救护车医生与OHCA患者预后条件逻辑回归分析数据集

数据集获取（Figshare）

• 源站标题：Conditional logistic regression analyses of a medical doctor in the ambulance car and outcome among propensity-matched patients with OHCA (n = 18,462).
• DOI：10.1371/journal.pone.0084424.t004
• 发布日期：2014-01-08
• 文件数：1 个
• 文件总体积：5.63 KB
• 源站页面：https://plos.figshare.com/articles/dataset/_Conditional_logistic_regression_analyses_of_a_medical_doctor_in_the_ambulance_car_and_outcome_among_propensity_matched_patients_with_OHCA_n_8202_8202_18_462_/897343

命令行下载

curl -L -o "Table_4.xls" "https://ndownloader.figshare.com/files/1342588"

文件清单

• Table_4.xls（5.63 KB）

文件总体积 5.63 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

OR: odds ratio; CI: confidence interval.
a: Significant variables in propensity-matched samples in listed Table 2 included relationship of bystander to patient, emergency life-saving technician in ambulance car, ALS by MD, and time from call to arrival at hospital.
b: Selected variables included age, sex, bystander eyewitness, relationship of bystander to patient, bystander chest compression, bystander rescue breathing, use of public-access AED by bystander, first documented rhythm, and time from call to arrival at the scene for a model with ROSC as a dependent variable. As for other models, ROSC and the above selected variables were adjusted.
c: All covariates included all variables except for endpoint variables listed in Table 1 plus 46 dummy variables for the 47 prefectures in Japan for a model with ROSC as a dependent variable. As for other models, ROSC, all variables except for endpoint variables listed in Table 1, and 46 dummy variables for the 47 prefectures in Japan were adjusted.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0084424.t004（source: https://plos.figshare.com/articles/dataset/_Conditional_logistic_regression_analyses_of_a_medical_doctor_in_the_ambulance_car_and_outcome_among_propensity_matched_patients_with_OHCA_n_8202_8202_18_462_/897343）。