Publications by authors named "R Uher"
Optimizing the Prediction of Depression Remission: A Longitudinal Machine Learning Approach.
Am J Med Genet B Neuropsychiatr Genet
October 2024
Article Synopsis
- The study analyzed how often to change antidepressant treatments and aimed to improve predictions about treatment outcomes using ongoing assessments of symptom severity.
- Participants (n=714) received either escitalopram or nortriptyline for 12 weeks, and remission was defined as a Hamilton Rating Scale score of 7 or lower.
- Results showed that predictive models based on gathered data, particularly after 4 weeks, could effectively guide treatment decisions, with AUC values indicating good discrimination for the different drugs.
Article Synopsis
- Current antidepressants show limited effectiveness, prompting research to identify biological targets for new treatments and understand their mechanisms.
- The study utilized EEG data from two Canadian trials to examine how changes in brain wave patterns (neural oscillations) correlate with symptom improvement in patients undergoing pharmacological and CBT treatments.
- Findings indicate that early increases in theta waves and late changes in delta and alpha waves are linked to better treatment outcomes, with common patterns observed in both treatment methods, enhancing our understanding of how depression treatments work.
Article Synopsis
- - The study aimed to explore the genetic basis of major depressive disorder by analyzing symptoms across various clinical and community cohorts, acknowledging challenges like sample size differences and missing data patterns.
- - Researchers performed genome-wide association studies using data from both diagnosed and undiagnosed participants, fitting models to understand the relationships between different depressive symptoms.
- - Findings emphasized the relevance of symptom directionality (e.g., hypersomnia vs. insomnia) and the necessity of considering study design when analyzing genetic data related to depression.