Canadian Stroke Best Practice Recommendations: Vascular cognitive impairment, 7th edition practice guidelines update, 2024.

The Canadian Stroke Best Practice Recommendations (CSPR) 7th edition includes this new module on the diagnosis and management of vascular cognitive impairment (VCI) with or without neurodegenerative disease. An expert writing group and people with VCI lived experience (PWLE) reviewed current evidence. Existing recommendations were reviewed and revised, and new recommendations added.

Predictive Model for Outcomes in Inflammatory Bowel Disease Patients Receiving Maintenance Infliximab Therapy.

Background: No models predict future outcomes in inflammatory bowel disease (IBD) patients receiving maintenance infliximab therapy. We created a predictive model for unfavorable outcomes.

Methods: Adult patients with IBD receiving maintenance infliximab therapy at 2 centers with matched serum infliximab concentrations and blinded histologic scores (Robarts Histopathologic Index [RHI]) were included.

Management of monochorionic diamniotic twin gestation affected by Type-II selective fetal growth restriction: cost-effectiveness analysis.

Objective: Monochorionic twin gestations affected by Type-II selective fetal growth restriction (sFGR) are at increased risk of intrauterine fetal demise, extreme preterm birth, severe neurodevelopmental impairment (NDI) and neonatal death of one or both twins. In the absence of a consensus on the optimal management strategy, we chose to evaluate which strategy was cost-effective in the setting of Type-II sFGR.

Methods: A decision-analytic model was used to compare expectant management (EM), bipolar cord occlusion (BCO), radiofrequency ablation (RFA) and fetoscopic laser photocoagulation (FLP) for a hypothetical cohort of 10 000 people with a monochorionic diamniotic twin pregnancy affected by Type-II sFGR.

AI-based automated segmentation for ovarian/adnexal masses and their internal components on ultrasound imaging.

Purpose: Segmentation of ovarian/adnexal masses from surrounding tissue on ultrasound images is a challenging task. The separation of masses into different components may also be important for radiomic feature extraction. Our study aimed to develop an artificial intelligence-based automatic segmentation method for transvaginal ultrasound images that (1) outlines the exterior boundary of adnexal masses and (2) separates internal components.