多种手术后手术部位感染半自动监测筛查工具的开发与验证(Table_1)

该数据表来自成人手术后手术部位感染半自动监测筛查工具开发与验证研究,涵盖骨科、结直肠和腹部子宫切除术患者。

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表格surgical site infectionsemi-automated surveillancescreening toolvalidationmodel development
The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries

基本信息

模态
表格
大小
0.000029086 GB
许可
CC BY 4.0
创建/更新时间
2026-10-10
版本
v1

资源简介

多种手术后手术部位感染半自动监测筛查工具的开发与验证(Table_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 29.09 KB,主题涵盖 surgical site infection、semi-automated surveillance、screening tool、validation、model development,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《Table_1_The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries.docx》。配套论文《Validation of semiautomated surgical site infection surveillance using electronic screening algorithms in 38 surgery categories》发表于 Infection Control & Hospital Epidemiology(2018),DOI:10.1017/ice.2018.116。源站首次发布:2023-01-26。

【数据内容】

源站原始描述:BackgroundSurveillance of surgical site infections (SSIs) is essential for better prevention. We developed a screening method for SSIs in adults. MethodsThe training dataset included data from patients who underwent orthopedic surgeries (N = 1,090), colorectal surgeries (N = 817), and abdominal hysterectomies (N = 523) during 2015–2018. The gold standard for the validation of the screening tool was the presence of SSI as determined by a trained infection control practitioner, via manual full med…

【数据结构与技术规格】

文件数 1 个,合计 29.09 KB。Table_1_The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries.docx:application/vnd.openxmlformats-officedocument.wordprocessingml.document,29.09 KB。数据集 DOI:10.3389/fmed.2023.1023385.s001。

【主题与分类】

源站学科分类:Radiology and Organ Imaging、Foetal Development and Medicine、Obstetrics and Gynaecology、Primary Health Care、Medical and Health Sciences not elsewhere classified、Dermatology。主题标签:surgical site infection、semi-automated surveillance、screening tool、validation、model development。

【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/Table_1_The_development_and_validation_of_screening_tools_for_semi-automated_surveillance_of_surgical_site_infection_following_various_surgeries_docx/21958580

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

规范引用:Shitrit, Pnina; Chowers, Michal Y.; Muhsen, Khitam (2023). Table_1_The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries.docx. Frontiers. Dataset

【使用注意】

· 源站最后修改于 2023-06-20,引用时请注意版本时效。

官方服务

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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 "Table_1_The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries.docx" "https://ndownloader.figshare.com/files/38954285"

文件清单

  • Table_1_The development and validation of screening tools for semi-automated surveillance of surgical site infection following various surgeries.docx(29.09 KB)

文件总体积 29.09 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

BackgroundSurveillance of surgical site infections (SSIs) is essential for better prevention. We developed a screening method for SSIs in adults.
MethodsThe training dataset included data from patients who underwent orthopedic surgeries (N = 1,090), colorectal surgeries (N = 817), and abdominal hysterectomies (N = 523) during 2015–2018. The gold standard for the validation of the screening tool was the presence of SSI as determined by a trained infection control practitioner, via manual full medical record review, using the US Center for Disease Control and Prevention criteria. Using multivariable regression models, we identified the correlates of SSI. Patients who had at least one of these correlates were classified as likely to having SSI and those who did not have any of the correlates were classified as unlikely to have SSI. We calculated the sensitivity and specificity of this tool compared to the gold standard and applied the tool to a validation dataset (N = 1,310, years 2019–2020).
ResultsSSI was diagnosed by an infection control specialist in 8.2, 5.2, and 31.2% of the patients in the training dataset who underwent hysterectomies, orthopedic surgeries and colorectal surgeries, respectively, vs. 6.2, 6.6, and 25.5%, respectively, in the validation dataset. The correlates of SSI after abdominal hysterectomy were prolonged hospitalization, ordering wound or blood culture, emergency room visit and reoperation; in orthopedic surgery, emergency room visit, wound culture, reoperation, and documentation of SSI, and in colorectal surgeries prolonged hospitalization, readmission, and ordering wound or blood cultures. Area under the curve was >90%. The sensitivity and specificity (95% CI) of the screening tool were 98% (88–100) and 58% (53–62), for abdominal hysterectomy, 91% (81–96) and 82% (80–84) in orthopedic surgeries and 96% (90–98) and 62% (58–66) in colorectal surgeries. The corresponding values for the validation dataset were 89% (67–97) and 75% (69–80) in abdominal hysterectomy; 85% (72–93) and 83% (80–86) in orthopedic surgeries and 98% (93–99) and 59% (53–64) in colorectal surgeries. The number of files needed to be fully reviewed declined by 61–66.
Co

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fmed.2023.1023385.s001(source: https://frontiersin.figshare.com/articles/dataset/Table_1_The_development_and_validation_of_screening_tools_for_semi-automated_surveillance_of_surgical_site_infection_following_various_surgeries_docx/21958580)。

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