炎症性肠病患者30天内再入院相关因素数据集

数据集获取（Figshare）

• 源站标题：Factors associated with readmission to the hospital within 30 days in patients with inflammatory bowel disease
• DOI：10.1371/journal.pone.0182900
• 发布日期：2017-08-24
• 文件数：7 个
• 文件总体积：1.01 MB
• 源站页面：https://plos.figshare.com/articles/dataset/Factors_associated_with_readmission_to_the_hospital_within_30_days_in_patients_with_inflammatory_bowel_disease/5344333

命令行下载

curl -L -o "S1 Table.docx" "https://ndownloader.figshare.com/files/9189151"
curl -L -o "S2 Table.docx" "https://ndownloader.figshare.com/files/9189157"
curl -L -o "S3 Table.docx" "https://ndownloader.figshare.com/files/9189166"
curl -L -o "S4 Table.docx" "https://ndownloader.figshare.com/files/9189193"
curl -L -o "S1 Fig.jpg" "https://ndownloader.figshare.com/files/9189199"
curl -L -o "S2 Fig.jpg" "https://ndownloader.figshare.com/files/9189217"
curl -L -o "S3 Fig.jpg" "https://ndownloader.figshare.com/files/9189229"

文件清单

• S1 Table.docx（127.94 KB）
• S2 Table.docx（91.29 KB）
• S3 Table.docx（103.84 KB）
• S4 Table.docx（95.82 KB）
• S1 Fig.jpg（196.83 KB）
• S2 Fig.jpg（196.77 KB）
• S3 Fig.jpg（197.05 KB）

文件总体积 1.01 MB（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
Management of inpatients with inflammatory bowel disease (IBD) requires increasing resources. We aimed to identify factors associated with hospital readmissions among individuals with IBD.
Materials & methods
We collected data from the Healthcare Cost and Utilization Project Nationwide Readmissions Database 2013. We identified individuals with index hospitalizations for IBD. Patient-specific factors, comorbidities and hospitalization characteristics were extracted for the index hospitalization. We performed logistic regression modeling to create adjusted odds ratios (ORs) for 30-day hospital readmission. Subgroup analysis was performed based on disease type and performance of surgery.
Results
We analyzed a total of 55,942 index hospital discharges; 3037 patients (7.0%) were readmitted to the hospital within 30 days. Increasing patient age (> 65: OR: 0.45; 95% CI 0.39–0.53) was associated with a decreased risk of readmission, while a diagnosis of Crohn’s disease (OR: 1.09; 95% CI 1.00–1.18) and male sex (OR: 1.16; 95% CI 1.07–1.25) were associated with an increased risk of readmission. The comorbidities of smoking (OR: 1.09; 95% CI 1.00–1.19), anxiety (OR: 1.17; 95% CI 1.01–1.36) and opioid dependence (OR: 1.40; 95% CI 1.06–1.86) were associated with an increased risk of 30-day readmission. Individual hospitalization characteristics and disease complications were significantly associated with readmission. Performance of a surgery during the index admission was associated with a decreased risk of readmission (OR: 0.57; 95% CI 0.33–0.96).
Conclusion
Analyzing data from a US publicly available all-payer inpatient healthcare database, we identified patient and hospitalization risk factors associated with 30-day readmission. Identifying patients at high risk for readmission may allow for interventions during or after the index hospitalization to decrease this risk.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0182900（source: https://plos.figshare.com/articles/dataset/Factors_associated_with_readmission_to_the_hospital_within_30_days_in_patients_with_inflammatory_bowel_disease/5344333）。