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We aimed to investigate the learning needs of general practitioners and their preferences as regards the most appropriate teaching session for continuing medical education in wound management. A survey targeting general practitioners at the public health centres in the City of Helsinki. Twenty-seven general practitioners participated in the study. The majority (74.1%) had received education in medical school, 40.7% from wound care nurses, and 40.7% from colleagues. Participants felt the most competent in wound diagnosis (59.3%) and etiological tests (55.6%) and requested training in these topics (74.1% and 74.1%). A peer-led lecture (88.9%) was the most preferred technique, followed by lectures by wound care nurses (55.6%), an educational video (44.4%), a specialist-led lecture (37.0%), an interactive wound product session (29.6%), and digital self-study (29.6%). Wound diagnostics and etiological tests are recognised as crucial topics for continuing medical education. Peer-led lectures were preferred over other techniques; however, we observed varying preferences regarding the most optimal technique. Based on our results, we propose a half-day training including lectures, interactive and hands-on activities, and reflection, led by a peer and a wound care nurse with supporting video materials. Future studies could assess its impact on learning outcomes and wound care quality.
Endovascular aortic aneurysm repair (EVAR) requires long-term surveillance to detect and treat postoperative complications. However, prediction models to optimise follow-up strategies are still lacking. The primary objective of this study is to develop predictive models of post-operative outcomes following elective EVAR using Artificial Intelligence (AI)-driven analysis. The secondary objective is to investigate morphological aortic changes following EVAR.
This international, multicentre, observational study will retrospectively include 500 patients who underwent elective EVAR. Primary outcomes are EVAR postoperative complications including deaths, re-interventions, endoleaks, limb occlusion and stent-graft migration occurring within 1 year and at mid-term follow-up (1 to 3 years). Secondary outcomes are aortic anatomical changes. Morphological changes following EVAR will be analysed and compared based on preoperative and postoperative CT angiography (CTA) images (within 1 to 12 months, and at the last follow-up) using the AI-based software PRAEVAorta 2 (Nurea). Deep learning algorithms will be applied to stratify the risk of postoperative outcomes into low or high-risk categories. The training and testing dataset will be respectively composed of 70% and 30% of the cohort.
The study protocol is designed to ensure that the sponsor and the investigators comply with the principles of the Declaration of Helsinki and the ICH E6 good clinical practice guideline. The study has been approved by the ethics committee of the University Hospital of Patras (Patras, Greece) under the number 492/05.12.2024. The results of the study will be presented at relevant national and international conferences and submitted for publication to peer-review journals.
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