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.

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.

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.

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.

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.

To understand which anthropometric diagnostic criteria best discriminate higher from lower risk of death in children and explore programme implications.

A multiple cohort individual data meta-analysis of mortality risk (within 6 months of measurement) by anthropometric case definitions. Sensitivity, specificity, informedness and inclusivity in predicting mortality, face validity and compatibility with current standards and practice were assessed and operational consequences were modelled.

Community-based cohort studies in twelve low-income countries between 1977 and 2013 in settings where treatment of wasting was not widespread.

Children aged 6 to 59 months.

Of the twelve anthropometric case definitions examined, four (weight-for-age Z-score (WAZ) <−2), (mid-upper arm circumference (MUAC) <125 mm), (MUAC < 115 mm or WAZ < −3) and (WAZ < −3) had the highest informedness in predicting mortality. A combined case definition (MUAC < 115 mm or WAZ < −3) was better at predicting deaths associated with weight-for-height Z-score <−3 and concurrent wasting and stunting (WaSt) than the single WAZ < −3 case definition. After the assessment of all criteria, the combined case definition performed best. The simulated workload for programmes admitting based on MUAC < 115 mm or WAZ < −3, when adjusted with a proxy for required intensity and/or duration of treatment, was 1·87 times larger than programmes admitting on MUAC < 115 mm alone.

A combined case definition detects nearly all deaths associated with severe anthropometric deficits suggesting that therapeutic feeding programmes may achieve higher impact (prevent mortality and improve coverage) by using it. There remain operational questions to examine further before wide-scale adoption can be recommended.

To compare the prognostic value of mid-upper arm circumference (MUAC), weight-for-height Z-score (WHZ) and weight-for-age Z-score (WAZ) for predicting death over periods of 1, 3 and 6 months follow-up in children.

Pooled analysis of twelve prospective studies examining survival after anthropometric assessment. Sensitivity and false-positive ratios to predict death within 1, 3 and 6 months were compared for three individual anthropometric indices and their combinations.

Community-based, prospective studies from twelve countries in Africa and Asia.

Children aged 6–59 months living in the study areas.

For all anthropometric indices, the receiver operating characteristic curves were higher for shorter than for longer durations of follow-up. Sensitivity was higher for death with 1-month follow-up compared with 6 months by 49 % (95 % CI (30, 69)) for MUAC < 115 mm (P < 0·001), 48 % (95 % CI (9·4, 87)) for WHZ < -3 (P < 0·01) and 28 % (95 % CI (7·6, 42)) for WAZ < -3 (P < 0·005). This was accompanied by an increase in false positives of only 3 % or less. For all durations of follow-up, WAZ < -3 identified more children who died and were not identified by WHZ < -3 or by MUAC < 115 mm, 120 mm or 125 mm, but the use of WAZ < -3 led to an increased false-positive ratio up to 16·4 % (95 % CI (12·0, 20·9)) compared with 3·5 % (95 % CI (0·4, 6·5)) for MUAC < 115 mm alone.

Frequent anthropometric measurements significantly improve the identification of malnourished children with a high risk of death without markedly increasing false positives. Combining two indices increases sensitivity but also increases false positives among children meeting case definitions.