Access to mechanical thrombectomy for cerebral ischaemia: A population-based study in the North-of-France

Background and purposeHospitals admitting acute strokes should offer access to mechanical thrombectomy (MT), but local organisations are still based on facilities available before MT was proven effective. MT rates and outcomes at population levels are needed to adapt organisations. We evaluated rates of MT and outcomes in inhabitants from the North-of-France (NoF) area.MethodWe prospectively evaluated rates of MT and outcomes of patients at 3 months, good outcomes being defined as a modified Rankin scale (mRS) 0 to 2 or like the pre-stroke mRS.ResultsDuring the study period (2016–2017), 666 patients underwent MT (454, 68.1% associated with intravenous thrombolysis [IVT]). Besides, 1595 other patients received IVT alone. The rate of MT was 81 (95% confidence interval [CI] 72–90) per million inhabitants-year, ranging from 36 to 108 between districts. The rate of IVT was 249 (95% CI 234–264) per million inhabitants-year, ranging from 155 to 268. After 3 months, 279 (41.9%) patients who underwent MT had good outcomes, and 167 (25.1%) had died. Patients living outside the district of Lille where the only MT centre is, were less likely to have good outcomes at 3 months, after adjustment on age, sex, baseline severity, and delay.ConclusionThe rate of MT is one of the highest reported up to now, even in low-rate districts, but outcomes were significantly worse in patients living outside the district of Lille, and this is not only explained by the delay.     

“人工智能+X”背景下医学信息管理专业研究生培养模式

阐述当前“人工智能+X”背景下市场对医学信息管理专业人才能力的需求，分析医学信息管理专业人才培养现状，提出从重塑学科人才培养目标、优化课程内容与课程设置、建设“双师型”导师队伍、搭建多方协同共建共享在线平台及设立“政用产学研”联合培养基地等方面探索医学信息管理专业研究生培养模式，以期培养适应人工智能时代发展，具备学科优势特色的高层次、高水平、高质量的复合型、应用型、创新型人才。     

Development of a trail running injury screening instrument: A multiple methods approach

ObjectiveTo develop a trail running injury screening instrument (TRISI) for utilisation as clinical decision aid in determining if a trail runner is at an increased risk for injury.DesignMultiple methods approach.MethodsThe study utilised five phases 1) identification of injury risk factors 2) determining the relevance of each identified risk factor in a trail running context, 3) creating the content of the Likert scale points from 0 to 4, 4) rescaling the Likert scale points to determine numerical values for the content of each Likert scale point, and 5) determining a weighted score for each injury risk factor that contributes to the overall combined composite score.ResultsOf the 77 identified injury risk factors, 26 were deemed relevant in trail running. The weighted score for each injury risk factor ranged from 2.21 to 5.53 with the highest calculated score being 5.53. The final TRISI includes risk categories of training, running equipment, demographics, previous injury, behavioural, psychological, nutrition, chronic disease, physiological, and biomechanical factors.ConclusionThe developed TRISI aims to assist the clinician during pre-race injury screening or during a training season to identify meaningful areas to target in designing injury risk management strategies and/or continuous health education.