Ankle injuries in football academies: a three-centre prospective study.

BACKGROUND: Injuries are common in youth soccer, of which ankle injuries form a significant proportion. However, there is a lack of prospective data on the epidemiology and nature of these injuries. AIM: To prospectively study the incidence of ankle injuries in three Football Association (FA) academies, with particular emphasis on severe injuries and factors associated with increased injury rate. DESIGN: Descriptive epidemiology study. METHODS: All 419 players within three FA youth academies during the 2007-2008 season were included, between under 9 and under 18 age groups. Ankle injuries causing a loss of more than 48 h training were studied, along with the setting and mechanism of injury, the diagnosis, time to rehabilitate, any investigations and surgical treatment. The incidence of injury per 1000 h exposure in match, training and in total was calculated. RESULTS: A total of 56 (incidence 14%) new ankle injuries were identified during this 1-year study period. Twenty-six (46%) of these occurred in competition, 24 (43%) were by contact, and eight (14%) had a severe injury diagnosed. The incidence was higher in the competitive setting. Ten injuries (18%) missed more than 6 weeks' training. Of these, seven were diagnosed as 'sprain' or 'strain,' of whom only three had been further investigated. There was a significant relationship between injury incidence and age group for total and match exposure, but not for training exposure. CONCLUSIONS: The incidence of ankle injury in youth soccer is higher in competition, and increases with age in competition. 17.5% of ankle injuries missed more than 6 weeks' training, but the authors found a subgroup of players with delay in returning to sport in whom there was no further investigation to establish the diagnosis. This group may harbour occult injury to the chondral surfaces, and earlier investigation could minimise secondary joint damage in this 'at risk' age group.

Regret-regression for optimal dynamic treatment regimes.

We consider optimal dynamic treatment regime determination in practice. Model building, checking, and comparison have had little or no attention so far in this literature. Motivated by an application on optimal dosage of anticoagulants, we propose a modeling and estimation strategy that incorporates the regret functions of Murphy (2003, Journal of the Royal Statistical Society, Series B 65, 331-366) into a regression model for observed responses. Estimation is quick and diagnostics are available, meaning a variety of candidate models can be compared. The method is illustrated using simulation and the anticoagulation application.