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Clinical and neurocognitive profiles of a combined clinical high risk for psychosis and clinical control sample: latent class analysis.
BJPsych Open
December 2024
University Hospital of Child and Adolescent Psychiatry and Psychotherapy Bern, University of Bern, Switzerland.
Article Synopsis
- The clinical high-risk (CHR) state for psychosis shows a lot of variability among individuals, causing challenges in treatment and research, especially since basic symptoms have often been overlooked.
- The study assessed 875 patients from early intervention centers in Germany and Switzerland, using specific diagnostic tools to categorize their symptoms and demographics.
- Results led to identifying three distinct clinical profiles: one with low symptom probability and high functioning, another with high basic and positive symptoms but low functioning, and a third mainly showing attenuated hallucinations, which can guide targeted interventions in future care.
Parsing stigma's relationship with the psychosocial functioning of youth identified as at clinical high risk for psychosis: evaluating whether symptom stigma or labelling stigma is stronger.
Br J Psychiatry
December 2024
School of Public Policy and Department of Sociology, University of California, Riverside, USA.
Article Synopsis
- The study focuses on the clinical high risk for psychosis (CHR-p) syndrome, distinguishing between two types of stigma: 'labelling-related' stigma stemming from the identification itself and 'symptom-related' stigma from experiencing mental health symptoms.
- It compares the rates and effects of these stigmas on self-esteem, social support, and quality of life in individuals identified as CHR-p.
- Results showed that symptom-related stigma was more strongly linked to negative psychosocial effects, while labelling-related stigma involved higher levels of secrecy, indicating the need for interventions that address the full stigma experience for those at risk.
In niche-based community assembly theory, it is presumed that communities in habitats with high natural disturbance regimes are less likely to be structured by competitive mechanisms. Laurentian Great Lakes (hereafter Great Lakes) coastal wetlands can experience drastic diel fluctuations in dissolved oxygen levels, severe wave action, ice scour, and near complete freezing during the winter such that conditions are inhospitable for most organisms. The high natural disturbance levels are thought to cause high interannual turnover for aquatic macroinvertebrate communities and support the hypothesis that these communities are less likely to experience less competitive interactions and negative co-occurrence structure.
View Article and Find Full Text PDFOral Microbe Community and Pyramid Scene Parsing Network-based Periodontitis Risk Prediction.
Int Dent J
November 2024
Key Laboratory of Shaanxi Province for Craniofacial Precision Medicine Research, College of Stomatology, Xi'an Jiaotong University, Xi'an, China. Electronic address:
Article Synopsis
- Periodontitis (PD) is a serious gum disease that can lead to tooth loss and other health issues, emphasizing the need for early detection.
- This study uses a deep learning model called PSPNet along with dental plaque microbial data to create a Periodontitis Risk Score (PRS), aiming to identify individuals at high risk for developing PD.
- The research found 27 key indicators for PD risk, demonstrating that the PRS can effectively differentiate between healthy individuals and PD patients with high accuracy in just 10 seconds per sample, paving the way for better early screening and preventive care.
Article Synopsis
- * Early detection of multiple KAs is important for diagnosing underlying causes and preventing related health issues, which can improve patient quality of life and provide family counseling.
- * Current research is limited and often based on small studies, so this work aims to review existing knowledge on multiple KAs, especially linked to genetic syndromes, and to propose a diagnostic algorithm for better clinical guidance.
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