Publications by authors named "L Ste-Marie"

Introduction: In the COVID-19 pandemic, healthcare workers (HCWs) were at high risk of infection due to their exposure to COVID infections. HCWs were the backbone of our healthcare response to this pandemic; every HCW withdrawn or lost due to infection had a substantial impact on our capacity to deliver care. Primary prevention was a key approach to reduce infection.

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Background: Bone loss is significant after orthotopic liver transplant (OLT) and is associated with increased fracture risk and decreased quality of life. In post-transplant fracture prevention, the cornerstone of therapeutic management is bisphosphonates.

Methods: We conducted a retrospective study in a cohort of 155 OLT recipients who received a bisphosphonate prescription at hospital discharge between 2012 and 2016 to investigate post-OLT fragility fracture incidence and predictive risk factors.

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Background: The study objectives were to ascertain the efficacy of vitamin D supplementation in rapidly increasing serum vitamin D and of implementation of a hybrid (virtual and in-person) trial.

Methods: In a randomized triple-blind controlled trial, healthcare workers were allocated to receive an oral bolus of 100,000 IU with 10,000 IU/week of vitamin D or placebo. The co-primary outcomes were the change from baseline in serum 25-hydroxyvitamin D [(Δ) 25(OH)D] and proportion with vitamin D sufficiency (25(OH)D ≥ 75 nmol/L), at endpoint.

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Context: The SELECT trial led to the approval of lenvatinib for the treatment of advanced radioiodine-refractory differentiated thyroid carcinomas (DTCs) but also revealed an important adverse event (AE) profile which may limit its use in clinical practice.

Objective: We aim to describe the efficacy and toxicity profiles of lenvatinib in real life.

Methods: We included all patients who received lenvatinib for an advanced DTC at our institution, enrolling 27 patients.

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In Canada and other countries, osteoporosis is monitored as part of chronic disease population surveillance programs. Although fractures are the principal manifestation of osteoporosis, very few algorithms are available to identify individuals at high risk of osteoporotic fractures in current surveillance systems. The objective of this study was to derive and validate predictive models to accurately identify individuals at high risk of osteoporotic fracture using information available in healthcare administrative data.

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