严重创伤患者ICU延长住院时间预测的登记数据分析

数据集获取（Figshare）

• 源站标题：Data_Sheet_1_Prediction of prolonged length of stay on the intensive care unit in severely injured patients—a registry-based multivariable analysis.PDF
• DOI：10.3389/fmed.2024.1358205.s001
• 发布日期：2024-06-05
• 文件数：1 个
• 文件总体积：104.64 KB
• 源站页面：https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Prediction_of_prolonged_length_of_stay_on_the_intensive_care_unit_in_severely_injured_patients_a_registry-based_multivariable_analysis_PDF/25971979

命令行下载

curl -L -o "Data_Sheet_1_Prediction of prolonged length of stay on the intensive care unit in severely injured patients—a registry-based multivariable analysis.PDF" "https://ndownloader.figshare.com/files/46826275"

文件清单

• Data_Sheet_1_Prediction of prolonged length of stay on the intensive care unit in severely injured patients—a registry-based multivariable analysis.PDF（104.64 KB）

文件总体积 104.64 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

PurposeMortality is the primary outcome measure in severely injured trauma victims. However, quality indicators for survivors are rare. We aimed to develop and validate an outcome measure based on length of stay on the intensive care unit (ICU).
MethodsThe TraumaRegister DGU of the German Trauma Society (DGU) was used to identify 108,178 surviving patients with serious injuries who required treatment on ICU (2014–2018). In a first step, need for prolonged ICU stay, defined as 8 or more days, was predicted. In a second step, length of stay was estimated in patients with a prolonged stay. Data from the same trauma registry (2019–2022, n = 72,062) were used to validate the models derived with logistic and linear regression analysis.
ResultsThe mean age was 50 years, 70% were males, and the average Injury Severity Score was 16.2 points. Average/median length of stay on ICU was 6.3/2 days, where 78% were discharged from ICU within the first 7 days. Prediction of need for a prolonged ICU stay revealed 15 predictors among which injury severity (worst Abbreviated Injury Scale severity level), need for intubation, and pre-trauma condition were the most important ones. The area under the receiver operating characteristic curve was 0.903 (95% confidence interval 0.900–0.905). Length of stay prediction in those with a prolonged ICU stay identified the need for ventilation and the number of injuries as the most important factors. Pearson’s correlation of observed and predicted length of stay was 0.613. Validation results were satisfactory for both estimates.
ConclusionLength of stay on ICU is a suitable outcome measure in surviving patients after severe trauma if adjusted for severity. The risk of needing prolonged ICU care could be calculated in all patients, and observed vs. predicted rates could be used in quality assessment similar to mortality prediction. Length of stay prediction in those who require a prolonged stay is feasible and allows for further benchmarking.

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.3389/fmed.2024.1358205.s001（source: https://frontiersin.figshare.com/articles/dataset/Data_Sheet_1_Prediction_of_prolonged_length_of_stay_on_the_intensive_care_unit_in_severely_injured_patients_a_registry-based_multivariable_analysis_PDF/25971979）。