一个数据驱动的算法,以支持在道路交通碰撞后患者脱离的临床决策
Eyston Vaughan-Huxley1,2, Joanne Griggs1,3, Jasmit Mohindru4,5
1Air Ambulance Kent Surrey Sussex, Hanger 10 Redhill Aerodrome, Redhill, RH1 5YP, UK.
Scandinavian journal of trauma, resuscitation and emergency medicine
|December 4, 2023
概括
一个名为APEX的新算法帮助紧急服务部门决定如何在道路交通碰撞 (RTC) 中困住的患者获救. 这种数据驱动的工具旨在加快关键干预并改善患者的治疗结果.
科学领域:
- 紧急医疗 紧急医疗
- 创伤护理 创伤护理
- 医院前护理 医院前护理
背景情况:
- 道路交通碰撞 (RTC) 经常导致患者陷入困境,需要进行关键干预.
- 目前的解脱方法包括加速或控制的方法,需要标准化的决策.
研究的目的:
- 为紧急服务提供商开发数据驱动的算法,以确定RTC后最佳的患者脱离方法.
- 作为现场紧急人员的决策支持工具.
主要方法:
- 英国直升机紧急医疗服务 (HEMS) 参与的RTC后被困的创伤患者的回顾性观察研究 (2013年3月至2021年12月).
- 确定与需要HEMS干预措施作为加速解救的替代品相关的变量.
- 基于已识别的变量开发一个实际的解脱算法.
主要成果:
- 在12931名患者中,有920人被困. 具有AVPU"A"分数的患者很少需要HEMS (3%).
- 气道或可触摸的辐射脉冲的缺失显著预测HEMS干预需要 (OR 6.98,OR 9.99).
- 没有反应或疼痛反应的患者几乎总是需要HEMS (86-90%). 衍生出了APEX算法.
结论:
- APEX算法提供了一个简单的,数据驱动的方法来确定被困RTC患者的首选解脱.
- 它可以帮助早期识别危急患者,减少脱离时间,并可能改善患者的治疗结果.
更多相关视频
07:31Implementation of a Real-Time Psychosis Risk Detection and Alerting System Based on Electronic Health Records using CogStack
Published on: May 15, 2020
7.1K
04:09Predicting Treatment Response to Image-Guided Therapies Using Machine Learning: An Example for Trans-Arterial Treatment of Hepatocellular Carcinoma
Published on: October 10, 2018
8.3K
相关概念视频
01:30Ethical Dilemmas II
1.1K
Resolving an ethical dilemma in healthcare involves a systematic approach that considers every aspect of the issue, respecting both the patient's needs and values and the healthcare professional's ethical obligations. Here are potential steps to resolve an ethical dilemma:
1.1K
01:21Cancer Survival Analysis
356
Cancer survival analysis focuses on quantifying and interpreting the time from a key starting point, such as diagnosis or the initiation of treatment, to a specific endpoint, such as remission or death. This analysis provides critical insights into treatment effectiveness and factors that influence patient outcomes, helping to shape clinical decisions and guide prognostic evaluations. A cornerstone of oncology research, survival analysis tackles the challenges of skewed, non-normally...
356