Publications by authors named "Martin Erik Nyeland"

Background: Time-restricted eating (TRE) has been suggested to be a simple, feasible, and effective dietary strategy for individuals with overweight or obesity. We aimed to investigate the effects of 3 months of 10-h per-day TRE and 3 months of follow-up on bodyweight and cardiometabolic risk factors in individuals at high risk of type 2 diabetes.

Methods: This was a single-centre, parallel, superiority, open-label randomised controlled clinical trial conducted at Steno Diabetes Center Copenhagen (Denmark).

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Objective: To identify PaCO trajectories and assess their associations with mortality in critically ill patients with coronavirus disease 2019 (COVID-19) during the first and second waves of the pandemic in Denmark.

Design: A population-based cohort study with retrospective data collection.

Patients: All COVID-19 patients were treated in eight intensive care units (ICUs) in the Capital Region of Copenhagen, Denmark, between March 1, 2020 and March 31, 2021.

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Introduction: In Denmark, physicians are legally obliged to report serious adverse drug reactions (ADRs), such as intracranial hemorrhage (ICH) following anticoagulant (AC) treatment, to the Danish Medicines Agency. We were therefore puzzled to discover a high number of reports concerning ICHs following treatment with the direct oral anticoagulants (DOACs) dabigatran, rivaroxaban, and apixaban compared with warfarin. This was surprising, as all DOACs have been found to be associated with a lower risk of ICH compared with warfarin in phase III randomized controlled trials.

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We aimed to characterize the in-hospital analgesic use among total hip or knee arthroplasty (THA or TKA) patients, and to identify possible drug-related challenges. We identified 15 263 patients operated with a THA or TKA between 1 January 2012 and 30 April 2016. The prevalence of analgesic users and patients with potential clinically relevant drug-drug interactions (DDIs), along with the prevalence of readmission among patients with vs.

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Patients with severe COVID-19 have overwhelmed healthcare systems worldwide. We hypothesized that machine learning (ML) models could be used to predict risks at different stages of management and thereby provide insights into drivers and prognostic markers of disease progression and death. From a cohort of approx.

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Aims: This retrospective, longitudinal study characterised 2430 adults (mean age 40.8±16.1years) with newly diagnosed type 1 diabetes (T1D) over the first 5years of insulin treatment.

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Purpose: For both marketing authorization holders and regulatory authorities, evaluating the effectiveness of risk minimization measures is now an integral part of pharmacovigilance in the European Union. The overall aim of activities in this area is to assess the performance of risk minimization measures implemented in order to ensure a positive benefit-risk balance in patients treated with a medicinal product.

Methods: Following a review of the relevant literature, we developed a conceptual framework consisting of four domains (data, knowledge, behaviour and outcomes) intended for the evaluation of risk minimization measures put into practice in the Danish health-care system.

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