Publications by authors named "W Good"

Background: Structural remodeling has been associated with increased incidence of atrial fibrillation, but how fibrotic regions allow atrial fibrillation to be sustained remains unclear.

Objective: With a novel transgenic goat model, we evaluated structural and functional differences between structurally remodeled and healthy regions of the atria.

Methods: A novel transgenic goat model with cardiac-specific overexpression of transforming growth factor β1 was used.

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Objectives: COVID-19 severity prediction scores need further validation due to evolving COVID-19 illness. We evaluated existing COVID-19 risk prediction scores in Aotearoa New Zealand, including for Māori and Pacific peoples who have been inequitably affected by COVID-19.

Methods: We conducted a multicenter retrospective cohort study in adults hospitalized with COVID-19 from January to May 2022, including all Māori and Pacific patients, and every second non-Māori, non-Pacific (NMNP) patient to achieve equal analytic power by ethnic grouping.

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This study aims to assess the sensitivity of epicardial potential-based electrocardiographic imaging (ECGI) to the removal or interpolation of bad leads.We utilized experimental data from two distinct centers. Langendorff-perfused pig (= 2) and dog (= 2) hearts were suspended in a human torso-shaped tank and paced from the ventricles.

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Objectives: This multicenter cohort study describes Aotearoa New Zealand children hospitalized during the country's first wave of sustained SARS-CoV-2 transmission, Omicron variant.

Methods: Children younger than 16 years, hospitalized for >6 hours with COVID-19 across New Zealand from January to May 2022 were included. Admissions for all Māori and Pacific and every second non-Maori non-Pacific children were selected to support equal explanatory power for ethnic grouping.

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Computational models of cardiac electrophysiology have gradually matured during the past few decades and are now being personalised to provide patient-specific therapy guidance for improving suboptimal treatment outcomes. The predictive features of these personalised electrophysiology models hold the promise of providing optimal treatment planning, which is currently limited in the clinic owing to reliance on a population-based or average patient approach. The generation of a personalised electrophysiology model entails a sequence of steps for which a range of activation mapping, calibration methods and therapy simulation pipelines have been suggested.

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