Background. Between 2005 and 2012, annual sales of E-bikes in Switzerland increased from 1,792 to 52,941. This continuous and rapid transition from human-powered bicycles to an electric bicycle technology may indicate the increasing demand for low-cost transportation technology in combination with a healthy lifestyle. Material and Methods. In the present study, from April 2012 to September 2013, we retrospectively analysed E-bike accidents treated in the Emergency Department of our hospital by focusing on the following parameters: age, gender, time, period, and cause of the accident, as well as injury and outcome. Results. Patients were predominantly male. The mean age of injured E-cyclists was 47.5 years. The main causes of injury were self-accident. Most injuries were to the head/neck. The mean ISS was 8.48. The outcome showed that 9 patients were treated as outpatients, 9 were inpatients, and 5 patients were kept in the Intensive Care Unit (ICU). Only six patients underwent surgery (S). Discussion. This is the first attempt to evaluate E-bike injuries in Switzerland in an acute hospital setting. Since there is increasing popular preference for E-bikes as means of transportation and injuries to the head or neck are prevalent among E-cyclists, the hazard should not to be underestimated.

BackgroundIn Switzerland there are about 150,000 equestrians. Horse related injuries, including head and spinal injuries, are frequently treated at our level I trauma centre.ObjectivesTo analyse injury patterns, protective factors, and risk factors related to horse riding, and to define groups of safer riders and those at greater riskMethodsWe present a retrospective and a case-control survey at conducted a tertiary trauma centre in Bern, Switzerland.Injured equestrians from July 2000 - June 2006 were retrospectively classified by injury pattern and neurological symptoms. Injured equestrians from July-December 2008 were prospectively collected using a questionnaire with 17 variables. The same questionnaire was applied in non-injured controls. Multiple logistic regression was performed, and combined risk factors were calculated using inference trees.ResultsRetrospective surveyA total of 528 injuries occured in 365 patients. The injury pattern revealed as follows: extremities (32%: upper 17%, lower 15%), head (24%), spine (14%), thorax (9%), face (9%), pelvis (7%) and abdomen (2%). Two injuries were fatal. One case resulted in quadriplegia, one in paraplegia.Case-control survey61 patients and 102 controls (patients: 72% female, 28% male; controls: 63% female, 37% male) were included. Falls were most frequent (65%), followed by horse kicks (19%) and horse bites (2%). Variables statistically significant for the controls were: Older age (p = 0.015), male gender (p = 0.04) and holding a diploma in horse riding (p = 0.004). Inference trees revealed typical groups less and more likely to suffer injury.ConclusionsExperience with riding and having passed a diploma in horse riding seem to be protective factors. Educational levels and injury risk should be graded within an educational level-injury risk index.

Introduction: The survival of patients admitted to an emergency department is determined by the severity of acute illness and the quality of care provided. The high number and the wide spectrum of severity of illness of admitted patients make an immediate assessment of all patients unrealistic. The aim of this study is to evaluate a scoring system based on readily available physiological parameters immediately after admission to an emergency department (ED) for the purpose of identification of at-risk patients. Methods: This prospective observational cohort study includes 4,388 consecutive adult patients admitted via the ED of a 960-bed tertiary referral hospital over a period of six months. Occurrence of each of seven potential vital sign abnormalities (threat to airway, abnormal respiratory rate, oxygen saturation, systolic blood pressure, heart rate, low Glasgow Coma Scale and seizures) was collected and added up to generate the vital sign score (VSS). VSS initial was defined as the VSS in the first 15 minutes after admission, VSS max as the maximum VSS throughout the stay in ED. Occurrence of single vital sign abnormalities in the first 15 minutes and VSS initial and VSS max were evaluated as potential predictors of hospital mortality. Results: Logistic regression analysis identified all evaluated single vital sign abnormalities except seizures and abnormal respiratory rate to be independent predictors of hospital mortality. Increasing VSS initial and VSS max were significantly correlated to hospital mortality (odds ratio (OR) 2.80, 95% confidence interval (CI) 2.50 to 3.14, P < 0.0001 for VSS initial ; OR 2.36, 95% CI 2.15 to 2.60, P < 0.0001 for VSS max ). The predictive power of VSS was highest if collected in the first 15 minutes after ED admission (log rank Chi-square 468.1, P < 0.0001 for VSS initial ;,log rank Chi square 361.5, P < 0.0001 for VSS max ). Conclusions: Vital sign abnormalities and VSS collected in the first minutes after ED admission can identify patients at risk of an unfavourable outcome.