COVID-19对先天性代谢错误诊断的影响:巴西一家参考中心的数据

COVID-19大流行导致巴西一家参考中心先天性代谢错误(IEM)的检测和诊断数量大幅下降,该数据集包含两个时间段的对比数据。

Figshare
2022-06-01 更新
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表格COVID-19Inborn Errors of Metabolismlysosomal disordersreference centerBrazil
COVID-19 impact on the diagnosis of Inborn Errors of Metabolism: Data from a reference center in Brazil

基本信息

模态
表格
大小
0.00031458 GB
许可
CC BY 4.0
创建/更新时间
2022-06-01
版本
v1

资源简介

COVID-19对先天性代谢错误诊断的影响:巴西一家参考中心的数据

【数据集背景】

本数据集源站标题为《COVID-19 impact on the diagnosis of Inborn Errors of Metabolism: Data from a reference center in Brazil》。配套论文《COVID-19 impact on the diagnosis of Inborn Errors of Metabolism: Data from a reference center in Brazil》发表于 Genetics and Molecular Biology(2022),DOI:10.1590/1678-4685-gmb-2021-0253。源站首次发布:2022-06-07。

【数据内容】

源站原始描述:Abstract The COVID-19 pandemic led to the reorganization of health care in several countries, including Brazil. Inborn Errors of Metabolism (IEM) are a group of rare and difficult to diagnose genetic diseases caused by pathogenic variants in genes that code for enzymes, cofactors, or structural proteins affecting different metabolic pathways. The aim of this study was to evaluate how COVID-19 affected the diagnosis of patients with IEM during the first year of the pandemic in Brazil comparing tw…

【数据结构与技术规格】

文件数 6 个,合计 314.58 KB。数据集 DOI:10.6084/m9.figshare.20018132.v1。

【主题与分类】

源站学科分类:Biochemistry and Cell Biology not elsewhere classified、Genetics not elsewhere classified。主题标签:COVID-19、Inborn Errors of Metabolism、lysosomal disorders、reference center、Brazil。

【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/COVID-19_impact_on_the_diagnosis_of_Inborn_Errors_of_Metabolism_Data_from_a_reference_center_in_Brazil/20018132

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

规范引用:Sebastião, Fernanda Medeiros; Michelin-Tirelli, Kristiane; Bender, Fernanda; Lopes, Franciele Fátima; Moraes, Inamara; Kubaski, Francyne; et al. (2022). COVID-19 impact on the diagnosis of Inborn Errors of Metabolism: Data from a reference center in Brazil. SciELO journals. Dataset

【使用注意】

· 源站最后修改于 2023-06-01,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。

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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。

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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 "5cfe29846940eb42acbebfcc84e26db30b308294.jpg" "https://ndownloader.figshare.com/files/35699249"
curl -L -o "a8d5b8a48309926f8e27cc269f4cc2e0e90e20bb.jpg" "https://ndownloader.figshare.com/files/35699252"
curl -L -o "72f17a47094632d119aad235547dbbee6d169500.jpg" "https://ndownloader.figshare.com/files/35699255"
curl -L -o "5b790c84e4c588dea941ddbdc6297de2d5640eff.jpg" "https://ndownloader.figshare.com/files/35699258"
curl -L -o "Table_1.xls" "https://ndownloader.figshare.com/files/35699261"
curl -L -o "Table_2.xls" "https://ndownloader.figshare.com/files/35699264"

文件清单

  • 5cfe29846940eb42acbebfcc84e26db30b308294.jpg(134.34 KB)
  • a8d5b8a48309926f8e27cc269f4cc2e0e90e20bb.jpg(4.73 KB)
  • 72f17a47094632d119aad235547dbbee6d169500.jpg(146.56 KB)
  • 5b790c84e4c588dea941ddbdc6297de2d5640eff.jpg(5.40 KB)
  • Table_1.xls(13.82 KB)
  • Table_2.xls(9.73 KB)

文件总体积 314.58 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

Abstract The COVID-19 pandemic led to the reorganization of health care in several countries, including Brazil. Inborn Errors of Metabolism (IEM) are a group of rare and difficult to diagnose genetic diseases caused by pathogenic variants in genes that code for enzymes, cofactors, or structural proteins affecting different metabolic pathways. The aim of this study was to evaluate how COVID-19 affected the diagnosis of patients with IEM during the first year of the pandemic in Brazil comparing two distinct periods: from March 1st, 2019 to February 29th, 2020 (TIME A) and from March 1st, 2020 to February 28th, 2021 (TIME B), by the analysis of the number of tests and diagnoses performed in a Reference Center in South of Brazil. In the comparison TIME A with TIME B, we observe a reduction in the total number of tests performed (46%) and in the number of diagnoses (34%). In both periods analyzed, mucopolysaccharidoses (all subtypes combined) was the most frequent LD suspected and/or confirmed. Our data indicates a large reduction in the number of tests requested for the investigation of IEM and consequently a large reduction in the number of diagnoses caused by the COVID-19 pandemic leading to a significant underdiagnosis of IEM.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.6084/m9.figshare.20018132.v1(source: https://scielo.figshare.com/articles/dataset/COVID-19_impact_on_the_diagnosis_of_Inborn_Errors_of_Metabolism_Data_from_a_reference_center_in_Brazil/20018132)。

数据缺失?

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