Publications by authors named "D Kyte"

Kidney services worldwide are increasingly using digital health technologies to deliver care. This includes kidney electronic patient-reported outcome (ePRO) systems: ambulatory digital technologies that enable the capture of PRO data electronically from people with kidney disease remotely and in real time to be shared with their kidney care team. Current kidney ePRO systems commonly aim to support the monitoring and management of symptoms in patients with kidney disease.

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Introduction: Aortic stenosis (AS) is common affecting >13% of adults over the age of 75 years. In people who develop symptoms, without valve replacement, prognosis is dismal with mortality as high as 50% at 1 year. In asymptomatic patients, the timing of valve intervention is less well defined and a strategy of watchful waiting is recommended.

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Background: Electronic patient-reported outcome (ePRO) systems are increasingly used in clinical trials to provide evidence of efficacy and tolerability of treatment from the patient perspective. The aim of this study is twofold: (1) to describe how we developed an electronic platform for patients to report their symptoms, and (2) to develop and undertake usability testing of an ePRO solution for use in a study of cell therapy seeking to provide early evidence of efficacy and tolerability of treatment and test the feasibility of the system for use in later phase studies.

Methods: An ePRO system was designed to be used in a single arm, multi-centre, phase II basket trial investigating the safety and activity of the use of ORBCEL-C™ in the treatment of patients with inflammatory conditions.

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Objectives: The use of electronic patient-reported outcome (ePRO) systems to support the management of patients with chronic kidney disease is increasing. This mixed-methods study aimed to comprehensively identify existing and developing ePRO systems, used in nephrology settings globally, ascertaining key characteristics and factors for successful implementation.

Study Design: ePRO systems and developers were identified through a scoping review of the literature and contact with field experts.

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Objective: A confirmatory factor analysis (CFA) of the Adolescent Dissociative Experiences Scale (A-DES) that found a best-fitting three-factor model for a trauma-exposed sample was recently replicated; however, a post hoc bifactor CFA model fit the data better and identified a strong general factor. Only the general factor was associated with cumulative trauma exposure, but this association was small.

Method: Structural equation modeling (SEM) and regression analyses were applied to the best-fitting three-factor bifactor model of dissociation found in the same sample of 1,157 treatment-seeking adolescents, most with high levels of trauma exposure, to further elucidate dissociation's construct validity and dimensionality.

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