数据表3：冠状动脉旁路移植术后延长机械通气风险预测模型的系统评价与Meta分析

数据集获取（Figshare）

• 源站标题：Data Sheet 3_Risk prediction models for prolonged mechanical ventilation following coronary artery bypass grafting surgery: a systematic review and meta-analysis.pdf
• DOI：10.3389/fcvm.2025.1616003.s003
• 发布日期：2025-09-12
• 文件数：1 个
• 文件总体积：130.24 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Data_Sheet_3_Risk_prediction_models_for_prolonged_mechanical_ventilation_following_coronary_artery_bypass_grafting_surgery_a_systematic_review_and_meta-analysis_pdf/30110782

命令行下载

curl -L -o "Data Sheet 3_Risk prediction models for prolonged mechanical ventilation following coronary artery bypass grafting surgery: a systematic review and me.pdf" "https://ndownloader.figshare.com/files/57894709"

文件清单

• Data Sheet 3_Risk prediction models for prolonged mechanical ventilation following coronary artery bypass grafting surgery: a systematic review and me.pdf（130.24 KB）

文件总体积 130.24 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

ObjectiveProlonged mechanical ventilation (PMV) results in significant morbidity, mortality, and associated hospital costs. Models predicting PMV following Coronary artery bypass grafting (CABG) surgery were growing. However, the reliability, validity and clinical applicability of these models remain unclear. This systematic review and meta-analysis aim to provide a comprehensive quality assessment of PMV-risk prediction models for patients after CABG.
MethodsNine relevant domestic and international databases were systematically searched from inception until November 4, 2024 using PICOTS format. The Prediction Model Risk of Bias Assessment Tool (PROBAST) checklist was employed to evaluate the risk of bias and applicability of each study. A meta-analysis of the area under the curve (AUC) values from model external validations was conducted using R software.
ResultsFifteen studies detailing 12 PMV-risk prediction models were included, with AUC values ranging from 0.561 to 0. 875. In the meta-analysis, the pooled AUC was 0.696 (95% CI: 0.553, 0.839, I-squared = 90.4%) for externally validated studies of three Society of Thoracic Surgeons (STS) models. The most frequently used predictors in the models were grouped into demographics, medical history, examination, and supportive therapy.
ConclusionsAlthough studies were judged as high overall risk of bias according to PROBAST guidelines evidence from our review indicates that risk factors of PMV in Post CABG Patients include age, BMI, history of cardiac surgery, history of cardiovascular disease, COPD, EF/LVEF, IABP, and cardiopulmonary bypass.
Systematic Review RegistrationPROSPERO CRD42024608639.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fcvm.2025.1616003.s003（source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_3_Risk_prediction_models_for_prolonged_mechanical_ventilation_following_coronary_artery_bypass_grafting_surgery_a_systematic_review_and_meta-analysis_pdf/30110782）。