Schizophrenia Bulletin最新文献

Background and hypothesis: In response to Health Canada's March 2020 directive, patients on clozapine for over 12 months were allowed to extend hematological testing intervals from 4 to 8 weeks during the COVID-19 pandemic. We hypothesized that this change would not affect the timely detection of hematological abnormalities in patients with severe mental illness.

Study design: A chart review was conducted of patients at the Royal Ottawa who were prescribed clozapine from March 2019 to March 2021. We analyzed clinical and hematological data from electronic health records and Clozaril Support and Assistance Network database to compare occurrences of hematological abnormalities [leukopenia (white blood cell count <3.5 × 109/L) and agranulocytosis (absolute neutrophil count <0.5 × 109/L)] from March 17, 2020 to March 16, 2021, between standard and extended monitoring protocols using binomial logistic and zero-inflated negative binomial regressions.

Study results: Of 621 patients, 196 were on extended blood monitoring, and 425 followed standard blood monitoring. Clozapine dose did not differ between groups (standard: 370 ± 201 mg; extended: 352 ± 172 mg; P = .14, ds = 0.10). Clozapine treatment duration up to March 2021 was 12.6 ± 8.3 years, with the extended group (10 ± 7.9 years) having a significantly (P < .01, ds = 0.50) shorter duration than the standard (14 ± 8.2 years). Extended monitoring did not significantly impact likelihood of detecting hematological abnormalities (OR = 0.83, 95% CI [0.58,1.41], P = .55) after controlling for age, sex, total bloodwork, and other psychotropics associated with neutrophil counts (ie, valproate, olanzapine). No patient on the extended regimen developed agranulocytosis.

Conclusions: Reducing blood monitoring frequency in patients on clozapine for more than 12 months did not compromise detection of hematological abnormalities.

Background and hypothesis: Schizophrenia (SZ) is characterized by significant cognitive and behavioral disruptions. Neuroimaging techniques, particularly magnetic resonance imaging (MRI), have been widely utilized to investigate biomarkers of SZ, distinguish SZ from healthy conditions or other mental disorders, and explore biotypes within SZ or across SZ and other mental disorders, which aim to promote the accurate diagnosis of SZ. In China, research on SZ using MRI has grown considerably in recent years.

Study design: The article reviews advanced neuroimaging and artificial intelligence (AI) methods using single-modal or multimodal MRI to reveal the mechanism of SZ and promote accurate diagnosis of SZ, with a particular emphasis on the achievements made by Chinese scholars around the past decade.

Study results: Our article focuses on the methods for capturing subtle brain functional and structural properties from the high-dimensional MRI data, the multimodal fusion and feature selection methods for obtaining important and sparse neuroimaging features, the supervised statistical analysis and classification for distinguishing disorders, and the unsupervised clustering and semi-supervised learning methods for identifying neuroimage-based biotypes. Crucially, our article highlights the characteristics of each method and underscores the interconnections among various approaches regarding biomarker extraction and neuroimage-based diagnosis, which is beneficial not only for comprehending SZ but also for exploring other mental disorders.

Conclusions: We offer a valuable review of advanced neuroimage analysis and AI methods primarily focused on SZ research by Chinese scholars, aiming to promote the diagnosis, treatment, and prevention of SZ, as well as other mental disorders, both within China and internationally.

Background and hypothesis: Identifying biomarkers that predict treatment response in early psychosis (EP) is a priority for psychiatry research. Previous work suggests that resting-state connectivity biomarkers may have promise as predictive measures, although prior results vary considerably in direction and magnitude. Here, we evaluated the relationship between intrinsic functional connectivity of the attention, default mode, and salience resting-state networks and 12-month clinical improvement in EP.

Study design: Fifty-eight individuals with EP (less than 2 years from illness onset, 35 males, average age 20 years) had baseline and follow-up clinical data and were included in the final sample. Of these, 30 EPs showed greater than 20% improvement in Brief Psychiatric Rating Scale (BPRS) total score at follow-up and were classified as "Improvers."

Study results: The overall logistic regression predicting Improver status was significant (χ2 = 23.66, Nagelkerke's R2 = 0.45, P < .001, with 85% concordance). Significant individual predictors of Improver status included higher default mode within-network connectivity, higher attention-default mode between-network connectivity, and higher attention-salience between-network connectivity. Including baseline BPRS as a predictor increased model significance and concordance to 92%, and the model was not significantly influenced by the dose of antipsychotic medication (chlorpromazine equivalents). Linear regression models predicting percent change in BPRS were also significant.

Conclusions: Overall, these results suggest that resting-state functional magnetic resonance imaging connectivity may serve as a useful biomarker of clinical outcomes in recent-onset psychosis.

Background: Various neurocognitive models explore perceptual distortions and hallucinations in schizophrenia and the general population. A variant of predictive coding account suggests that strong priors, like cognitive expectancy, may influence perception. This study examines if stronger cognitive expectancies result in more auditory false percepts in clinical and healthy control groups, investigates group differences, and explores the association between false percepts and hallucinations.

Study design: Patients diagnosed with schizophrenia with current auditory hallucinations (n = 51) and without hallucinations (n = 66) and healthy controls (n = 51) underwent the False Perception Task under various expectancy conditions. All groups were examined for the presence and severity of hallucinations or hallucinatory-like experiences.

Study results: We observed a main effect of condition across all groups, ie, the stronger the cognitive expectancy, the greater the ratio of auditory false percepts. However, there was no group effect for the ratio of auditory false percepts. Despite modest pairwise correlations in the hallucinating group, the ratio of auditory false percepts was not predicted by levels of hallucinations and hallucinatory-like experiences in a linear mixed model.

Conclusions: The current study demonstrates that strong priors in the form of cognitive expectancies affect perception and play a role in perceptual disturbances. There is also a tentative possibility that overreliance on strong priors may be associated with hallucinations in currently hallucinating subjects. Possible, avoidable confounding factors are discussed in detail.

Background: Clinical forecasting models have potential to optimize treatment and improve outcomes in psychosis, but predicting long-term outcomes is challenging and long-term follow-up data are scarce. In this 10-year longitudinal study, we aimed to characterize the temporal evolution of cortical correlates of psychosis and their associations with symptoms.

Design: Structural magnetic resonance imaging (MRI) from people with first-episode psychosis and controls (n = 79 and 218) were obtained at enrollment, after 12 months (n = 67 and 197), and 10 years (n = 23 and 77), within the Thematically Organized Psychosis (TOP) study. Normative models for cortical thickness estimated on public MRI datasets (n = 42 983) were applied to TOP data to obtain deviation scores for each region and timepoint. Positive and Negative Syndrome Scale (PANSS) scores were acquired at each timepoint along with registry data. Linear mixed effects models assessed effects of diagnosis, time, and their interactions on cortical deviations plus associations with symptoms.

Results: LMEs revealed conditional main effects of diagnosis and time × diagnosis interactions in a distributed cortical network, where negative deviations in patients attenuate over time. In patients, symptoms also attenuate over time. LMEs revealed effects of anterior cingulate on PANSS total, and insular and orbitofrontal regions on PANSS negative scores.

Conclusions: This long-term longitudinal study revealed a distributed pattern of cortical differences which attenuated over time together with a reduction in symptoms. These findings are not in line with a simple neurodegenerative account of schizophrenia, and deviations from normative models offer a promising avenue to develop biomarkers to track clinical trajectories over time.

Background and hypothesis: Schizotypy is a useful and unifying construct for examining the etiology, development, and expression of schizophrenia-spectrum psychopathology. The positive, negative, and disorganized schizotypy dimensions are associated with distinct patterns of schizophrenia-spectrum symptoms and impairment. Furthermore, they are differentiated by mean levels of psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, and by temporal dynamics of affect. The schizotypy dimensions were thus hypothesized to be differentiated by the temporal dynamics of schizotypic experiences in daily life.

Study design: The present study employed experience sampling methodology in a large nonclinically ascertained sample (n = 693) to examine the associations of multidimensional schizotypy with psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, as well as with their temporal dynamics (variability, reactivity, inertia, and instability).

Study results: We replicated the mean-level associations between multidimensional schizotypy and schizotypic experiences in daily life. Furthermore, positive, negative, and disorganized schizotypy demonstrated hypothesized, differential patterns of temporal dynamics of schizotypic experiences. Disorganized schizotypy demonstrated the most robust associations, including intensity, variability, and inertia of disorganized schizotypic experiences. Disorganized schizotypy also moderated reactivity of psychotic-like and disorganized schizotypic experiences following previously reported stress. Positive schizotypy was associated with intensity and variability of psychotic-like experiences. Negative schizotypy was associated with intensity and variability of negative schizotypic experiences.

Conclusions: The findings indicate that schizotypy dimensions can be differentiated by both mean levels and temporal patterns of psychotic-like, suspicious, negative, and disorganized schizotypic experiences in daily life, with disorganized schizotypy uniquely characterized by stress reactivity.