亚洲结核病诊断与治疗中患者和医生延迟的相关因素：系统回顾与荟萃分析

数据集获取（Figshare）

• 源站标题：Factors Associated with Patient and Provider Delays for Tuberculosis Diagnosis and Treatment in Asia: A Systematic Review and Meta-Analysis
• DOI：10.1371/journal.pone.0120088
• 发布日期：2015-03-25
• 文件数：4 个
• 文件总体积：322.05 KB
• 源站页面：https://plos.figshare.com/articles/dataset/_Factors_Associated_with_Patient_and_Provider_Delays_for_Tuberculosis_Diagnosis_and_Treatment_in_Asia_A_Systematic_Review_and_Meta_Analysis_/1354850

命令行下载

curl -L -o "S1_Table.doc" "https://ndownloader.figshare.com/files/1987375"
curl -L -o "S2_Table.doc" "https://ndownloader.figshare.com/files/1987376"
curl -L -o "S3_Table.doc" "https://ndownloader.figshare.com/files/1987377"
curl -L -o "S4_Table.doc" "https://ndownloader.figshare.com/files/1987378"

文件清单

• S1_Table.doc（85.50 KB）
• S2_Table.doc（75.78 KB）
• S3_Table.doc（62.98 KB）
• S4_Table.doc（97.79 KB）

文件总体积 322.05 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
Delays in tuberculosis (TB) diagnosis and treatment is a major barrier to effective management of the disease. Determining the factors associated with patient and provider delay of TB diagnosis and treatment in Asia may contribute to TB prevention and control.
Methods
We searched the PubMed, EMBASE and Web of Science for studies that assessed factors associated with delays in care-seeking, diagnosis, or at the beginning of treatment, which were published from January 1992 to September 2014. Two reviewers independently identified studies that were related to our meta-analysis and extracted data from each study. Independent variables were categorized in separate tables for patient and provider delays.
Results
Among 45 eligible studies, 40 studies assessed patient delay whereas 30 assessed provider delay. Cross-sectional surveys were used in all but two articles, which included 17 countries and regions. Socio-demographic characteristics, TB-related symptoms and medical examination, and conditions of seeking medical care in TB patients were frequently reported. Male patients and long travel time/distance to the first healthcare provider led to both shorter patient delays [odds ratio (OR) (95% confidence intervals, CI) = 0.85 (0.78, 0.92); 1.39 (1.08, 1.78)] and shorter provider delays [OR (95%CI) = 0.96 (0.93, 1.00); 1.68 (1.12, 2.51)]. Unemployment, low income, hemoptysis, and positive sputum smears were consistently associated with patient delay [ORs (95%CI) = 1.18 (1.07, 1.30), 1.23 (1.02, 1.49), 0.64 (0.40, 1.00), 1.77 (1.07, 2.94), respectively]. Additionally, consultation at a public hospital was associated with provider delay [OR (95%CI) = 0.43 (0.20, 0.91)].
Conclusions
We propose that the major opportunities to reduce delays involve enabling socio-demographic factors and medical conditions. Male, unemployed, rural residence, low income, hemoptysis, positive sputum smear, and long travel time/distance significantly correlated with patient delay. Male, long travel time/distance and consultation at a public hospital were related to provider delay.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0120088（source: https://plos.figshare.com/articles/dataset/_Factors_Associated_with_Patient_and_Provider_Delays_for_Tuberculosis_Diagnosis_and_Treatment_in_Asia_A_Systematic_Review_and_Meta_Analysis_/1354850）。