Longitudinal clinical and functional outcome in distinct cognitive subgroups of first-episode psychosis: a cluster analysis

Longitudinal clinical outcomes based on cognitive and hippocampal clusters of first episode psychosis

BACKGROUND

In first episode psychosis (FEP), cognitive impairments are core features contributing to clinical and functional heterogeneity. Significant impairment indicates greater clinical severity throughout the course of the illness, particularly for negative symptoms. Hippocampal volume is smaller in FEP than in healthy controls (notably subfields like Cornu Ammonis 1-3 and subiculum), and is related to cognitive impairments and negative symptoms. The aim of this study was to compare the clinical and functional trajectories of FEP subgroups as a function of cognitive performance and hippocampal volumes.

METHODS

One hundred FEP patients and sixty healthy controls initially assessed using the CogState research battery, underwent 3 T MRI to extract hippocampal subfields and adjacent structures using the MAGeT brain algorithm. Clinical assessments were carried out for negative (Motivational and Pleasure - MAP, and diminished expression - EXP) and depressive symptoms, and global functioning. Measurements were taken at 4 time points (3, 9, 15, 21 months following program entry). Based on available first timepoint standardized cognitive and hippocampal features, using healthy controls as reference, clusters were determined by a hierarchical ascending classification. Their clinical and functional longitudinal trajectories were analyzed using linear mixed-effects models.

RESULTS

Three baseline clusters were revealed: normal-range hippocampal volume with low attention, working and verbal memory (FEP 0), small hippocampus with low verbal memory and social cognition (FEP 1), and large hippocampus with low verbal memory (FEP 2). At baseline, the clusters did not differ on symptoms severity and global functioning. Longitudinally, MAP, EXP and depressive symptoms decreased over time in FEP 0. Global functioning improved in FEP 0 and FEP 1, while FEP 2 was clinically and functionally stable over time. Longitudinal inter-group comparisons did not yield any significant differences.

CONCLUSION

The clusters were dissociated between hippocampus and cognition, but their trajectories suggest the importance of hippocampal integrity in the clinical and/or functional outcome. Future studies are needed to understand intervention efficiency depending on hippocampal integrity.

Neurocognitive resilience as a predictor of psychosis onset and functional outcomes in individuals at high risk

BACKGROUND

Neurocognitive resilience (NCR) refers to the ability of individuals to maintain cognitive function despite the presence of risk factors for psychosis. Investigating NCR is important as it may help predict the onset of psychosis and functional outcomes in individuals at clinical high risk (CHR) for psychosis.

METHODS

This study employed a multi-group prospective design with a 3-year follow-up as part of the ShangHai At Risk for Psychosis-Extended project. Neurocognitive performance was assessed using the Chinese version of the Measurement and Treatment Research to Improve Cognition in Schizophrenia Consensus Cognitive Battery. The study focused on two primary outcomes: conversion/non-conversion to psychosis (CHR-C/CHR-NC) and non-remission/remission (CHR-NR/CHR-R). NCR was defined based on the adjusted cognitive variable relative to the healthy control(HC) group's mean, with three categories: NCR (NCR = 0) for scores within one standard deviation, NCR + (NCR = 1) for scores more than one standard deviation above, and NCR - (NCR = - 1) for scores more than one standard deviation below.

RESULTS

The study included 771 individuals at CHR (346 males, mean age 18.8 years) and 764 HCs (359 males, mean age 22.5 years). Among the CHR participants, 540 (70.0%) completed the 3-year follow-up, with 106 (19.6%) converting to psychosis (CHR-C) and 277 (51.3%) classified as non-remission (CHR-NR). Significant negative correlations were found between the total NCR score and various clinical symptoms. Comparing CHR-C and non-converters (CHR-NC), there were notable differences in NCR distributions across four cognitive measures, with a higher proportion of CHR-C individuals categorized as NCR - . For CHR-NR versus remission (CHR-R), CHR-NR individuals were more likely to be classified as NCR - across nearly all cognitive domains. The receiver operating characteristic (ROC) curve for predicting conversion to psychosis yielded an area under the curve (AUC) of 0.621 (95% CI (0.561-0.681), p = 0.0001), while the ROC for predicting non-remission demonstrated a higher AUC of 0.826 (95% CI (0.790-0.861), p < 0.0001).

CONCLUSIONS

NCR was associated with both conversion to psychosis and non-remission outcomes in CHR individuals, showing notable predictive accuracy, particularly for non-remission.

Neuropsychological profiles in first-episodes psychosis and their relationship with clinical, metacognition and social cognition variables

An increasing interest in the assessment of neuropsychological performance variability in people with first-episode psychosis (FEP) has emerged. However, its association with clinical and functional outcomes requires further study. Furthermore, FEP neuropsychological subgroups have not been characterized by clinical insight or metacognition and social cognition domains. The aim of this exploratory study was to identify specific groups of patients with FEP based on neuropsychological variables and to compare their sociodemographic, clinical, metacognition and social cognition profiles. A sample of 149 FEP was recruited from adult mental health services. Neuropsychological performance was assessed by a neuropsychological battery (WAIS-III; TMT; WSCT; Stroop Test; TAVEC). The assessment also included sociodemographic characteristics, clinical, functional, metacognition and social cognition variables. Two distinct neuropsychological profiles emerged: one neuropsychological impaired cluster (N = 56) and one relatively intact cluster (N = 93). Significant differences were found between both profiles in terms of sociodemographic characteristics (age and level of education) (p = 0.001), clinical symptoms (negative, positive, disorganized, excitement and anxiety) (p = 0.041-0.001), clinical insight (p = 0.038-0.017), global functioning (p = 0.014), as well as in social cognition domains (emotional processing and theory of mind) (p = 0.001; p = 0.002). No significant differences were found in metacognitive variables (cognitive insight and 'jumping to conclusions' bias). Relationship between neurocognitive impairment, social cognition and metacognition deficits are discussed. Early identifying of neuropsychological profiles in FEP, characterized by significant differences in clinical and social cognition variables, could provide insight into the prognosis and guide the implementation of tailored early-intervention.

Cognitive and clinical profiles in first-episode psychosis and their relationship with functional outcomes

BACKGROUND

While cognitive impairment is a core feature of psychosis, significant heterogeneity in cognitive and clinical outcomes is observed.

AIMS

The aim of this study was to identify cognitive and clinical subgroups in first-episode psychosis (FEP) and determine if these profiles were linked to functional outcomes over time.

METHOD

A total of 323 individuals with FEP were included. Two-step hierarchical and k-means cluster analyses were performed using baseline cognitive and clinical variables. General linear mixed models were used to investigate whether baseline cognitive and clinical clusters were associated with functioning at follow-up time points (6-9, 12 and 15 months).

RESULTS

Three distinct cognitive clusters were identified: a cognitively intact group (N = 59), a moderately impaired group (N = 77) and a more severely impaired group (N = 122). Three distinct clinical clusters were identified: a subgroup characterised by predominant mood symptoms (N = 76), a subgroup characterised by predominant negative symptoms (N = 19) and a subgroup characterised by overall mild symptom severity (N = 94). The subgroup with more severely impaired cognition also had more severe negative symptoms at baseline. Cognitive clusters were significantly associated with later social and occupational function, and associated with changes over time. Clinical clusters were associated with later social functioning but not occupational functioning, and were not associated with changes over time.

CONCLUSIONS

Baseline cognitive impairments are predictive of both later social and occupational function and change over time. This suggests that cognitive profiles offer valuable information in terms of prognosis and treatment needs.

Cognitive functioning and functional ability in women with schizophrenia and homelessness

Background

Studies of schizophrenia and homelessness are minimal from the Indian subcontinent. Women with schizophrenia and homelessness in India remain a highly vulnerable group and there is no data to date regarding their clinical characteristics. Cognitive impairment in schizophrenia remains a major factor determining outcomes in schizophrenia. We examined the cognitive functioning of women with schizophrenia and homelessness (WSH) and compared it to an age-matched group of women with schizophrenia living with their family (WSF).

Methods

36 women with schizophrenia and homelessness, and 32 women with schizophrenia who were living with family were evaluated for psychopathology using Scale for Assessment of Positive Symptoms (SAPS)/ Scale for assessment of negative symptoms (SANS) scales. Cognitive function was assessed using Montreal Cognitive Assessment (MOCA)/Rowland Universal Dementia Scale (RUDAS), and Frontal Assessment Battery (FAB), disability using World Health Organization - Disability assessment Scale (WHO-DAS) and psychosocial factors using a semi-structured proforma. The groups were compared using t-tests and chi-square for continuous and categorical variables respectively.

Results

Women with schizophrenia and homelessness were found to have significantly lower cognitive functioning, and much higher disability. Cognition and disability for women with schizophrenia and homelessness differed by 2-3 standard deviations with the mean for women living with family (i.e. z scores). Women with schizophrenia experiencing homelessness (WSH group) exhibited higher literacy levels and previous work experience compared to their counterparts. Those with family support are likely to face reduced pressures to work or earn, which further suggests that premorbid levels of functioning may not be the primary factors influencing the differences observed in cognitive assessments.

Conclusions

The study demonstrates significantly higher cognitive dysfunction in women with homelessness and schizophrenia, raising the possibility of much higher cognitive dysfunction being a predictor for homelessness in Indian women with schizophrenia.

Two-Month Cognitive Changes Enhance Prediction of Nonremission in Clinical High-Risk Individuals

BACKGROUND

Longitudinal changes in cognitive function may be crucial in predicting clinical outcomes in clinical high-risk (CHR) individuals. In this study, we aimed to investigate the predictive value of baseline cognitive impairment and short-term cognitive changes for nonremission and conversion to psychosis in individuals at CHR for psychosis compared with healthy control individuals (HCs).

METHODS

This study used a multiple-group prospective design with a 3-year follow-up. CHR individuals and HCs were assessed at baseline and at a 2-month follow-up. Neuropsychological performance was evaluated using the Chinese version of the MATRICS (Measurement and Treatment Research to Improve Cognition in Schizophrenia) Consensus Cognitive Battery.

RESULTS

The study included 310 CHR individuals and 93 HCs. Significant improvements in predicting nonremission in CHR individuals were observed when incorporating cognitive changes over 2 months (area under the receiver operating characteristic curve [AUC] for baseline cognition, 0.690; AUC for changes, 0.819; z = 3.365, p < .001). Key predictors included the Hopkins Verbal Learning Test-Revised (β = 0.083, p = .003), Wechsler Memory Scale-III spatial span (β = 0.330, p < .001), and Brief Visuospatial Memory Test-Revised (β = 0.127, p < .001). Conversely, predicting conversion to psychosis showed no significant difference between baseline and 2-month cognitive changes (AUC for baseline cognition, 0.667; AUC for changes, 0.666; z = 0.021, p = .242).

CONCLUSIONS

The findings underscore the importance of dynamic cognitive monitoring in CHR individuals. Short-term cognitive changes significantly enhanced the prediction of nonremission but did not add predictive value for conversion to psychosis beyond baseline assessments. Specific cognitive domains, such as verbal learning and working memory, were particularly valuable for predicting clinical outcomes.

Associations between momentary mental states and concurrent social functioning after remission from first episode psychosis: A HAMLETT ecological momentary assessment study

BACKGROUND

Symptom severity and social functioning are important outcomes after first episode psychosis (FEP), yet current evidence about associations between them is inconsistent and lacks (subclinical) momentary insights.

METHODS

The current Ecological Momentary Assessment (EMA) study was conducted in 58 people in remission from FEP, as part of the HAMLETT (Handling Antipsychotic Medication: Long-term Evaluation of Targeted Treatment) trial. At baseline, participants were prompted to report momentary mental states and social context 10x/day for eight consecutive days, including psychotic experiences (PEs), motivation/drive and negative affect, that may indicate proxies of (subclinical) psychotic, negative and general affective symptoms, respectively. We employed multilevel mixed-effects regressions to investigate associations between self-reported mental states and concurrent activity or social company and subjective appraisal thereof. We also conducted retrospective clinical assessments of symptoms (PANSS) and social functioning (WHODAS 2.0) and investigated their cross-sectional associations using multivariable linear regression.

RESULTS

Analyses of 3101 EMA-questionnaires showed that lower motivation/drive was associated with more passive activity and less company (OR = 0.96 [95%CI: 0.96; 0.97], OR = 0.95 [95%CI: 0.93; 0.96], N.B. ORs per 1-point symptom-score change). PEs and negative affect were associated with more proactive activity (OR = 1.02 [95%CI: 1.00; 1.03], OR = 1.02 [95%CI: 1.01; 1.03]). All three mental state domains were associated with lower activity appraisal overall, though activity-specific associations differed. PEs and negative affect were associated with lower company appraisal (B = -0.25 [95%CI: -0.36; -0.14], B = -0.15 [95%CI: -0.23; -0.06]). When assessed retrospectively, only PANSS general psychopathology was associated with poorer social functioning (B = 2.52 [95%CI: 1.69; 3.34]).

CONCLUSION

Self-reported PEs, momentary motivation/drive and general affective symptoms are associated with daily-life functioning after remission from FEP. Retrospective observer-rated and momentary self-report assessment methods do not measure the same aspects or intensity of psychopathology.

Magnetic resonance imaging-based machine learning classification of schizophrenia spectrum disorders: a meta-analysis

BACKGROUND

Recent advances in multivariate pattern recognition have fostered the search for reliable neuroimaging-based biomarkers in psychiatric conditions, including schizophrenia. These approaches consider the complex pattern of alterations in brain function and structure, overcoming the limitations of traditional univariate methods. To assess the reliability of neuroimaging-based biomarkers and the contribution of study characteristics in distinguishing individuals with schizophrenia spectrum disorder (SSD) from healthy controls (HCs), we conducted a systematic review of the studies that used multivariate pattern recognition for this objective.

METHODS

We systematically searched PubMed, Scopus, and Web of Science for studies on SSD classification using multivariate pattern analysis on magnetic resonance imaging data. We employed a bivariate random-effects meta-analytic model to explore the classification of sensitivity (SE) and specificity (SP) across studies while also evaluating the moderator effects of clinical and non-clinical variables.

RESULTS

A total of 119 studies (with 12,723 patients with SSD and 13,196 HCs) were identified. The meta-analysis estimated a SE of 79.1% (95% confidence interval [CI], 77.1%-81.0%) and a SP of 80.0% (95% CI, 77.8%-82.0%). In particular, the Positive and Negative Syndrome Scale and the Global Assessment of Functioning scores, age, age of onset, duration of untreated psychosis, deep learning, algorithm type, features selection, and validation methods had significant effects on classification performance.

CONCLUSIONS

Multivariate pattern analysis reliably identifies neuroimaging-based biomarkers of SSD, achieving ∼80% SE and SP. Despite clinical heterogeneity, discernible brain modifications effectively differentiate SSD from HCs. Classification performance depends on patient-related and methodological factors crucial for the development, validation, and application of prospective models in clinical settings.

Association between treatment response and dose of blonanserin transdermal patch in patients with acute schizophrenia: A post hoc cluster analysis based on baseline psychiatric symptoms

AIM

To explore the optimal dose of blonanserin transdermal patch (BNS-P) based on baseline psychiatric symptomatic characteristics during acute schizophrenia.

METHODS

A post hoc cluster analysis was conducted using data from a 6-week randomized, double-blind, placebo-controlled study of BNS-P (40 or 80 mg/day) in acute schizophrenia. We classified patients into three clusters based on baseline psychiatric symptoms. Efficacy was assessed using the change from baseline to week 6 in the PANSS total score. Safety was assessed by the incidence of adverse events.

RESULTS

Among 577 patients, three clusters were identified, characterized by severe psychiatric (Cluster-S; n = 122), predominant negative (Cluster-N; n = 191), and predominant positive (Cluster-P; n = 264) symptoms. In Cluster-P, both BNS-P 40 and 80 mg/day reduced PANSS total score significantly more than placebo (p = 0.036, effect size = 0.342; p < 0.001, effect size = 0.687, respectively). In Cluster-S and -N, only BNS-P 80 mg/day reduced PANSS total score significantly more than placebo (p = 0.045, effect size = 0.497; p = 0.034, effect size = 0.393, respectively). The effect size was greater at 80 mg/day than at 40 mg/day across all clusters. The most common treatment-emergent adverse events were akathisia and skin-related adverse events in all clusters.

CONCLUSION

BNS-P exhibited a dose-dependent antipsychotic effect in all clusters, particularly highlighting its efficacy in patients with predominant positive symptoms, even at lower doses. These findings provide novel and valuable insights for determining BNS-P dose tailoring to individual symptomatic characteristics in real-world practice.

Prediction of Clinical Outcomes in Psychotic Disorders Using Artificial Intelligence Methods: A Scoping Review

BACKGROUND

Psychotic disorders are major psychiatric disorders that can impact multiple domains including physical, social, and psychological functioning within individuals with these conditions. Being able to better predict the outcomes of psychotic disorders will allow clinicians to identify illness subgroups and optimize treatment strategies in a timely manner.

OBJECTIVE

In this scoping review, we aimed to examine the accuracy of the use of artificial intelligence (AI) methods in predicting the clinical outcomes of patients with psychotic disorders as well as determine the relevant predictors of these outcomes.

METHODS

This review was guided by the PRISMA Guidelines for Scoping Reviews. Seven electronic databases were searched for relevant published articles in English until 1 February 2024.

RESULTS

Thirty articles were included in this review. These studies were mainly conducted in the West (63%) and Asia (37%) and published within the last 5 years (83.3%). The clinical outcomes included symptomatic improvements, illness course, and social functioning. The machine learning models utilized data from various sources including clinical, cognitive, and biological variables such as genetic, neuroimaging measures. In terms of main machine learning models used, the most common approaches were support vector machine, random forest, logistic regression, and linear regression models. No specific machine learning approach outperformed the other approaches consistently across the studies, and an overall range of predictive accuracy was observed with an AUC from 0.58 to 0.95. Specific predictors of clinical outcomes included demographic characteristics (gender, socioeconomic status, accommodation, education, and employment); social factors (activity level and interpersonal relationships); illness features (number of relapses, duration of relapses, hospitalization rates, cognitive impairments, and negative and disorganization symptoms); treatment (prescription of first-generation antipsychotics, high antipsychotic doses, clozapine, use of electroconvulsive therapy, and presence of metabolic syndrome); and structural and functional neuroimaging abnormalities, especially involving the temporal and frontal brain regions.

CONCLUSIONS

The current review highlights the potential and need to further refine AI and machine learning models in parsing out the complex interplay of specific variables that contribute to the clinical outcome prediction of psychotic disorders.

Personalized Cognitive Health in Psychiatry: Current State and the Promise of Computational Methods

BACKGROUND

Decades of research have firmly established that cognitive health and cognitive treatment services are a key need for people living with psychosis. However, many current clinical programs do not address this need, despite the essential role that an individual's cognitive and social cognitive capacities play in determining their real-world functioning. Preliminary practice-based research in the Early Psychosis Intervention Network early psychosis intervention network shows that it is possible to develop and implement tools that delineate an individuals' cognitive health profile and that help engage the client and the clinician in shared decision-making and treatment planning that includes cognitive treatments. These findings signify a promising shift toward personalized cognitive health.

STUDY DESIGN

Extending upon this early progress, we review the concept of interindividual variability in cognitive domains/processes in psychosis as the basis for offering personalized treatment plans. We present evidence from studies that have used traditional neuropsychological measures as well as findings from emerging computational studies that leverage trial-by-trial behavior data to illuminate the different latent strategies that individuals employ.

STUDY RESULT

We posit that these computational techniques, when combined with traditional cognitive assessments, can enrich our understanding of individual differences in treatment needs, which in turn can guide evermore personalized interventions.

CONCLUSION

As we find clinically relevant ways to decompose maladaptive behaviors into separate latent cognitive elements captured by model parameters, the ultimate goal is to develop and implement approaches that empower clients and their clinical providers to leverage individual's existing learning capacities to improve their cognitive health and well-being.

Childhood trauma and treatment resistance in first-episode psychosis: Investigating the role of premorbid adjustment and duration of untreated psychosis

BACKGROUND

Early identification of treatment non-response in first-episode psychosis (FEP) is essential to outcome. Despite indications that exposure to childhood trauma (CT) can have adverse effects on illness severity, its impact on treatment non-response and the interplay with other pre-treatment characteristics is sparsely investigated. We use a lack of clinical recovery as an early indicator of treatment resistance to investigate the relationship between CT and treatment resistance status at one-year follow-up and the potential mediation of this effect by other pre-treatment characteristics.

METHODS

This prospective one-year follow-up study involved 141 participants recruited in their first year of treatment for a schizophrenia-spectrum disorder. We investigated clinical status, childhood trauma (CT), premorbid adjustment (PA), and duration of untreated psychosis (DUP) at baseline and clinical status at one-year follow-up. Ordinal regression analyses were conducted to investigate how PA and DUP affected the relationship between CT and one-year outcome in FEP.

RESULTS

45 % of the FEP sample reported moderate to severe CT, with significantly higher levels of CT in the early treatment resistant group compared to participants with full or partial early recovery. Ordinal regression analysis showed that CT was a significant predictor of being in a more severe outcome group (OR = 4.59). There was a partial mediation effect of PA and a full mediation effect of DUP on the effect of CT on outcome group membership.

DISCUSSION

Our findings indicate that reducing treatment delays may mitigate the adverse effects of CT on clinical outcomes and support the inclusion of broad trauma assessment in FEP services.

Longitudinal changes in cognitive function in early psychosis: a meta-analysis with the MATRICS consensus cognitive battery (MCCB)

INTRODUCTION

A previous meta-analysis indicated stable progress in cognitive functions in early psychosis, assessed through various tools. To avoid assessment-related heterogeneity, this study aims to examine the longitudinal cognitive function changes in early psychosis utilizing the MATRICS Consensus Cognitive Battery (MCCB).

METHODS

Embase, PubMed, and Scopus were systematically searched from their inception to September 26th 2023. The inclusion criteria were longitudinal studies that presented follow-up MCCB data for individuals experiencing first-episode psychosis (FEP) and those with ultra-high risk for psychosis (UHR).

RESULTS

Twelve studies with 791 participants (566 FEP patients and 225 healthy controls) were subjected to analysis. Suitable UHR studies were absent. Over time, both FEP patients and healthy controls showed significant improvements in MCCB total scores. Furthermore, FEP patients demonstrated improvements across all MCCB domains, while healthy controls only showed augmentations in specific domains such as speed of processing, attention, working memory, and reasoning and problem-solving. Visuospatial learning improvements were significantly greater in FEP patients compared to healthy controls. Subgroup analyses suggested that neither diagnostic type nor follow-up duration influenced the magnitude of cognitive improvement in FEP patients.

CONCLUSION

The magnitude of cognitive improvement for MCCB domains was not significantly different between FEP and healthy controls other than visuospatial learning. This underscores visuospatial learning as a potentially sensitive cognitive marker for early pathologic state changes in psychotic disorders.

Breaking the cycle: Exploring the relationship of metacognition beliefs, obsessive-compulsive symptoms, and psychosocial performance among individuals diagnosed with schizophrenia

THE RELEVANCE TO MENTAL HEALTH NURSING

This research paper explores the intricate relationship between metacognitive dysfunctional beliefs, obsessive-compulsive symptoms, and psychosocial performance in patients diagnosed with schizophrenia. Understanding these dynamics can help mental health nurses identify and address each patient's needs more effectively. It can guide them in devising personalized care plans that not only manage the symptoms but also improve the underlying mechanism that exacerbates the psychotic symptoms and social functioning and the overall quality of life. Moreover, the findings of this research can contribute to developing training programs for mental health nurses, equipping them with the necessary skills and knowledge to provide optimal care. What the paper adds to existing knowledge? • This study provides empirical evidence of the significant positive correlation between OCS and metacognitive dimensions in individuals with schizophrenia. • It highlights the role of certain demographic factors, such as younger age and single marital status, in increasing the likelihood of elevated OCS. • It underscores the inverse relationship between higher metacognitive dysfunctional beliefs and lower levels of psychosocial functioning. • It identifies age and metacognitive scores as crucial predictors of psychosocial functioning across various domains. What are the implications for practice? • The findings suggest that therapeutic nursing interventions for individuals diagnosed with schizophrenia should address metacognitive dysfunctional beliefs to improve overall functioning and well-being. • Clinicians, including psychiatrists and psychiatric nurses, should consider the patient's age, marital status, and metacognitive scores when assessing the risk of elevated OCS and devising treatment plans. • The study emphasizes the need for comprehensive psychiatric nursing assessment, including metacognitive dysfunction and OCS evaluation. What are the implications for future research? • Future research could explore the causal relationships between metacognitive dysfunctional beliefs, OCS, and psychosocial functioning in schizophrenia. • Longitudinal studies could provide insights into the progression of these relationships over time and the impact of therapeutic interventions. • Further research could also investigate the effectiveness of specific therapeutic strategies such as Metacognitive Therapy (MCT), Schema Therapy (ST), Cognitive Enhancement Therapy (CET), and Cognitive Behaviour Therapy (CBT) to address this population's metacognitive dysfunctional beliefs.

ABSTRACT

BACKGROUND: Schizophrenia is a chronic mental health disorder that significantly impacts an individual's cognitive, emotional and social functioning. Recent research has highlighted the role of metacognitive beliefs and obsessive-compulsive symptoms (OCS) in the psychosocial performance of individuals diagnosed with schizophrenia. Understanding these relationships could provide valuable insights for developing more effective nursing interventions. This study aimed to investigate the relationship between metacognitive beliefs, OCS and psychosocial performance among individuals diagnosed with schizophrenia.

DESIGN

A cross-sectional survey was conducted involving 174 purposively selected participants diagnosed with schizophrenia.

TOOLS

The Meta-Cognitions Questionnaire-30, Young Adult Self-Report Scale for OCS and Specific Level of Functioning Scale were used to gather the necessary data.

RESULTS

The study found a significant positive correlation between OCS and metacognitive dimensions. Age was a significant predictor with an Oddis Ratio of 2.471. The metacognitive dysfunction was a highly significant predictor in univariate and multivariate analyses, with Oddis Ratios of 1.087 and 1.106, respectively. The study also discovered that higher levels of metacognitive dysfunctional beliefs were associated with lower levels of psychosocial functioning. Age and the metacognitive dysfunction score were significant predictors of psychosocial functioning scores, accounting for 26.8% of the variance in these scores.

CONCLUSION

The study reveals a compelling inverse relationship between higher metacognitive dysfunctional beliefs and lower levels of psychosocial functioning in individuals diagnosed with schizophrenia. It also identifies certain demographic factors, such as younger age, as significant contributors to elevated OCS. Importantly, metacognitive dysfunction emerged as a critical predictor of psychosocial functioning across various domains. These findings underscore the potential of incorporating metacognitive-focused interventions in the treatment plans for schizophrenia patients. By addressing these cognitive patterns, healthcare professionals can enhance overall functioning and well-being in individuals diagnosed with schizophrenia.

Multivariate associations between neuroanatomy and cognition in unmedicated and medicated individuals with schizophrenia

Previous studies that focused on univariate correlations between neuroanatomy and cognition in schizophrenia identified some inconsistent findings. Moreover, antipsychotic medication may impact the brain-behavior profiles in affected individuals. It remains unclear whether unmedicated and medicated individuals with schizophrenia would share common neuroanatomy-cognition associations. Therefore, we aimed to investigate multivariate neuroanatomy-cognition relationships in both groups. A sample of 59 drug-naïve individuals with first-episode schizophrenia (FES) and a sample of 115 antipsychotic-treated individuals with schizophrenia were finally included. Multivariate modeling was conducted in the two patient samples between multiple cognitive domains and neuroanatomic features, such as cortical thickness (CT), cortical surface area (CSA), and subcortical volume (SV). We observed distinct multivariate correlational patterns between the two samples of individuals with schizophrenia. In the FES sample, better performance in token motor, symbol coding, and verbal fluency tests was associated with greater thalamic volumes but lower CT in the prefrontal and anterior cingulate cortices. Two significant multivariate correlations were identified in antipsychotic-treated individuals: 1) worse verbal memory performance was related to smaller volumes for the most subcortical structures and smaller CSA mainly in the temporal regions and inferior parietal lobule; 2) a lower symbol coding test score was correlated with smaller CSA in the right parahippocampal gyrus but greater volume in the right caudate. These multivariate patterns were sample-specific and not confounded by imaging quality, illness duration, antipsychotic dose, or psychopathological symptoms. Our findings may help to understand the neurobiological basis of cognitive impairments and the development of cognition-targeted interventions.

Cognitive Function and Variability in Antipsychotic Drug-Naive Patients With First-Episode Psychosis: A Systematic Review and Meta-Analysis

Importance

Cognitive impairment contributes significantly to clinical outcome and level of function in individuals with psychotic disorders. These impairments are present already at psychosis onset at a group level; however, the question of heterogeneity in cognitive function among patients has not been systematically investigated.

Objective

To provide an updated quantification of cognitive impairment at psychosis onset before patients receive potentially confounding antipsychotic treatment, and to investigate variability in cognitive function compared with healthy controls.

Data Sources

In this systematic review and meta-analysis, PubMed articles were searched up to September 15, 2022.

Study Selection

Original studies reporting data on cognitive function in antipsychotic drug-naive patients with first-episode psychosis (FEP) were included.

Data Extraction and Synthesis

Data were independently extracted by 2 researchers. Cognitive tasks were clustered according to 6 domains of the Measurement and Treatment Research to Improve Cognition in Schizophrenia (MATRICS) Consensus Cognitive Battery and the domain of executive function. Random-effects model meta-analyses of mean differences and coefficient of variation ratios (CVRs) were performed, as well as meta-regressions, assessment of study quality, and publication bias.

Main Outcomes and Measures

The main outcome measure was Hedges g for mean differences in cognition and CVR for within-group variability.

Results

Fifty studies were included in the analysis with a total of 2625 individuals with FEP (mean [SD] age, 25.2 [3.6] years, 60% male; 40% female) and 2917 healthy controls (mean [SD] age, 26.0 [4.6]; 55% male; 45% female). In all cognitive domains, the FEP group displayed significant impairment compared with controls (speed of processing: Hedges g = -1.16; 95% CI, -1.35 to -0.98; verbal learning: Hedges g = -1.08; 95% CI, -1.28 to -0.88; visual learning: Hedges g = -1.05; 95% CI, -1.27 to -0.82; working memory: Hedges g = -1.04; 95% CI, -1.35 to -0.73; attention: Hedges g = -1.03; 95% CI, -1.24 to -0.82; reasoning/problem solving: Hedges g = -0.90; 95% CI, -1.12 to -0.68; executive function: Hedges g = -0.88; 95% CI, -1.07 to -0.69). Individuals with FEP also exhibited a larger variability across all domains (CVR range, 1.34-1.92).

Conclusions and Relevance

Results of this systematic review and meta-analysis identified cognitive impairment in FEP before the initiation of antipsychotic treatment, with large effect sizes. The high variability within the FEP group suggests the need to identify those individuals with more severe cognitive problems who risk worse outcomes and could benefit the most from cognitive remediation.

Prevalence of Autism Spectrum Disorder in Children in Andalusia (Spain)

Autism Spectrum Disorder (ASD) is socially relevant because of its number and the intensity of the medical and socio-educational response it requires. In Andalusia, one in 70 children will be diagnosed with ASD in 2021. It is much more frequent in boys than in girls, being 5.91 times more likely to present it as a boy than as a girl. The age of diagnosis is increasingly younger, standing at 4.4 years. In more than half of primary schools and more than 75% of secondary schools there are an average of three students with ASD per school. It is necessary to develop a network of preferential care centers for students with ASD to generalize specialized care in ordinary modalities.

Prevalence of cognitive impairments and strengths in the early course of psychosis and depression

BACKGROUND

Studies investigating cognitive impairments in psychosis and depression have typically compared the average performance of the clinical group against healthy controls (HC), and do not report on the actual prevalence of cognitive impairments or strengths within these clinical groups. This information is essential so that clinical services can provide adequate resources to supporting cognitive functioning. Thus, we investigated this prevalence in individuals in the early course of psychosis or depression.

METHODS

A comprehensive cognitive test battery comprising 12 tests was completed by 1286 individuals aged 15-41 (mean age 25.07, s.d. 5.88) from the PRONIA study at baseline: HC (N = 454), clinical high risk for psychosis (CHR; N = 270), recent-onset depression (ROD; N = 267), and recent-onset psychosis (ROP; N = 295). Z-scores were calculated to estimate the prevalence of moderate or severe deficits or strengths (>2 s.d. or 1-2 s.d. below or above HC, respectively) for each cognitive test.

RESULTS

Impairment in at least two cognitive tests was as follows: ROP (88.3% moderately, 45.1% severely impaired), CHR (71.2% moderately, 22.4% severely impaired), ROD (61.6% moderately, 16.2% severely impaired). Across clinical groups, impairments were most prevalent in tests of working memory, processing speed, and verbal learning. Above average performance (>1 s.d.) in at least two tests was present for 40.5% ROD, 36.1% CHR, 16.1% ROP, and was >2 SDs in 1.8% ROD, 1.4% CHR, and 0% ROP.

CONCLUSIONS

These findings suggest that interventions should be tailored to the individual, with working memory, processing speed, and verbal learning likely to be important transdiagnostic targets.

Real-life outcomes in biotypes of psychotic disorders based on neurocognitive performance

Aiming at discerning potential biotypes within the psychotic syndrome, we have recently reported the possible existence of two clusters or biotypes across schizophrenia and bipolar disorder characterized by their cognitive performance using the Brief Assessment of Cognition in Schizophrenia (BACS) instrument and validated with independent biological and clinical indexes (Fernández-Linsenbarth et al. in Schizophr Res 229:102-111, 2021). In this previous work, the group with larger cognitive deficits (N = 93, including 69 chronic schizophrenia, 17 first episodes (FE) of schizophrenia and 7 bipolar disorder patients) showed smaller thalamus and hippocampus volume and hyper-synchronic electroencephalogram than the group with milder deficits (N = 105, including 58 chronic schizophrenia, 25 FE and 22 bipolar disorder patients). We predicted that if these biotypes indeed corresponded to different cognitive and biological substrates, their adaptation to real life would be different. To this end, in the present work we have followed up the patients' population included in that work at 1st and 3rd years after the date of inclusion in the 2021 study and we report on the statistical comparisons of each clinical and real-life outcomes between them. The first cluster, with larger cognitive deficits and more severe biological alterations, showed during that period a decreased capacity for job tenure (1st and 3rd years), more admissions to a psychiatric ward (1st year) and a higher likelihood for quitting psychiatric follow-up (3rd year). Patients in the second cluster, with moderate cognitive deficits, were less compliant with prescribed treatment at the 3rd year. The differences in real-life outcomes may give additional external validity to that yielded by biological measurements to the described biotypes based on neurocognition.

Cognitive subgroups and the relationships with symptoms, psychosocial functioning and quality of life in first-episode non-affective psychosis: a cluster-analysis approach

Introduction

Prior research examining cognitive heterogeneity in psychotic disorders primarily focused on chronic schizophrenia, with limited data on first-episode psychosis (FEP). We aimed to identify distinct cognitive subgroups in adult FEP patients using data-driven cluster-analytic approach, and examine relationships between cognitive subgroups and a comprehensive array of illness-related variables.

Methods

Two-hundred-eighty-nine Chinese patients aged 26-55 years presenting with FEP to an early intervention program in Hong Kong were recruited. Assessments encompassing premorbid adjustment, illness-onset profile, symptom severity, psychosocial functioning, subjective quality-of-life, and a battery of cognitive tests were conducted. Hierarchical cluster-analysis was employed, optimized with k-means clustering and internally-validated by discriminant-functional analysis. Cognitive subgroup comparisons in illness-related variables, followed by multivariable multinominal-regression analyzes were performed to identify factors independently predictive of cluster membership.

Results

Three clusters were identified including patients with globally-impaired (n = 101, 34.9%), intermediately-impaired (n = 112, 38.8%) and relatively-intact (n = 76, 26.3%) cognition (GIC, IIC and RIC subgroups) compared to demographically-matched healthy-controls' performance (n = 50). GIC-subgroup was older, had lower educational attainment, greater positive, negative and disorganization symptom severity, poorer insight and quality-of-life than IIC- and RIC-subgroups, and higher antipsychotic-dose than RIC-subgroup. IIC-subgroup had lower education levels and more severe negative symptoms than RIC-subgroup, which had better psychosocial functioning than two cognitively-impaired subgroups. Educational attainment and disorganization symptoms were found to independently predict cluster membership.

Discussion

Our results affirmed cognitive heterogeneity in FEP and identified three subgroups, which were differentially associated with demographic and illness-related variables. Further research should clarify longitudinal relationships of cognitive subgroups with clinical and functional outcomes in FEP.

Cognition and social functioning in first episode psychosis: A systematic review of longitudinal studies

Introduction

This systematic review aimed to answer whether we can predict subsequent social functioning in first episode psychosis (FEP) by means of an initial cognitive examination. In order to do this, we gathered longitudinal studies which evaluated neurocognition and/or social cognition regarding their impact on long-term social functioning of FEP patients.

Methods

The MOOSE method was employed and 28 studies covering data from a total of 2572 patients with longitudinal trajectories from 2 months to 5 years were reviewed.

Results

In general, cognitive deficits impacted on the social functioning of the FEP patients across the time. The neurocognitive domains which most closely predicted social functioning were processing speed, sustained attention and working memory. An overall cognitive dysfunction, low IQ and the academic trajectory were also found predictive. Regarding social cognition, the findings were not unanimous.

Discussion

In addition of the impact of each variable, several of the articles found a complex relationship between social cognition, neurocognition, social functioning and negative symptoms, pointing social cognition as a modulator of neurocognition but being modulated as well by negative symptoms. The principal clinical implication of this review is that the initial assessment of FEP patients and their rehabilitation must take cognition into account.

The enigma of vascular depression in old age: a critical update

Depression is common in older individuals and is associated with high disability and increased mortality, yet the factors predicting late-life depression (LLD) are poorly understood. The relationship between of depressive disorder, age- and disease-related processes have generated pathogenic hypotheses and provided new treatment options. LLD syndrome is often related to a variety of vascular mechanisms, in particular hypertension, cerebral small vessel disease, white matter lesions, subcortical vascular impairment, and other processes (e.g., inflammation, neuroimmune regulatory dysmechanisms, neurodegenerative changes, amyloid accumulation) that may represent etiological factors by affecting frontolimbic and other neuronal networks predisposing to depression. The "vascular depression" hypothesis suggests that cerebrovascular disease (CVD) and vascular risk factors may predispose, induce or perpetuate geriatric depressive disorders. It is based on the presence of various cerebrovascular risk factors in many patients with LLD, its co-morbidity with cerebrovascular lesions, and the frequent development of depression after stroke. Other findings related to vascular depression are atrophy of the medial temporal cortex or generalized cortical atrophy that are usually associated with cognitive impairment. Other pathogenetic hypotheses of LLD, such as metabolic or inflammatory ones, are briefly discussed. Treatment planning should consider there may be a modest response to antidepressants, but several evidence-based and novel treatment options for LLD exist, such as electroconvulsive therapy, transcranial magnetic stimulation, neurobiology-based psychotherapy, as well as antihypertension and antiinflammatory drugs. However, their effectiveness needs further investigation, and new methodologies for prevention and treatment of depression in older individuals should be developed.

Immune System Abnormalities in Schizophrenia: An Integrative View and Translational Perspectives

The immune system is generally known to be the primary defense mechanism against pathogens. Any pathological conditions are reflected in anomalies in the immune system parameters. Increasing evidence suggests the involvement of immune dysregulation and neuroinflammation in the pathogenesis of schizophrenia. In this systematic review, we summarized the available evidence of abnormalities in the immune system in schizophrenia. We analyzed impairments in all immune system components and assessed the level of bias in the available evidence. It has been shown that schizophrenia is associated with abnormalities in all immune system components: from innate to adaptive immunity and from humoral to cellular immunity. Abnormalities in the immune organs have also been observed in schizophrenia. Evidence of increased C-reactive protein, dysregulation of cytokines and chemokines, elevated levels of neutrophils and autoantibodies, and microbiota dysregulation in schizophrenia have the lowest risk of bias. Peripheral immune abnormalities contribute to neuroinflammation, which is associated with cognitive and neuroanatomical alterations and contributes to the pathogenesis of schizophrenia. However, signs of severe inflammation are observed in only about 1/3 of patients with schizophrenia. Immunological parameters may help identify subgroups of individuals with signs of inflammation who well respond to anti-inflammatory therapy. Our integrative approach also identified gaps in knowledge about immune abnormalities in schizophrenia, and new horizons for the research are proposed.

The neurobiological characterization of distinct cognitive subtypes in early-phase schizophrenia-spectrum disorders

INTRODUCTION

Cognitive deficits are present in some, but not all patients with schizophrenia-spectrum disorders (SSD). We and others have demonstrated three cognitive clusters: cognitively intact patients, patients with deficits in a few domains and those with global cognitive deficits. This study aimed to identify cognitive subtypes of early-phase SSD with matched controls as a reference group, and evaluated cognitive subgroups regarding clinical and brain volumetric measures.

METHODS

Eighty-six early-phase SSD patients were included. Hierarchical cluster analysis was conducted using global performance on the Brief Assessment of Cognition in Schizophrenia (BACS). Cognitive subgroups were subsequently related to clinical and brain volumetric measures (cortical, subcortical and cortical thickness) using ANCOVA.

RESULTS

Three distinct cognitive clusters emerged: relative to controls we found one cluster of patients with preserved cognition (n = 25), one moderately impaired cluster (n = 38) and one severely impaired cluster (n = 23). Cognitive subgroups were characterized by differences in volume of the left postcentral gyrus, left middle caudal frontal gyrus and left insula, while differences in cortical thickness were predominantly found in fronto-parietal regions. No differences were demonstrated in subcortical brain volume.

DISCUSSION

Current results replicate the existence of three distinct cognitive subgroups including one relatively large group with preserved cognitive function. Cognitive subgroups were characterized by differences in cortical regional brain volume and cortical thickness, suggesting associations with cortical, but not subcortical development and cognitive functioning such as attention, executive functions and speed of processing.