深静脉血栓发生率与静脉血栓栓塞预防质量
评估住院血管和骨科手术患者深静脉血栓发生率及预防质量,含风险分层和指南依从性数据。

基本信息
资源简介
深静脉血栓发生率与静脉血栓栓塞预防质量
【一句话概览】
本数据集是 figshare 公开的结构化表格数据集,收录 12 个文件、合计 67.58 KB,主题涵盖 Thromboembolism、Venous thrombosis、Venous thrombosis/prevention and control、Risk factors、Incidence,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《Incidence of deep vein thrombosis and quality of venous thromboembolism prophylaxis》。配套论文《Incidence of deep vein thrombosis and quality of venous thromboembolism prophylaxis》发表于 Revista do Colégio Brasileiro de Cirurgiões(2014),DOI:10.1590/S0100-69912014000100002。源站首次发布:2022-06-02。
【数据内容】
源站原始描述:OBJECTIVE: to determine the incidence of deep vein thrombosis and prophylaxis quality in hospitalized patients undergoing vascular and orthopedic surgical procedures. METHODS: we evaluated 296 patients, whose incidence of deep venous thrombosis was studied by vascular ultrasonography. Risk factors for venous thrombosis were stratified according the Caprini model. To assess the quality of prophylaxis we compared the adopted measures with the prophylaxis guidelines of the American College of Chest…
中文译文(机器翻译,仅供快速理解,请以原文为准):目的:确定接受血管外科和骨科手术的住院患者中深静脉血栓形成的发生率及预防质量。 方法:我们评估了296例患者,通过血管超声检查研究其深静脉血栓形成发生率。根据Caprini模型对静脉血栓形成危险因素进行分层。为评估预防质量,我们将所采取的措施与美国胸科医师学会的预防指南进行比较
【数据结构与技术规格】
文件数 12 个,合计 67.58 KB。数据集 DOI:10.6084/m9.figshare.19958879.v1。
【主题与分类】
源站学科分类:Surgery。主题标签:Thromboembolism、Venous thrombosis、Venous thrombosis/prevention and control、Risk factors、Incidence。
【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://scielo.figshare.com/articles/dataset/Incidence_of_deep_vein_thrombosis_and_quality_of_venous_thromboembolism_prophylaxis/19958879
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Okuhara, Alberto; Navarro, Túlio Pinho; Procópio, Ricardo Jayme; Bernardes, Rodrigo De Castro; Oliveira, Leonardo De Campos Correa; Nishiyama, Mariana Paschoaleti (2014). Incidence of deep vein thrombosis and quality of venous thromboembolism prophylaxis. SciELO journals. Dataset
【使用注意】
· 源站最后修改于 2023-06-04,引用时请注意版本时效。
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)
- 源站标题:Incidence of deep vein thrombosis and quality of venous thromboembolism prophylaxis
- DOI:10.6084/m9.figshare.19958879.v1
- 发布日期:2022-06-02
- 文件数:12 个
- 文件总体积:67.58 KB
- 源站页面:https://scielo.figshare.com/articles/dataset/Incidence_of_deep_vein_thrombosis_and_quality_of_venous_thromboembolism_prophylaxis/19958879
命令行下载
curl -L -o "Table_1.xls" "https://ndownloader.figshare.com/files/35514134"
curl -L -o "Table_2.xls" "https://ndownloader.figshare.com/files/35514137"
curl -L -o "Table_3.xls" "https://ndownloader.figshare.com/files/35514140"
curl -L -o "Table_4.xls" "https://ndownloader.figshare.com/files/35514143"
curl -L -o "Table_5.xls" "https://ndownloader.figshare.com/files/35514146"
curl -L -o "Table_6.xls" "https://ndownloader.figshare.com/files/35514149"
curl -L -o "Table_7.xls" "https://ndownloader.figshare.com/files/35514152"
curl -L -o "Table_8.xls" "https://ndownloader.figshare.com/files/35514155"
文件清单
Table_1.xls(5.63 KB)Table_2.xls(5.63 KB)Table_3.xls(5.63 KB)Table_4.xls(5.63 KB)Table_5.xls(5.63 KB)Table_6.xls(5.63 KB)Table_7.xls(5.63 KB)Table_8.xls(5.63 KB)Table_9.xls(5.63 KB)Table_10.xls(5.63 KB)Table_11.xls(5.63 KB)Table_12.xls(5.63 KB)
文件总体积 67.58 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
OBJECTIVE: to determine the incidence of deep vein thrombosis and prophylaxis quality in hospitalized patients undergoing vascular and orthopedic surgical procedures. METHODS: we evaluated 296 patients, whose incidence of deep venous thrombosis was studied by vascular ultrasonography. Risk factors for venous thrombosis were stratified according the Caprini model. To assess the quality of prophylaxis we compared the adopted measures with the prophylaxis guidelines of the American College of Chest Physicians. RESULTS: the overall incidence of deep venous thrombosis was 7.5%. As for the risk groups, 10.8% were considered low risk, 14.9%moderate risk, 24.3% high risk and 50.5% very high risk. Prophylaxis of deep venous thrombosis was correct in 57.7%. In groups of high and very high risk, adequate prophylaxis rates were 72.2% and 71.6%, respectively. Excessive use of chemoprophylaxis was seen in 68.7% and 61.4% in the low and moderate-risk groups, respectively. CONCLUSION: although most patients are deemed to be at high and very high risk for deep vein thrombosis, deficiency in the application of prophylaxis persists in medical practice.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.6084/m9.figshare.19958879.v1(source: https://scielo.figshare.com/articles/dataset/Incidence_of_deep_vein_thrombosis_and_quality_of_venous_thromboembolism_prophylaxis/19958879)。
数据缺失?
依托陕西、四川两大基地,我们与超过十家三甲医院建立直接合作关系,覆盖合规授权、采集治理、专业标注、数据交付的全流程,为AI医疗团队提供即拿即用的高质量临床数据。
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