20 research outputs found
Predicting general criminal recidivism in mentally disordered offenders using a random forest approach
Hippocampus abnormalities in at risk mental states for psychosis? A cross-sectional high resolution region of interest magnetic resonance imaging study
Background: Hippocampal volume (HV) reduction is well documented in schizophrenia. However, it is still unclear whether this change is a pre-existing vulnerability factor, a sign of disease progression, a consequence of environmental factors, such as drug use, antipsychotic medication, or malnutrition. The timing of HV changes is not well established, but a lack of macrostructural hippocampal brain abnormalities before disease onset would rather support a neuroprogressive illness model.
Aim: To investigate the timing of HV changes in emerging psychosis.
Methods: A cross-sectional MRI study of manually traced HVs in 37 individuals with an At Risk Mental State (ARMS) for psychosis, 23 individuals with First-Episode Psychosis (FEP), and 22 Healthy Controls (HC) was performed. We compared left and right HVs corrected for whole brain volume across groups using analysis of covariance (ANCOVA) with gender as a covariate. Sixteen of 37 ARMS individuals developed a psychotic disorder during follow up (ARMS-T). The mean duration of follow up in ARMS was 25.1 months.
Results: The overall ANCOVA model comparing left HVs across FEP, ARMS and HC indicated a significant general group effect (p < .05) with largest volumes in ARMS and smallest in FEP. ARMS-T subjects had significantly larger left HVs compared to FE but no HV differences compared to HC (p < 0.05). Over all groups, we found an asymmetry between the left and right mean HVs and a strong effect of sex.
Discussion: The present study suggests that macrostructural hippocampal abnormalities probably occur in the context of the first psychotic breakdown
Sleep Disruption and Daytime Sleepiness Correlating with Disease Severity and Insulin Resistance in Non-Alcoholic Fatty Liver Disease: A Comparison with Healthy Controls
BACKGROUND & AIMS: Sleep disturbance is associated with the development of obesity, diabetes and hepatic steatosis in murine models. Hepatic triglyceride accumulation oscillates in a circadian rhythm regulated by clock genes, light-dark cycle and feeding time in mice. The role of the sleep-wake cycle in the pathogenesis of human non-alcoholic fatty liver disease (NAFLD) is indeterminate. We sought to detail sleep characteristics, daytime sleepiness and meal times in relation to disease severity in patients with NAFLD. METHODS: Basic Sleep duration and latency, daytime sleepiness (Epworth sleepiness scale), Pittsburgh sleep quality index, positive and negative affect scale, Munich Chronotype Questionnaire and an eating habit questionnaire were assessed in 46 patients with biopsy-proven NAFLD and 22 healthy controls, and correlated with biochemical and histological parameters. RESULTS: In NAFLD compared to healthy controls, time to fall asleep was vastly prolonged (26.9 vs. 9.8 min., p = 0.0176) and sleep duration was shortened (6.3 vs. 7.2 hours, p = 0.0149). Sleep quality was poor (Pittsburgh sleep quality index 8.2 vs. 4.7, p = 0.0074) and correlated with changes in affect. Meal frequency was shifted towards night-times (p = 0.001). In NAFLD but not controls, daytime sleepiness significantly correlated with liver enzymes (ALAT [r = 0.44, p = 0.0029], ASAT [r = 0.46, p = 0.0017]) and insulin resistance (HOMA-IR [r = 0.5, p = 0.0009]) independent of cirrhosis. In patients with fibrosis, daytime sleepiness correlated with the degree of fibrosis (r = 0.364, p = 0.019). CONCLUSIONS: In NAFLD sleep duration was shortened, sleep onset was delayed and sleep quality poor. Food-intake was shifted towards the night. Daytime sleepiness was positively linked to biochemical and histologic surrogates of disease severity. The data may indicate a role for sleep-wake cycle regulation and timing of food-intake in the pathogenesis of human NAFLD as suggested from murine models
Can cognitive deficits facilitate differential diagnosis between at-risk mental state for psychosis and depressive disorders?
AIM: Many studies have provided evidence of cognitive deficits in individuals in an 'At Risk Mental State' (ARMS) for psychosis, which makes neuropsychology potentially useful in the early detection of psychosis. As depression is an important differential diagnosis in prodromal states of psychosis, the specificity of neurocognitive deficits in ARMS individuals as compared with non-psychotic depressive disorders is investigated. METHODS: Neurocognitive performance of four groups was analysed: 22 ARMS individuals with later transition to psychosis (ARMS-T), 25 ARMS individuals without later transition to psychosis (ARMS-NT), 34 controls with depressive disorders and 76 healthy controls. The subjects were assessed with a neurocognitive test battery covering the domains' intelligence, executive function and attention/ working memory. MANOVAs, ANOVAs and Tukey's tests were applied after adjustment for confounding factors. RESULTS: ARMS-T showed significant cognitive deficits in working memory and in certain executive function tasks compared with healthy controls as well as with controls with depression. Controls with depression were only impaired in time per move in the tower of Hanoi test when compared with healthy controls. CONCLUSIONS: The psychosis prodrome seems to be associated with cognitive deficits in the domains of working memory and executive function. In contrast, depressive patients showed no cognitive deficits, but slowing in one executive function task. Neurocognitive testing might therefore contribute to the differential diagnosis between prodromal psychosis and depressive disorders
Duration of untreated psychosis and cognitive functioning
BACKGROUND: Studies examining the influence of duration of untreated psychosis (DUP) or duration of untreated illness (DUI) on cognition vary with regard to results and methods. This study is the first in this field to include an at risk mental state with later transition to psychosis (ARMS-T) sample and to analyse how the DUI relates to their cognitive functioning. Because methodological operationalization of cognitive functioning in previous studies is highly heterogeneous, we aimed to compare different approaches. METHOD: 60 first episode psychosis (FEP) patients and 24 ARMS-T patients were examined. Associations between DUP, DUI and neurocognitive performance were tested by three different operationalizations of cognition: as the raw outcome measure of different neuropsychological tests, as outcome scores which were normed on a sample of 75 healthy participants, and as the deterioration index (DI). RESULTS: There were no significant correlations between DUP or DUI and outcome of neuropsychological tests in both normed and raw scores. When adjusted for covariates, DUP and DUI also did not significantly predict any cognitive performance. There was no significant relationship between DUP or DUI and the DI index. However, longer DUP and DUI were significantly associated with stronger negative symptoms. CONCLUSIONS: This study could not confirm an association between duration of untreated psychosis or duration of untreated illness and neurocognitive performance in the ARMS-T and FEP samples. This could be because schizophrenic psychoses are neurodevelopmental disorders in which most cognitive deficits exist long before the onset of psychiatric symptoms
The neuropsychology of emerging psychosis and the role of working memory in episodic memory encoding
Resting-state functional connectivity remains unaffected by preceding exposure to aversive visual stimuli
While much is known about immediate brain activity changes induced by the confrontation with emotional stimuli, the subsequent temporal unfolding of emotions has yet to be explored. To investigate whether exposure to emotionally aversive pictures affects subsequent resting-state networks differently from exposure to neutral pictures, a resting-state fMRI study implementing a two-group repeated-measures design in healthy young adults (NÂ =Â 34) was conducted. We focused on investigating (i) patterns of amygdala whole-brain and hippocampus connectivity in both a seed-to-voxel and seed-to-seed approach, (ii) whole-brain resting-state networks with an independent component analysis coupled with dual regression, and (iii) the amygdala's fractional amplitude of low frequency fluctuations, all while EEG recording potential fluctuations in vigilance. In spite of the successful emotion induction, as demonstrated by stimuli rating and a memory-facilitating effect of negative emotionality, none of the resting-state measures was differentially affected by picture valence. In conclusion, resting-state networks connectivity as well as the amygdala's low frequency oscillations appear to be unaffected by preceding exposure to widely used emotionally aversive visual stimuli in healthy young adults
Predicting general criminal recidivism in mentally disordered offenders using a random forest approach
EEG spectral power and negative symptoms in at-risk individuals predict transition to psychosis
EEG power in the delta, theta and beta1 bands has been shown to be positively correlated with negative symptoms in first episode psychotic patients. The present study investigates this correlation in an "at risk mental state for psychosis" (ARMS) with the aim to improve prediction of transition to psychosis
EEG : a helpful tool in the prediction of psychosis
OBJECTIVE: EEG investigation in patients with an at risk mental state (ARMS) for psychosis and patients with a first episode of psychosis (FE) in comparison to healthy controls (HC) in a clinical follow up study of Early Detection of Psychosis. METHOD: Seventy-three patients (42 ARMS, 31 FE) and 35 HC were investigated. ARMS patients were followed up in order to monitor transition to psychosis. Psychopathology was assessed with respect to positive and negative symptoms. At study baseline EEG was recorded using the 10/20 system. Two blinded neurologists analyzed the EEGs visually for presence of generalized or focal slowing and epileptiform discharges. EEG data were controlled for medication and substance abuse. For statistical analyses we used chi(2)-tests, logistic regression, ANOVA, and receiver operating characteristics. RESULTS: Patients showed significantly more pathological EEG abnormalities than HC (P > 0.05), located more frequently in temporal or fronto-temporal regions (P > 0.01) of the brain, with twice as many pathologies in ARMS than in FE patients. The specificity of the prediction of psychosis could be increased from 59 to 73% by considering EEG pathology in addition to psychopathology alone. In contrast, sensitivity of prediction remained unchanged. CONCLUSIONS: These results show that EEG investigation in patients at risk for psychosis can add to the identification of those patients who will not develop psychosis later on