scholarly journals Prediction of transition from ultra-high risk to first-episode psychosis using a probabilistic model combining history, clinical assessment and fatty-acid biomarkers

2016 ◽  
Vol 6 (9) ◽  
pp. e897-e897 ◽  
Author(s):  
S R Clark ◽  
B T Baune ◽  
K O Schubert ◽  
S Lavoie ◽  
S Smesny ◽  
...  
2020 ◽  
Vol 46 (Supplement_1) ◽  
pp. S93-S93
Author(s):  
Irina Falkenberg ◽  
Huai-Hsuan Tseng ◽  
Gemma Modinos ◽  
Barbara Wild ◽  
Philip McGuire ◽  
...  

Abstract Background Studies indicate that people with schizophrenia and first-episode psychosis experience deficits in their ability to accurately detect and display emotions through facial expressions, and that functioning and symptoms are associated with these deficits. This study aims to examine how emotion recognition and facial emotion expression are related to functioning and symptoms in a sample of individuals at ultra-high risk, first-episode psychosis and healthy controls. Methods During fMRI, we combined the presentation of emotional faces with the instruction to react with facial movements predetermined and assigned. 18 patients with first-episode psychosis (FEP), 18 individuals at ultra high risk of psychosis (UHR) and 22 healthy controls (HCs) were examined while viewing happy, sad, or neutral faces and were instructed to simultaneously move the corners of their mouths either (a). upwards or (b). downwards, or (c). to refrain from movement. The subjects’ facial movements were recorded with an MR-compatible video camera. Results Neurofunctional and behavioral response to emotional faces were measured. Analyses have only recently commenced and are ongoing. Full results of the clinical and functional impact of behavioral and neuroimaging results will be presented at the meeting. Discussion Increased knowledge about abnormalities in emotion recognition and behaviour as well as their neural correlates and their impact on clinical measures and functional outcome can inform the development of novel treatment approaches to improve social skills early in the course of schizophrenia and psychotic disorders.


2013 ◽  
Vol 33 (1) ◽  
pp. 18-23 ◽  
Author(s):  
Chen-Chung Liu ◽  
Yi-Ling Chien ◽  
Ming H. Hsieh ◽  
Tzung-Jeng Hwang ◽  
Hai-Gwo Hwu ◽  
...  

2013 ◽  
Vol 43 (12) ◽  
pp. 2547-2562 ◽  
Author(s):  
W. Pettersson-Yeo ◽  
S. Benetti ◽  
A. F. Marquand ◽  
F. Dell‘Acqua ◽  
S. C. R. Williams ◽  
...  

BackgroundGroup-level results suggest that relative to healthy controls (HCs), ultra-high-risk (UHR) and first-episode psychosis (FEP) subjects show alterations in neuroanatomy, neurofunction and cognition that may be mediated genetically. It is unclear, however, whether these groups can be differentiated at single-subject level, for instance using the machine learning analysis support vector machine (SVM). Here, we used a multimodal approach to examine the ability of structural magnetic resonance imaging (sMRI), functional MRI (fMRI), diffusion tensor neuroimaging (DTI), genetic and cognitive data to differentiate between UHR, FEP and HC subjects at the single-subject level using SVM.MethodThree age- and gender-matched SVM paired comparison groups were created comprising 19, 19 and 15 subject pairs for FEPversusHC, UHRversusHC and FEPversusUHR, respectively. Genetic, sMRI, DTI, fMRI and cognitive data were obtained for each participant and the ability of each to discriminate subjects at the individual level in conjunction with SVM was tested.ResultsSuccessful classification accuracies (p < 0.05) comprised FEPversusHC (genotype, 67.86%; DTI, 65.79%; fMRI, 65.79% and 68.42%; cognitive data, 73.69%), UHRversusHC (sMRI, 68.42%; DTI, 65.79%), and FEPversusUHR (sMRI, 76.67%; fMRI, 73.33%; cognitive data, 66.67%).ConclusionsThe results suggest that FEP subjects are identifiable at the individual level using a range of biological and cognitive measures. Comparatively, only sMRI and DTI allowed discrimination of UHR from HC subjects. For the first time FEP and UHR subjects have been shown to be directly differentiable at the single-subject level using cognitive, sMRI and fMRI data. Preliminarily, the results support clinical development of SVM to help inform identification of FEP and UHR subjects, though future work is needed to provide enhanced levels of accuracy.


2005 ◽  
Vol 162 (1) ◽  
pp. 71-78 ◽  
Author(s):  
Warrick J. Brewer ◽  
Shona M. Francey ◽  
Stephen J. Wood ◽  
Henry J. Jackson ◽  
Christos Pantelis ◽  
...  

2021 ◽  
Vol 233 ◽  
pp. 24-30
Author(s):  
E. Burkhardt ◽  
M. Berger ◽  
R.H. Yolken ◽  
A. Lin ◽  
H.P. Yuen ◽  
...  

BJPsych Open ◽  
2017 ◽  
Vol 3 (4) ◽  
pp. 165-170 ◽  
Author(s):  
Arsime Demjaha ◽  
Sara Weinstein ◽  
Daniel Stahl ◽  
Fern Day ◽  
Lucia Valmaggia ◽  
...  

BackgroundFormal thought disorder is a cardinal feature of psychosis. However, the extent to which formal thought disorder is evident in ultra-high-risk individuals and whether it is linked to the progression to psychosis remains unclear.AimsExamine the severity of formal thought disorder in ultra-high-risk participants and its association with future psychosis.MethodThe Thought and Language Index (TLI) was used to assess 24 ultra-high-risk participants, 16 people with first-episode psychosis and 13 healthy controls. Ultra-high-risk individuals were followed up for a mean duration of 7 years (s.d.=1.5) to determine the relationship between formal thought disorder at baseline and transition to psychosis.ResultsTLI scores were significantly greater in the ultra-high-risk group compared with the healthy control group (effect size (ES)=1.2), but lower than in people with first-episode psychosis (ES=0.8). Total and negative TLI scores were higher in ultra-high-risk individuals who developed psychosis, but this was not significant. Combining negative TLI scores with attenuated psychotic symptoms and basic symptoms predicted transition to psychosis (P=0.04; ES=1.04).ConclusionsTLI is beneficial in evaluating formal thought disorder in ultra-high-risk participants, and complements existing instruments for the evaluation of psychopathology in this group.


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