Post-epidemic group

该数据集包含2020年1月至2024年3月急诊创伤患者的临床数据,用于比较COVID-19疫情期间和疫情后的患者特征差异。

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2024-12-18 更新
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表格retrospective comparative analysisespecially obvious effectearly december 2022using statistical methodstrauma patients admittedemergency trauma patientsaverage hospital staytrauma patientshospital stayemergency departmentaverage lengthyounger patients
Post-epidemic group

基本信息

模态
表格
大小
0.009489598 GB
许可
CC BY 4.0
创建/更新时间
2024-12-18
版本
v1

资源简介

Post-epidemic group

【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 9.49 MB,主题涵盖 retrospective comparative analysis、especially obvious effect、early december 2022、using statistical methods、trauma patients admitted,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《Post-epidemic group.》。源站首次发布:2024-12-18。

【数据内容】

源站原始描述:Background The spread of COVID-19 has a huge impact on the medical system, affecting the normal order of routine patients, especially obvious effect on the Shenzhen Third People’s Hospital as the designated hospital for COVID-19 patients. After the epidemic was loosened in early December 2022, the normal medical order gradually restored in China. How much was the impact on the admission and treatment of emergency trauma patients during and after the epidemic? This study aims to compare the diffe…

【数据结构与技术规格】

文件数 1 个,合计 9.49 MB。数据集 DOI:10.1371/journal.pone.0315416.s003。

【主题与分类】

源站学科分类:Medicine、Neuroscience、Biotechnology、Developmental Biology、Cancer、Science Policy。主题标签:retrospective comparative analysis、especially obvious effect、early december 2022、using statistical methods、trauma patients admitted、emergency trauma patients、average hospital stay、trauma patients、hospital stay、emergency department。

【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://plos.figshare.com/articles/dataset/Post-epidemic_group_/28055669

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

规范引用:Chang, Haifeng; Li, Siyuan; Ke, Xijie; Zhou, Zhenyu; Zhang, Lijun; Yang, Baisong; et al. (2024). Post-epidemic group.. PLOS ONE. Dataset

官方服务

专家保障全链路合规授权与标注交付

陕川双基地 × 超十家三甲医院直连

从合规授权、采集治理、专业标注到数据集交付,我们提供全链路闭环服务,让高质量临床数据即拿即用。

⚡️ 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。

免登录

有偿下载

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 "pone.0315416.s003.xlsx" "https://ndownloader.figshare.com/files/51280574"

文件清单

  • pone.0315416.s003.xlsx(9.49 MB)

文件总体积 9.49 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
The spread of COVID-19 has a huge impact on the medical system, affecting the normal order of routine patients, especially obvious effect on the Shenzhen Third People’s Hospital as the designated hospital for COVID-19 patients. After the epidemic was loosened in early December 2022, the normal medical order gradually restored in China. How much was the impact on the admission and treatment of emergency trauma patients during and after the epidemic? This study aims to compare the differences between trauma patients admitted to the emergency department during and after the COVID-19 pandemic.
Methods and findings
The study included all trauma patients admitted through the emergency department from January 2020 to March 2024. Clinical data were collected, and a retrospective comparative analysis was performed on the characteristics of the two groups of trauma patients during and after the pandemic, including gender, age, average length of hospital stay, proportions of admissions to various departments, proportions of severe cases, proportions of surgical patients, and mortality rates, using statistical methods for analysis.
The proportion of male patients during the pandemic (69.98%) was higher than after the pandemic (67.01%). The proportion of patients under 60 years of age during the pandemic was higher than that after the pandemic. There was no significant difference in the average hospital stay between patients during and after the pandemic (P>0.05). Comparisons between the two groups in terms of admissions to departments such as otolaryngology, hepatobiliary surgery, hepatic surgery, orthopedics, urology, neurosurgery, gastroenterology surgery, thoracic surgery, ophthalmology and intensive care unit showed no significant differences (P>0.05). The proportion of surgical patients during the pandemic (75.09%) was higher than after the pandemic (69.53%). The mortality rate during the pandemic (0.13%) was lower than after the pandemic (2.45%).
Conclusion
The COVID-19 pandemic has impacted trauma patients admitted through the emergency department, with increases in the proportion of male and younger patients, surgical cases, and a decrease in mortality ra

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.1371/journal.pone.0315416.s003(source: https://plos.figshare.com/articles/dataset/Post-epidemic_group_/28055669)。

数据缺失?

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