Publications by authors named "C G Davey"
Background: Accurate electroanatomic mapping is critical for identifying scar and the long-term success of ventricular tachycardia ablation.
Objectives: This study sought to determine the accuracy of multielectrode mapping (MEM) catheters to identify scar on cardiac magnetic resonance (CMR) and histopathology.
Methods: In an ovine model of myocardial infarction, we examined the effect of electrode size, spacing, and mapping rhythm on scar identification compared to CMR and histopathology using 5 multielectrode mapping catheters.
Accurately predicting individual antidepressant treatment response could expedite the lengthy trial-and-error process of finding an effective treatment for major depressive disorder (MDD). We tested and compared machine learning-based methods that predict individual-level pharmacotherapeutic treatment response using cortical morphometry from multisite longitudinal cohorts. We conducted an international analysis of pooled data from six sites of the ENIGMA-MDD consortium (n = 262 MDD patients; age = 36.
View Article and Find Full Text PDFBackground: Youth with depression may be at a higher risk of developing bipolar disorder (BD). Self-reported, dimensional measures, like the Bipolar Spectrum Diagnostic Scale (BSDS), aim to assess for BD in these groups. We explored properties of this instrument within a cohort of depressed, help-seeking youth.
View Article and Find Full Text PDFA mindfulness-based, cognitive, social, digital relapse-prevention intervention for youth with depression in Australia: study protocol for a randomised controlled trial of Rebound.
BMJ Open
November 2024
Article Synopsis
- * A new online social therapy platform has been developed to support young people with MDD through peer networking, therapeutic content, and various human supports, aiming to prevent relapses alongside traditional treatments.
- * This study will conduct a randomised controlled trial with 255 participants aged 14-27, tracking outcomes like depressive relapse and psychological symptoms over 18 months to assess the effectiveness of the new intervention compared to enhanced usual care.
Background/objectives: Glaucoma is the leading cause of irreversible blindness, with a significant proportion of cases remaining undiagnosed globally. The interpretation of optic disc and retinal nerve fibre layer images poses challenges for optometrists and ophthalmologists, often leading to misdiagnosis. AI has the potential to improve diagnosis.
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