Women sport injuries: a retrospective study of elite windsurfers

This study was designed to identify the injuries of professional women windsurfers, from their anatomical location, type of sport, context when they occurred, type of injury, the time of inactivity as a result of the same, the type of health care received and the relationship between the number of injuries and the position in the final classification of professional windsurfing competitions. We gave a retrospective questionnaire to 18 women elite windsurfers, who took part in the World Cup competition held in Fuerteventura (2008). Women are injured more frequently during training than competition (77.8%; p<0.05 vs. 20.5%). Women suffer leg injuries more than men (83.3%; p<0.05 vs. 14.3%) in freestyle. Serious injuries were more frequent for women (66.7%; p<0.05 vs. 28.2%) and the time of inactivity due to the injury was shorter for women (50%; p<0.05 vs. 20.5%). These results indicate that female windsurfers are more liable to suffer injuries, generally serious, during training sessions. Freestyle involves a greater risk of leg injuries for women. The knee is the area where most injuries occur, both for men and women, followed by the legs.

Participation and performance trends in 6-hour ultra-marathoners – a retrospective data analysis of worldwide participation from 1991-2010

Participation trends in 6-hour ultra-marathons held word-wide were investigated to gain basic demographic data on 6-hour ultra-marathoners and where these races took place. Participation trends and the association between nationality and race performance were investigated in all 6-hour races held worldwide between 1991 and 2010. Participation increased linearly in both women and men across years. The annual number of finishes was significantly higher in men than in women (P=0.013). The male-to-female ratio remained stable at ~4 since 1991. Runners in age group 45-49 years showed the largest increase in participation for both men (800 participants in 18 years) and women (208 participants in 16 years). Europe attracted most of the runners from other continents (166 runners), more than all other continents combined (55 runners). European runners also showed the best top ten performances (73±3 km for women and 77±11 km for men), while African (with 65±9 km for men) and South American (54±4 km for women and 65±2 km for men) runners showed the weakest. To summarize, participation in 6-hour ultra-marathons increased across years. Most of the development took place in Europe and in athletes in the age group 45-49 years. Europe also attracted the most diverse field of athletes with runners from all other continents. European runners accounted for the most runners and achieved the best top ten performances.

The aid of machine learning to overcome the classification of real health discharge reports written in Spanish

Hospitals attached to the Spanish Ministry of Health are currently using the International Classification of Diseases 9 Clinical Modification (ICD9-CM) to classify health discharge records. Nowadays, this work is manually done by experts. This paper tackles the automatic classification of real Discharge Records in Spanish following the ICD9-CM standard. The challenge is that the Discharge Records are written in spontaneous language. We explore several machine learning techniques to deal with the classification problem. Random Forest resulted in the most competitive one, achieving an F-measure of 0.876.