院前急救系统对急性心肌梗死死亡率影响评估数据集

评估巴西院前急救系统对急性心肌梗死死亡率影响的回顾性生态研究数据集,包含2008-2016年各市死亡率及住院率指标。

SciELO journalsSciELO journals
DataCite Commons
2022-09-24 更新
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表格Acute Myocardial InfarctionEmergency Medical ServicesHospital Mortality
Assessment of the Impact of the Implementation of a Pre-Hospital Ambulance System on Acute Myocardial Infarction Mortality in a Developing Country

基本信息

模态
表格
大小
0.033555811 GB
许可
CC BY 4.0
创建/更新时间
2022-09-24
版本
v1

资源简介

院前急救系统对急性心肌梗死死亡率影响评估数据集

【一句话概览】

本数据集是 figshare 公开的结构化表格数据集,收录 26 个文件、合计 33.56 MB,主题涵盖 Acute Myocardial Infarction、Emergency Medical Services、Hospital Mortality,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《Assessment of the Impact of the Implementation of a Pre-Hospital Ambulance System on Acute Myocardial Infarction Mortality in a Developing Country》。源站首次发布:2022-09-24。

【数据内容】

源站原始描述:Abstract Background The effective management of patients with acute myocardial infarction (AMI) is time-dependent. Objectives To assess the impacts of the implementation of prehospital care on admission rates and mortality associated with AMI. Methods Retrospective, ecological study, which assessed data from the Brazilian Universal Health System, from all 853 municipalities of Minas Gerais, from 2008 to 2016. Excessive skewness of general and in-hospital mortality rates was smoothed using the em…

中文译文(机器翻译,仅供快速理解,请以原文为准):摘要 背景 急性心肌梗死(AMI)患者的有效管理具有时间依赖性。 目的 评估实施院前急救对AMI相关入院率和死亡率的影响。 方法 回顾性生态学研究,评估了2008年至2016年巴西统一卫生系统中米纳斯吉拉斯州全部853个市的数据。采用经验贝叶斯方法对总体死亡率和院内死亡率的高度偏态进行了平滑处理。本研究使用泊松分层模型评估了各市移动急救服务(SAMU)与以下3项结局之间的关系:AMI死亡率、AMI院内死亡率和AMI住院率。率值按年龄结构进行了校正,并去除了季节性和时间因素的影响。采用95%置信区间。 结果 整个研究期间,AMI死亡率呈下降趋势,平均每年下降2%,并存在季节性变化。AMI院内死亡率也呈下降趋势,从2008年的13.81%降至2016年的11.43%。SAMU的实施与AMI死亡率降低相关(比值比[OR]=0.967,95%置信区间[CI]0.936至0.998),也与AMI院内死亡率降低相关(OR=0.914,95% CI 0.845至0.986),但与住院率无关(OR=1.003,95% CI 0.927至1.083)。 结论 SAMU的实施与AMI院内死亡率适度但显著的下降相关。这一发现强化了院前急救在AMI救治中的关键作用,以及在低中等收入国家增加对该服务投入以改善临床结局的必要性。

【数据结构与技术规格】

文件数 26 个,合计 33.56 MB。数据集 DOI:10.6084/m9.figshare.21201161.v1。

【主题与分类】

源站学科分类:Cardiology。主题标签:Acute Myocardial Infarction、Emergency Medical Services、Hospital Mortality。

【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/Assessment_of_the_Impact_of_the_Implementation_of_a_Pre-Hospital_Ambulance_System_on_Acute_Myocardial_Infarction_Mortality_in_a_Developing_Country/21201161

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

规范引用:Vieira, Rodrigo Costa Pereira; Marcolino, Milena Soriano; Silva, Luis Gustavo Silva e; Pereira, Daniella Nunes; Nascimento, Bruno Ramos; Jorge, Alzira de Oliveira; et al. (2022). Assessment of the Impact of the Implementation of a Pre-Hospital Ambulance System on Acute Myocardial Infarction Mortalit…

【使用注意】

· 源站最后修改于 2023-06-04,引用时请注意版本时效。

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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 "50a71309d210c27d38e9347561dc8529029ac907.tif" "https://ndownloader.figshare.com/files/37589579"
curl -L -o "cb2e2b9d3e33c8ef6fbe3e7f9293d0737af95590.png" "https://ndownloader.figshare.com/files/37589582"
curl -L -o "9900a966e7ab667a0dd9074c31573d71c50e777c.jpg" "https://ndownloader.figshare.com/files/37589585"
curl -L -o "a89e5b33b284336965d273df363b5c42518c7d1e.tif" "https://ndownloader.figshare.com/files/37589588"
curl -L -o "a4d4927c41b7ae5af5544e5198d3017a87a2c135.png" "https://ndownloader.figshare.com/files/37589591"
curl -L -o "3026641069c64f09386eb8706b71beb922c38295.jpg" "https://ndownloader.figshare.com/files/37589594"
curl -L -o "79781ebbedfaf0804b706122bba5df025faf26e5.tif" "https://ndownloader.figshare.com/files/37589597"
curl -L -o "49e42fcb61757b4d298055bedf5fba33517e2e85.png" "https://ndownloader.figshare.com/files/37589600"

文件清单

  • 50a71309d210c27d38e9347561dc8529029ac907.tif(4.26 MB)
  • cb2e2b9d3e33c8ef6fbe3e7f9293d0737af95590.png(966.38 KB)
  • 9900a966e7ab667a0dd9074c31573d71c50e777c.jpg(4.64 KB)
  • a89e5b33b284336965d273df363b5c42518c7d1e.tif(3.39 MB)
  • a4d4927c41b7ae5af5544e5198d3017a87a2c135.png(231.41 KB)
  • 3026641069c64f09386eb8706b71beb922c38295.jpg(6.17 KB)
  • 79781ebbedfaf0804b706122bba5df025faf26e5.tif(3.46 MB)
  • 49e42fcb61757b4d298055bedf5fba33517e2e85.png(401.93 KB)
  • f3f01948a506a106f65270a2666ba7dd0a1ea797.jpg(6.81 KB)
  • 442c19569b70b299f3d9918c7e9f5f6f143ad371.tif(3.93 MB)
  • c729b7959a2723ef939d5d38239abb1f981558f1.png(119.59 KB)
  • a42be77f45df55d1c47f8194cdb8a237188771c3.jpg(3.23 KB)
  • 991fdabbcae5480d41d08e9bccfb798771735e09.tif(4.26 MB)
  • cd1d6656ba3dad137fed0778b5dd95cffafccf70.png(964.50 KB)
  • c29d1f52bfd660baeae738b8898f5262e0471ec7.jpg(4.61 KB)
  • 6ceb6efb357a82c42d55654ac21d2a16dd721f7a.tif(3.39 MB)
  • 6faf68142b95cc77c7cb6ef7d6c2dda710a264f2.png(234.35 KB)
  • a2cecef73c564c31f39268658de029321517a1c1.jpg(6.24 KB)
  • 324bc875df448dd3ae0e16a8a62dce94b38fed56.tif(3.46 MB)
  • 8ce92771b30a243c1918dd1b40c8e82c611c259f.png(396.18 KB)

文件总体积 33.56 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

Abstract Background The effective management of patients with acute myocardial infarction (AMI) is time-dependent. Objectives To assess the impacts of the implementation of prehospital care on admission rates and mortality associated with AMI. Methods Retrospective, ecological study, which assessed data from the Brazilian Universal Health System, from all 853 municipalities of Minas Gerais, from 2008 to 2016. Excessive skewness of general and in-hospital mortality rates was smoothed using the empirical Bayes method. This study assessed the relationship between Mobile Emergency Care Service (SAMU) in each municipality and the following 3 outcomes: mortality rate due to AMI, AMI in-hospital mortality, and AMI hospitalization rate, using the Poisson hierarchical model. Rates were corrected by age structure and detrended by seasonality and temporal influences. A confidence interval of 95% was adopted. Results AMI mortality rates decreased throughout the study, on average 2% per year, with seasonal variation. AMI in-hospital mortality also showed a decreasing trend, from 13.81% in 2008 to 11.43% in 2016. SAMU implementation was associated with decreased AMI mortality (odds ratio [OR] = 0.967, 95% confidence interval [CI] 0.936 to 0.998) and AMI in-hospital mortality (OR = 0.914, 95% CI 0.845 to 0.986), with no relation with hospitalizations (OR = 1.003, 95% CI 0.927 to 1.083). Conclusion SAMU implementation was associated with a modest but significant decrease in AMI in-hospital mortality. This finding reinforces the key role of prehospital care in AMI care and the need for investments on this service to improve clinical outcomes in low- and middle-income countries.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.21201161.v1(source: https://scielo.figshare.com/articles/dataset/Assessment_of_the_Impact_of_the_Implementation_of_a_Pre-Hospital_Ambulance_System_on_Acute_Myocardial_Infarction_Mortality_in_a_Developing_Country/21201161)。

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