院外心脏骤停中旁观者和第一响应者治疗时间优化

数据集获取（Figshare）

• 源站标题：Optimizing Bystander and First Responder Time to Treatment in Out-of-Hospital Cardiac Arrest.pdf
• DOI：10.25376/hra.24712629.v1
• 发布日期：2023-12-01
• 文件数：1 个
• 文件总体积：489.99 KB
• 源站页面：https://hra.figshare.com/articles/dataset/Optimizing_Bystander_and_First_Responder_Time_to_Treatment_in_Out-of-Hospital_Cardiac_Arrest_pdf/24712629

命令行下载

curl -L -o "Optimizing Bystander and First Responder Time to Treatment in Out-of-Hospital Cardiac Arrest.pdf" "https://ndownloader.figshare.com/files/43420557"

文件清单

• Optimizing Bystander and First Responder Time to Treatment in Out-of-Hospital Cardiac Arrest.pdf（489.99 KB）

文件总体积 489.99 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

Objective: Telecommunicator cardiopulmonary resuscitation (T-CPR) is a critical component of optimized out-of-hospital cardiac arrest (OHCA) care. We assessed a pilot tool to capture American Heart Association (AHA) T-CPR measures and T-CPR coaching by telecommunicators using audio review.

Methods: Using a pilot tool, we conducted a retrospective review of 911 call audio from 65 emergency medical services-treated out-of-hospital cardiac arrest (OHCA) patients. Data collection included events (e.g., OHCA recognition), time intervals, and coaching quality measures. We calculated summary statistics for all performance and quality measures.

Results: Among 65 cases, the patients’’ mean age was 64.7 years (SD: 14.6) and 17 (26.2%) were women. Telecommunicator recognition occurred in 72% of cases (47/65). Among 18 non-recognized cases, reviewers determined 12 (66%) were not recognizable based on characteristics of the call. Median time-to-recognition was 76 seconds (n = 40; IQR:39-138), while median time-to-first-instructed-compression was 198 seconds (n = 26; IQR:149-233). In 36 cases where coaching was needed, coaching on compression-depth occurred in 27 (75%); -rate in 28 (78%); and chest recoil in 10 (28%) instances. In 30 cases where repositioning was needed, instruction to position the patient’'s body flat occurred in 18 (60%) instances, on-back in 22 (73%) instances, and on-ground in 22 (73%) instances.

Conclusions: Successful collection of data to calculate AHA T-CPR measures using a pilot tool for audio review revealed performance near AHA benchmarks, although coaching instructions did not occur in many instances. Application of this standardized tool may aid in T-CPR quality review.

Keywords: 9-1-1; 911; AHA; Abstraction; American Heart Association; Audio; CPR; Cardiac Arrest; Cardiopulmonary resuscitation; Coaching; Dispatch; Dispatch-Assisted; ECC; EMS; Emergency communication center; Emergency medical services; Identifiability; Identifiable; M-RISE; MPDS; Measurement; Metrics; OHCA; Out-of-hospital; PSAP; Performance; Pre-arrival; Protocol; Public safety answering point; Quality assurance; Recognition; Recognizability; Review; SFRN; T-CPR; Telecommunicat

许可

CC BY 4.0

引用

学术使用请引用 DOI 10.25376/hra.24712629.v1（source: https://hra.figshare.com/articles/dataset/Optimizing_Bystander_and_First_Responder_Time_to_Treatment_in_Out-of-Hospital_Cardiac_Arrest_pdf/24712629）。