-trainer seminar for stroke team simulation training and a stroke team simulation training session at each hospital as well as a recommendation to take up regular stroke team trainings.
Results
The intervention reduced the network-wide median door-to-needle time by 12 minutes from 43,0 (IQR 29,8–60,0, n = 122) to 31,0 (IQR 24,0–42,0, n = 112) minutes (p Conclusions
The composite intervention of a binding team-based algorithm and stroke team simulation training showed to be well-transferable in our regional stroke network. We provide suggestions and materials for similar campaigns in other stroke networks.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0188231（source: https://plos.figshare.com/articles/dataset/Implementation_of_stroke_teams_and_simulation_training_shortened_process_times_in_a_regional_stroke_network_A_network-wide_prospective_trial/5672932）。