患者特征
美国房颤患者口服抗凝药使用及特征数据集,基于医保索赔数据,涵盖种族、地理、评分等信息。

基本信息
资源简介
患者特征
【数据集背景】
本数据集源站标题为《Patient characteristics.》。源站首次发布:2024-12-12。
【数据内容】
源站原始描述:Introduction Use of oral anticoagulants (OACs) for stroke reduction in atrial fibrillation (AF) varies by race and geography within the United States. We seek to better understand the relationship between OAC underutilization, race, and US geography. Methods Patients with AF were selected from the US Centers for Medicare & Medicaid Services claims database from January 1, 2013, to December 31, 2016. The final population consisted of patients with 12 months of health plan enrollment before and af…
【数据结构与技术规格】
文件数 1 个,合计 5.63 KB。Table 1.xls:application/vnd.ms-excel,5.63 KB。数据集 DOI:10.1371/journal.pone.0314345.t001。
【主题与分类】
源站学科分类:Biotechnology、Evolutionary Biology、Ecology、Developmental Biology、Cancer、Infectious Diseases。主题标签:student &# 8217、health plan enrollment、digit zip code、study showed differences、statistically significant differences、highly variable within、final population consisted、830 final patients、us county based、index af diagnosis。
【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/Patient_characteristics_/28020103
使用许可:CC BY 4.0(https://creativecommons.org/licenses/by/4.0/)。
规范引用:Jackson, Larry R.; Kang, Amiee; Noxon, Virginia; Atreja, Nipun; Hines, Dionne M.; Hagan, Melissa; et al. (2024). Patient characteristics.. PLOS ONE. Dataset
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:Patient characteristics.
- DOI:10.1371/journal.pone.0314345.t001
- 发布日期:2024-12-12
- 文件数:1 个
- 文件总体积:5.63 KB
- 源站页面:https://plos.figshare.com/articles/dataset/Patient_characteristics_/28020103
命令行下载
curl -L -o "Table 1.xls" "https://ndownloader.figshare.com/files/51136270"
文件清单
Table 1.xls(5.63 KB)
文件总体积 5.63 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
Introduction
Use of oral anticoagulants (OACs) for stroke reduction in atrial fibrillation (AF) varies by race and geography within the United States. We seek to better understand the relationship between OAC underutilization, race, and US geography.
Methods
Patients with AF were selected from the US Centers for Medicare & Medicaid Services claims database from January 1, 2013, to December 31, 2016. The final population consisted of patients with 12 months of health plan enrollment before and after their index AF diagnosis, with a baseline CHAD2S2-VASc ≥2 and of either Black or White race (other races are underrepresented in the data). Among those with AF that met the inclusion criteria, patients who were prescribed warfarin or DOACs within 12 months after the index date were extracted. Each patient was assigned to a US county based on their 5-digit zip code and OAC use was stratified by race. Statistically significant differences were determined by student’s t-test and chi-square.
Results
Of the 2,390,830 final patients, 94.1% were White and 5.9% were Black patients. Mean (SD) age and HASBLED scores were 78 (9) and 3.9 (1.2) respectively, for Black patients and 80 (9) and 3.3 (1.2), respectively, for White patients (p2S2-VASc scores were 4.5 (1.9) for White patients, and 5.3 (1.9) for Black patients with pConclusion
Our study showed differences in the use of OACs across US counties and among various racial groups. These disparities highlighted the areas of unmet need for both Black and White patients.
许可
CC BY 4.0
引用
学术使用请引用 DOI 10.1371/journal.pone.0314345.t001(source: https://plos.figshare.com/articles/dataset/Patient_characteristics_/28020103)。
数据缺失?
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