A Retrospective Application of the Arbon and Hartman Models to the Union Cycliste International Mountain Bike World Cup

INTRODUCTION: Outdoor activities have accelerated in the past several years. The authors were tasked with providing medical care for the Union Cycliste International (UCI) mountain biking World Cup in Snowshoe, West Virginia (USA) in September 2021. The Hartman and Arbon models were designed to predict patient presentation and hospital transport rates as well as needed medical resources at urban mass-gathering events. However, there is a lack of standardized methods to predict injury, illness, and insult severity at rural mass gatherings. STUDY OBJECTIVE: This study aimed to determine whether the Arbon model would predict, within 10%, the number of patient presentations to be expected and to determine if the event classification provided by the Hartman model would adequately predict resources needed during the event. METHODS: Race data were collected from UCI event officials and injury data were collected from participants at time of presentation for medical care. Predicted presentation and transport rates were calculated using the Arbon model, which was then compared to the actual observed presentation rates. Furthermore, the event classification provided by the Hartman model was compared to the resources utilized during the event. RESULTS: During the event, 34 patients presented for medical care and eight patients required some level of transport to a medical facility. The Arbon predictive model for the 2021 event yielded 30.3 expected patient presentations. There were 34 total patient presentations during the 2021 race, approximately 11% more than predicted. The Hartman model yielded a score of four. Based on this score, this race would be classified as an “intermediate” event, requiring multiple Advanced Life Support (ALS) and Basic Life Support (BLS) personnel and transport units. CONCLUSION: The Arbon model provided a predicted patient presentation rate within reasonable error to allow for effective pre-event planning and resource allocation with only a four patient presentation difference from the actual data. While the Arbon model under-predicted patient presentations, the Hartman model under-estimated resources needed due to the high-risk nature of downhill cycling. The events staffed required physician skills and air medical services to safely care for patients. Further evaluation of rural events will be needed to determine if there is a generalized need for physician presence at smaller events with inherently risky activities, or if this recurring cycling event is an outlier.