虚弱与危重急性心肌梗死患者短期和长期死亡率关联的表1数据（来自MIMIC-IV）

数据集获取（Figshare）

• 源站标题：Table_1_Association between frailty and short- and long-term mortality in patients with critical acute myocardial infarction: Results from MIMIC-IV.DOCX
• DOI：10.3389/fcvm.2022.1056037.s001
• 发布日期：2022-12-15
• 文件数：1 个
• 文件总体积：36.87 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Table_1_Association_between_frailty_and_short-_and_long-term_mortality_in_patients_with_critical_acute_myocardial_infarction_Results_from_MIMIC-IV_DOCX/21729659

命令行下载

curl -L -o "Table_1_Association between frailty and short- and long-term mortality in patients with critical acute myocardial infarction: Results from MIMIC-IV.DOCX" "https://ndownloader.figshare.com/files/38555084"

文件清单

• Table_1_Association between frailty and short- and long-term mortality in patients with critical acute myocardial infarction: Results from MIMIC-IV.DOCX（36.87 KB）

文件总体积 36.87 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

BackgroundFrailty has been recognized as an important prognostic indicator in patients with acute myocardial infarction (AMI). However, no study has focused on critical AMI patients. We aimed to determine the impact of frailty on short- and long-term mortality risk in critical AMI patients.
MethodsData from the Medical Information Mart for Intensive Care (MIMIC)-IV database was used. Frailty was assessed using the Hospital Frailty Risk Score (HFRS). Outcomes were in-hospital mortality and 1-year mortality. Logistic regression and Cox proportional-hazards models were used to investigate the association between frailty and outcomes.
ResultsAmong 5,003 critical AMI patients, 2,176 were non-frail (43.5%), 2,355 were pre-frail (47.1%), and 472 were frail (9.4%). The in-hospital mortality rate was 13.8%, and the 1-year mortality rate was 29.5%. In our multivariable model, frailty was significantly associated with in-hospital mortality [odds ratio (OR) = 1.30, 95% confidence interval (CI): 1.20–1.41] and 1-year mortality [hazard ratio (HR) = 1.29, 95% CI: 1.24–1.35] as a continuous variable (per five-score increase). When assessed as categorical variables, pre-frailty and frailty were both associated with in-hospital mortality (OR = 2.80, 95% CI: 2.19–3.59 and OR = 2.69, 95% CI: 1.93–3.73, respectively) and 1-year mortality (HR = 2.32, 95% CI: 2.00–2.69 and HR = 2.81, 95% CI: 2.33–3.39, respectively) after adjustment for confounders. Subgroup analysis showed that frailty was only associated with in-hospital mortality in critically ill patients with non-ST-segment elevation myocardial infarction (STEMI) but not STEMI (p for interaction = 0.012). In addition, frailty was associated with 1-year mortality in both STEMI and non-STEMI patients (p for interaction = 0.447). The addition of frailty produced the incremental value over the initial model generated by baseline characteristics for both in-hospital and 1-year mortality.
ConclusionFrailty, as assessed by the HFRS, was associated with both in-hospital and 1-year mortality in critical AMI patients. Frailty improves the prediction of short- and long-term mortality in critical AMI patients and may have potential clinical

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fcvm.2022.1056037.s001（source: https://frontiersin.figshare.com/articles/dataset/Table_1_Association_between_frailty_and_short-_and_long-term_mortality_in_patients_with_critical_acute_myocardial_infarction_Results_from_MIMIC-IV_DOCX/21729659）。