Development and evaluation of a free e-learning program on dementia risk reduction for the general public: A pre-post study.

Background: There is consistent evidence for the contribution of modifiable risk factors to dementia risk, offering opportunities for primary prevention. Yet, most individuals are unaware of these opportunities.

Objective: To investigate whether online education about dementia risk reduction may be a low-level means to increase knowledge and support self-management of modifiable dementia risk factors.

Perioperative patient safety indicators-A Delphi study.

Aim: To identify, define and achieve consensus on perioperative patient safety indicators within a Swedish context.

Design: A modified Delphi method.

Methods: A purposeful sample of 22 experts, all experienced operating room nurse specialists, was recruited for this study.

Longer work experience and age associated with safety attitudes in operating room nurses: an online cross-sectional study.

Background: Patient safety is fundamental when providing care in the operating room. Still, adverse events and errors are a challenge for patient safety worldwide. To avoid preventable patient harm, organisations need a positive safety culture, the measurable component of which is known as the safety climate.

Uncemented trabecular metal high-flex posterior-stabilized monoblock total knee arthroplasty in patients aged 60 years or younger.

Background: Uncemented trabecular metal (TM) monoblock tibial components in total knee arthroplasty (TKA) have shown excellent clinical results for up to 10 years. However, these studies were performed in highly specialized units, with few surgeons and often excluding knees with secondary osteoarthritis (OA), severe malalignments and previous surgery. The purpose of this study was to investigate implant survivorship and clinical and radiological outcome of the uncemented TM high-flex posterior stabilized (PS) monoblock tibial component in routine clinical practice.

Detection of duodenal villous atrophy on endoscopic images using a deep learning algorithm.

Background And Aims: Celiac disease with its endoscopic manifestation of villous atrophy (VA) is underdiagnosed worldwide. The application of artificial intelligence (AI) for the macroscopic detection of VA at routine EGD may improve diagnostic performance.

Methods: A dataset of 858 endoscopic images of 182 patients with VA and 846 images from 323 patients with normal duodenal mucosa was collected and used to train a ResNet18 deep learning model to detect VA.