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Risk factors contributing to cardiovascular diseases (CVD) can be addressed through behavior modification, including changes in diet and physical activity. In 2021, The Wellness Institute (WI), located at Seven Oaks General Hospital, created a virtual cardiometabolic risk reduction program in response to COVID-19 pandemic public health restrictions, encompassing virtual health coaching and lifestyle education. The objective was to evaluate the acceptability, adherence, efficacy and engagement of the WI online cardiometabolic and weight loss program.

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Background: Patients with end-stage kidney disease often prefer home-based dialysis due to higher self-efficacy, which relates to improved medical treatment adherence. Kidney transplantation (KT) success depends on adhering to immunosuppressive medication post-transplant.

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Long COVID and gut microbiome: insights into pathogenesis and therapeutics.

Gut Microbes

December 2025

Department of Medicine and Therapeutics, Faculty of Medicine, The Chinese University of Hong Kong, Hong Kong SAR, China.

Post-acute coronavirus disease 2019 syndrome (PACS), following severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection or coronavirus disease 2019 (COVID-19), is typically characterized by long-term debilitating symptoms affecting multiple organs and systems. Unfortunately, there is currently a lack of effective treatment strategies. Altered gut microbiome has been proposed as one of the plausible mechanisms involved in the pathogenesis of PACS; extensive studies have emerged to bridge the gap between the persistent symptoms and the dysbiosis of gut microbiome.

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Introduction And Aim: Peritonitis is a critical complication in peritoneal dialysis (PD) patients, making compliance with personal hygiene essential. This study examines the impact of the COVID-19 (Coronavirus Disease 2019) pandemic on hygiene behaviors and peritonitis incidence in PD patients.

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An important aspect of precision medicine focuses on characterizing diverse responses to treatment due to unique patient characteristics, also known as heterogeneous treatment effects (HTE) or individualized treatment effects (ITE), and identifying beneficial subgroups with enhanced treatment effects. Estimating HTE with right-censored data in observational studies remains challenging. In this paper, we propose a pseudo-ITE-based framework for analyzing HTE in survival data, which includes a group of meta-learners for estimating HTE, a variable importance metric for identifying predictive variables to HTE, and a data-adaptive procedure to select subgroups with enhanced treatment effects.

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