大流行相关医疗中断对糖尿病患者的差异影响:德克萨斯州证据(数据表1)

基于德州超800万住院记录,分析COVID-19大流行及医疗中断对糖尿病酮症酸中毒患者住院频率和死亡率的影响。

NIAID Data Ecosystem
浏览 11
表格COVID-19 pandemicSARS-CoV-2 virushealthcare disruptionsin-hospital mortalitylength of staydiabetic ketoacidosisdiabetesCOVID-19
Pandemic-driven healthcare disruptions and their disproportionate impact on patients with diabetes: evidence from Texas

基本信息

模态
表格
大小
0.000717942 GB
许可
CC BY 4.0
创建/更新时间
2026-10-09
版本
v1

资源简介

大流行相关医疗中断对糖尿病患者的差异影响:德克萨斯州证据(数据表1)

【一句话概览】

本数据集是 figshare 公开的结构化表格数据集,收录 1 个文件、合计 717.94 KB,主题涵盖 COVID-19 pandemic、SARS-CoV-2 virus、healthcare disruptions、in-hospital mortality、length of stay,可用于统计建模、特征工程与队列分析,CC BY 4.0 许可开放获取。

【数据集背景】

本数据集源站标题为《Data Sheet 1_Pandemic-driven healthcare disruptions and their disproportionate impact on patients with diabetes: evidence from Texas.pdf》。配套论文《The impact of COVID-19 on Diabetic Ketoacidosis patients》发表于 Diabetes & Metabolic Syndrome: Clinical Research & Reviews(2022),DOI:10.1016/j.dsx.2022.102389。源站首次发布:2025-10-03。

【数据内容】

源站原始描述:BackgroundDiabetic Ketoacidosis (DKA) is a life-threatening complication of uncontrolled diabetes. The COVID-19 pandemic may have increased DKA incidences and worsened outcomes both through the potential diabetogenic effects of SARS-CoV-2 infection (direct effect) and through pandemic-related disruptions in healthcare (indirect effects,) including delays in seeking or receiving care, reduced access to routine outpatient services, and strains on hospital capacity. The objective of this study is t…

【数据结构与技术规格】

文件数 1 个,合计 717.94 KB。Data Sheet 1_Pandemic-driven healthcare disruptions and their disproportionate impact on patients with diabetes: evidence from Texas.pdf:application/pdf,717.94 KB。数据集 DOI:10.3389/fpubh.2025.1597297.s001。

【主题与分类】

源站学科分类:Public Health and Health Services not elsewhere classified。主题标签:COVID-19 pandemic、SARS-CoV-2 virus、healthcare disruptions、in-hospital mortality、length of stay、diabetic ketoacidosis、diabetes。

【适用方向】

结构化表格数据可直接用于统计建模、特征工程与队列分析。

【获取与许可】

源站页面:https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Pandemic-driven_healthcare_disruptions_and_their_disproportionate_impact_on_patients_with_diabetes_evidence_from_Texas_pdf/30269863

使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。

规范引用:Saygili, Meryem; Gollu, Gultekin; Tekin, Zehra (2025). Data Sheet 1_Pandemic-driven healthcare disruptions and their disproportionate impact on patients with diabetes: evidence from Texas.pdf. Frontiers. Dataset

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陕川双基地 × 超十家三甲医院直连

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⚡️ 需要原始数据或标注支持?联系我们获取定制方案。

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下载信息

注册下载

需要注册 Kaggle 账号并登录后下载,适合需要跟踪下载记录和使用 API 的用户。

暂未开放

公开下载

无需注册即可直接获取公开样本或文档,适合快速预览和评估数据集质量。

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公开数据集受托下载与技术交付服务。

提供高速下载与技术交付服务(收技术服务费,非数据销售)

暂未开放

当前数据集主要来源为 Kaggle 公开托管,完整影像包建议通过原始链接或 Kaggle API 获取。

使用方式

数据集获取(Figshare)

命令行下载

curl -L -o "Data Sheet 1_Pandemic-driven healthcare disruptions and their disproportionate impact on patients with diabetes: evidence from Texas.pdf" "https://ndownloader.figshare.com/files/58468987"

文件清单

  • Data Sheet 1_Pandemic-driven healthcare disruptions and their disproportionate impact on patients with diabetes: evidence from Texas.pdf(717.94 KB)

文件总体积 717.94 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

BackgroundDiabetic Ketoacidosis (DKA) is a life-threatening complication of uncontrolled diabetes. The COVID-19 pandemic may have increased DKA incidences and worsened outcomes both through the potential diabetogenic effects of SARS-CoV-2 infection (direct effect) and through pandemic-related disruptions in healthcare (indirect effects,) including delays in seeking or receiving care, reduced access to routine outpatient services, and strains on hospital capacity. The objective of this study is to examine changes in the frequency and outcomes of hospitalizations with DKA in Texas hospitals following the COVID-19 pandemic and to quantify the contributions of pandemic-related healthcare disruptions and SARS-CoV-2 infection. Comparisons to patients with Acute Myocardial Infarction (AMI) and Acute Kidney Injury (AKI) were made to assess the disproportionate impacts of healthcare system disruptions on DKA patients.
MethodsThis retrospective observational study uses regression analyses to evaluate the relative contributions of healthcare disruptions and viral infection on DKA frequency, in-hospital mortality, and length of stay. Event study and difference-in-differences models are employed to analyze whether DKA cases were disproportionately affected compared to patients with AMI or AKI. Quarterly inpatient discharge records from 2018 to 2021 are obtained from the Texas Department of State Health Services. Over 8 million discharge records are examined.
ResultsDKA hospitalizations increased by 8% post-pandemic, with half of the increase attributable to pandemic-induced healthcare disruptions (indirect effects.) The average mortality of patients with DKA increased by 44% compared to the pre-pandemic average. Non-COVID channels contributed to a 30% increase in mortality. Compared to AMI and AKI patients, DKA patients were disproportionately affected by pandemic-induced disruptions.
DiscussionThe COVID-19 pandemic significantly impacted DKA outcomes through the direct effects of SARS-CoV-2 infection and through various healthcare system disruptions—such as reduced access to routine diabetes care, delays in seeking treatment, and hospital resource constraints. Policies supp

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fpubh.2025.1597297.s001(source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Pandemic-driven_healthcare_disruptions_and_their_disproportionate_impact_on_patients_with_diabetes_evidence_from_Texas_pdf/30269863)。

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