Network Structures of Social Functioning Domains in Schizophrenia and Bipolar Disorder: A Preliminary Study

Analysis of functional connectivity using machine learning and deep learning in different data modalities from individuals with schizophrenia

Objective. Schizophrenia(SCZ) is a severe mental disorder associated with persistent or recurrent psychosis, hallucinations, delusions, and thought disorders that affect approximately 26 million people worldwide, according to the World Health Organization. Several studies encompass machine learning (ML) and deep learning algorithms to automate the diagnosis of this mental disorder. Others study SCZ brain networks to get new insights into the dynamics of information processing in individuals suffering from the condition. In this paper, we offer a rigorous approach with ML and deep learning techniques for evaluating connectivity matrices and measures of complex networks to establish an automated diagnosis and comprehend the topology and dynamics of brain networks in SCZ individuals.Approach.For this purpose, we employed an functional magnetic resonance imaging (fMRI) and electroencephalogram (EEG) dataset. In addition, we combined EEG measures, i.e. Hjorth mobility and complexity, with complex network measurements to be analyzed in our model for the first time in the literature.Main results.When comparing the SCZ group to the control group, we found a high positive correlation between the left superior parietal lobe and the left motor cortex and a positive correlation between the left dorsal posterior cingulate cortex and the left primary motor. Regarding complex network measures, the diameter, which corresponds to the longest shortest path length in a network, may be regarded as a biomarker because it is the most crucial measure in different data modalities. Furthermore, the SCZ brain networks exhibit less segregation and a lower distribution of information. As a result, EEG measures outperformed complex networks in capturing the brain alterations associated with SCZ.Significance. Our model achieved an area under receiver operating characteristic curve (AUC) of 100% and an accuracy of 98.5% for the fMRI, an AUC of 95%, and an accuracy of 95.4% for the EEG data set. These are excellent classification results. Furthermore, we investigated the impact of specific brain connections and network measures on these results, which helped us better describe changes in the diseased brain.

Effectiveness of Switching to Long-acting Injectable Aripiprazole in Patients with Recent-onset and Chronic Schizophrenia

Objective

This study investigated the effectiveness of switching to once-monthly long-acting injectable (LAI) aripiprazole from other second-generation antipsychotics including LAI paliperidone palmitate in both recent-onset and chronic schizophrenia patients.

Methods

This was a 24-week prospective, open-label, flexible dose-switching study in patients with schizophrenia. Scores on the Positive and Negative Syndrome Scale (PANSS), Personal and Social Performance (PSP) scale, Clinical Global Impression (CGI), Subjective Well-being Under Neuroleptics-Short Form (SWN-K), and a computerized emotional recognition test (ERT) were evaluated. Subjects were divided into two groups (recent onset and chronic) based on 5 years' duration of the illness.

Results

Among the 82 patients participating, 67 (81.7%) completed the 24-week study. The discontinuation rate after switching to LAI aripiprazole did not differ according to clinical characteristics including type of previous antipsychotics. Scores on the PANSS, PSP, SWN-K, CGI, and ERT were significantly improved after a switch to LAI aripiprazole without exacerbation of metabolic parameters and bodyweight. The improvements in the PANSS, PSP, and CGI scores were significantly greater in patients with recent-onset than in those with chronic schizophrenia; the improvement in metabolic parameters was significantly greater in the latter group.

Conclusion

High rates of successful switching to LAI aripiprazole from other antipsychotics suggest its good tolerability and effectiveness. Improvements in psychopathology and social functioning were more evident in patients with recent- onset schizophrenia, and improvements in metabolic abnormalities were more prominent in patients with chronic schizophrenia.

Patient-reported needs predict perceived psychosocial disability and quality of life beyond symptom severity in schizophrenia

PURPOSE

We examined whether patient-rated or clinician-rated needs are more strongly associated with perceived psychosocial disability (PPD) and subjective quality of life (SQOL) of schizophrenia patients, beyond symptom severity.

METHODS

Hierarchical regression analyses were computed to test patient and clinician-rated unmet and met needs (estimated by eighty-two patient-clinician pairs) as predictors of PPD and SQOL above and beyond demographics and psychopathology. Needs, symptomatology, PPD and SQOL were estimated using Camberwell Assessment of Need (CAN), PANSS, WHODAS 2.0 and WHOQOL-BREF respectively.

RESULTS

Needs were significantly associated with all WHODAS 2.0 and WHOQOL-BREF domains above and beyond demographics and PANSS variables. Clinician-rated needs were better predictors of only one WHODAS 2.0 domain, while patient-rated needs were better predictors of all other WHODAS 2.0 and WHOQOL-BREF domains. Patient-rated unmet needs were more strongly than met needs associated with the most WHODAS 2.0 and WHOQOL-BREF subscores.

CONCLUSION

This study offers the first evidence that patient-rated needs, especially unmet needs, are strongly associated, above and beyond symptomatology, with global and domain-specific PPD of schizophrenia patients. Accordingly, strong relations of patient-rated needs with SQOL emerged. Identifying and addressing patient-reported needs could facilitate PPD and SQOL improvement more effectively than interventions confined solely to symptom remission.IMPLICATIONS FOR REHABILITATIONSchizophrenia is associated with poor rehabilitation and recovery outcomes, i.e., perceived psychosocial disability (PPD) and subjective quality of life (SQOL).Assessment of patients' needs constitutes the basis of determining treatment goals and planning tailor-made interventions to achieve crucial rehabilitative outcomes.Higher levels of patient-reported unmet needs are associated with poorer SQOL and higher global and domain-specific PPD of schizophrenia patients, above and beyond symptom severity.Addressing patient-reported needs through personalized interventions can facilitate more effectively PPD and SQOL improvement, than treatment confined to symptomatic alleviation.

Effectiveness of group metacognitive training and cognitive-behavioural therapy in a transdiagnostic manner for young patients with psychotic and non-psychotic disorders

AIM

To investigate group metacognitive training and cognitive-behavioural therapy (MCT/CBT) prospectively in a young population with various psychiatric disorders, including psychotic and mood disorders.

METHODS

This was a prospective study to investigate the effectiveness of group MCT/CBT on quality of life, psychotic symptoms, depression, self-esteem, perceived stress, social function and social cognition. The objective measures included the Positive and Negative Syndrome Scale (PANSS), clinical global impression (CGI), personal and social performance scale for social functioning, a computerized continuous performance test for sustained attention and a computerized emotional recognition test for social cognition. Self-report measures administered included the Subjective Well-being under Neuroleptics for quality of life, Ambiguous Intentions Hostility Questionnaire for suspiciousness, Drug Attitude Inventory, Beck Depression Inventory, Perceived Stress Scale, Brief Resilience Scale, Rosenberg Self-esteem Scale and visual analogue scale for the EQ-5D.

RESULTS

Among 110 young patients with early psychosis and mood disorders who participated, 82 (74.5%) completed the study. Social functioning, quality of life, self-esteem, resilience, depression, suspiciousness, social cognition, sustained attention and scores on the PANSS and CGI improved significantly after completing group MCT/CBT. Perceived stress, resilience and suspiciousness improved significantly only in participants with a non-psychotic disorder. Improvements in subjective well-being of the participants were associated with increases in self-esteem and resilience and decreases in depression and perceived stress.

CONCLUSIONS

Our study showed that group transdiagnostic MCT/CBT for young patients with mental illness improved subjective wellbeing, self-esteem, resilience, social cognition and social functioning and significantly diminished suspiciousness, perceived stress and depression.

Number of episodes and duration of illness associated with hypertension and 10-year cardiovascular risk in patients with bipolar disorder type I

Severe Mental Illnesses, including bipolar disorder (BD) and schizophrenia (SCZ), are burdened with an increased mortality and a significantly reduced life expectancy than general population, and cardiovascular diseases (CVD) are considered the most contributing conditions. The aim of the present study is to evaluate 10-year CV risk and the associated clinical characteristics in patients with SCZ, BD type I and II. Patients were consecutively recruited from two Italian psychiatric acute units. Single CV risk factors were assessed, and 10-year CV risk calculated by means of the CUORE Project 10-year CV risk algorithm, based on the combination of the following risk factors: age, systolic blood pressure, total and high-density lipoprotein cholesterol, diabetes, smoking habit, and hypertensive treatment. Three hundred patients were included. Patients with BD type I showed a higher prevalence of hypertension and 10-year CV risk score compared to the other groups. In subjects with BD type I, we found a significant correlation between duration of illness and number of mood episodes and both hypertension and 10-year CV risk score. Several preventive strategies should be provided to these vulnerable populations, such as correcting unhealthy lifestyles, prescribing medications at lower CV and metabolic risk, enhancing access to care.

Network Analysis of the Brief ICF Core Set for Schizophrenia

BACKGROUND

The International Classification of Functioning, Disability, and Health Core Sets (ICF-CSs) for schizophrenia are a set of categories for assessing functioning in persons with this health condition. This study aimed to: a) estimate the network structure of the Brief ICF-CS for schizophrenia, b) examine the community structure (categories strongly clustered together) underlying this network, and c) identify the most central categories within this network.

METHODS

A total of 638 health professionals from different backgrounds and with a significant role in the treatment of individuals with schizophrenia participated in a series of Delphi studies. Based on their responses we used the Ising model to estimate the network structure of the 25-category Brief ICF-CS, and then estimated the degree of centrality for all categories. Finally, the community structure was detected using the walktrap algorithm.

RESULTS

The resulting network revealed strong associations between individual categories within components of the ICF (i.e., Body functions, Activities and participation, and Environmental factors). The results also showed three distinct clusters of categories corresponding to the same three components. The categories e410 Individual attitudes of immediate family members, e450 Individual attitudes of health professionals, d910 Community life, and d175 Solving problems were among the most central categories in the Brief ICF-CS network.

CONCLUSION

These results demonstrate the utility of a network approach for estimating the structure of the ICF-CSs. Implications of these results for clinical interventions and development of new instruments are discussed.