Vagelos College of Physicians and Surgeons, Columbia University, New York, New York.
Department of Medical Education, Icahn School of Medicine at Mount Sinai, New York, New York.
J Emerg Med. 2022 Jun;62(6):733-749. doi: 10.1016/j.jemermed.2022.01.018. Epub 2022 May 11.
Wilderness expeditions require extensive planning and the correct medical supplies to ensure clinical care is possible in the event of illness or injury. There are gaps in the literature regarding evidence-based methods for medical kit design.
This report describes a preliminary method for predicting medical events to determine medical supply requirements for a wilderness expedition. The performance of this method was evaluated using data from the 2017 Equal Playing Field (EPF) expedition to Mount Kilimanjaro.
Eight reports documenting medical events during wilderness expeditions were reviewed. Incidence data were consolidated into a new dataset, and a subset of data from adventure race expeditions (ARS) was created. The cumulative incidence of medical events was then predicted for the 9-day EPF expedition. The medical supply list was determined based on indication. The effectiveness of the full dataset and ARS to predict the cumulative incidence of medical events by category during the EPF expedition was evaluated using regression analysis.
The ARS predicted a higher incidence rate of medical events than the full dataset did but underestimated the EPF expedition incidence rate. The full dataset was a weak predictor of the cumulative incidence of medical events by category during the EPF expedition, while the ARS was a strong predictor. The finalized medical kit overestimated all nonreusable supplies.
The medical kit created using this method managed all medical events in the field. This report demonstrates the potential utility of using a tailored, evidence-based approach to design a medical kit for wilderness expeditions.
荒野探险需要进行广泛的规划并配备正确的医疗用品，以确保在发生疾病或受伤时能够进行临床治疗。目前，关于基于证据的医疗装备设计方法的文献还存在空白。
本报告介绍了一种预测医疗事件的初步方法，用于确定荒野探险所需的医疗用品。使用 2017 年赤道极限挑战赛（EPF）攀登乞力马扎罗山的数据对该方法的性能进行了评估。
回顾了 8 份记录荒野探险中医疗事件的报告。将发病率数据合并到一个新的数据集，并创建了一个冒险竞赛探险（ARS）的数据子集。然后预测了为期 9 天的 EPF 探险中医疗事件的累积发病率。根据适应症确定医疗用品清单。使用回归分析评估完整数据集和 ARS 预测 EPF 探险中各类别医疗事件累积发病率的有效性。
ARS 预测的医疗事件发生率高于完整数据集，但低估了 EPF 探险的发病率。完整数据集是 EPF 探险期间各类别医疗事件累积发病率的弱预测指标，而 ARS 则是强预测指标。最终的医疗包高估了所有不可重复使用的用品。
使用该方法创建的医疗包在野外处理了所有医疗事件。本报告证明了使用量身定制的基于证据的方法设计荒野探险医疗装备的潜在效用。
