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数据集获取（Figshare）

• 源站标题：Adherence score for Users of Oral Anticoagulants
• DOI：10.6084/m9.figshare.6503636.v1
• 发布日期：2018-06-13
• 文件数：6 个
• 文件总体积：801.52 KB
• 源站页面：https://scielo.figshare.com/articles/dataset/Adherence_score_for_Users_of_Oral_Anticoagulants/6503636

命令行下载

curl -L -o "2359-4802-ijcs-20180028-gf01.jpg" "https://ndownloader.figshare.com/files/11957342"
curl -L -o "2359-4802-ijcs-20180028-gf02.jpg" "https://ndownloader.figshare.com/files/11957348"
curl -L -o "2359-4802-ijcs-20180028-gf03.jpg" "https://ndownloader.figshare.com/files/11957357"
curl -L -o "Table_1.xls" "https://ndownloader.figshare.com/files/11957360"
curl -L -o "Table_2.xls" "https://ndownloader.figshare.com/files/11957363"
curl -L -o "Table_3.xls" "https://ndownloader.figshare.com/files/11957369"

文件清单

• 2359-4802-ijcs-20180028-gf01.jpg（401.67 KB）
• 2359-4802-ijcs-20180028-gf02.jpg（180.73 KB）
• 2359-4802-ijcs-20180028-gf03.jpg（198.13 KB）
• Table_1.xls（5.63 KB）
• Table_2.xls（9.73 KB）
• Table_3.xls（5.63 KB）

文件总体积 801.52 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

Abstract Background: The score is an effective instrument for the assessment of treatment adherence in users of oral anticoagulants and maintenance of INR (international normalized ratio) within the therapeutic range. Objective: To develop an adherence score for oral anticoagulant users for the maintenance of INR within the therapeutic range. Methods: This was an analytical, observational, cross-sectional study, with a quantitative approach, conducted in a public cardiology hospital. A total of 607 patients who met the inclusion criteria were evaluated. Variables with a significance level of 5% in the exploratory analysis and considered clinically relevant were included and subjected to a multiple logistic regression model. Predictive accuracy of the model was determined using the C statistic. Results: The variables with a significance level of 5% in the multivariate analysis were: education, family income, inadequate use of medications, drug-drug interactions, invasive procedures, food-drug interactions, physical activity, medical conditions, other factors, and complications related to oral anticoagulant therapy. The following prognostic variables were identified: family income, inadequate use of medications, invasive procedures, drug-drug interactions, dietary habits, medical conditions, other factors (stress, thinness, weight loss). C-statistic for adherence score was 0.94. Conclusion: The Simonetti adherence score proved to be easily applicable and feasible, with high predictive value for influencing factors, promoting the improvement of adherence and maintenance of INR in the ideal range. (Int J Cardiovasc Sci. 2018; [online].ahead print, PP.0-0)

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.6503636.v1（source: https://scielo.figshare.com/articles/dataset/Adherence_score_for_Users_of_Oral_Anticoagulants/6503636）。