Objective:
In psychosis, treatment often focuses on symptom reduction whereas social functioning is also essential. In this study, we investigate positive psychotic symptoms and medication use in ...relation to social functioning over a 3-year time-period in 531 patients diagnosed with psychosis. Furthermore, relations of positive symptoms with needs for care and quality of life were also investigated.
Method:
Using repeated measures analysis, changes were measured over time. Hereafter, mixed model analyses were performed to determine the associations of social functioning, needs for care, and quality of life with psychotic symptoms and patient characteristics. Finally, we assessed differences in symptoms and medication dose between those with an increase and those with a decrease in social functioning.
Results:
Patients significantly improved in social functioning, while psychotic symptoms increased. Improvement in social functioning was associated with younger age, higher IQ, and lower social functioning at T1, but not with positive symptoms. Also, improvement in social functioning was found to be related to a decrease in the dose of clozapine. Improvement in social functioning occurs despite worsening of positive symptoms.
Conclusions:
The findings suggest the need to further explore the relation between symptomatology, social functioning, and medication use. In the treatment of psychotic disorders, one should reconsider the strong focus on reducing psychotic symptoms. The current focus needs to shift much more toward improving functional outcome, especially when the patient expresses a desire for change in this respect.
Objective:Despite the multitude of longitudinal neuroimaging studies that have been published, a basic question on the progressive brain loss in schizophrenia remains unaddressed: Does it reflect ...accelerated aging of the brain, or is it caused by a fundamentally different process? The authors used support vector regression, a supervised machine learning technique, to address this question.Method:In a longitudinal sample of 341 schizophrenia patients and 386 healthy subjects with one or more structural MRI scans (1,197 in total), machine learning algorithms were used to build models to predict the age of the brain and the presence of schizophrenia (“schizophrenia score”), based on the gray matter density maps. Age at baseline ranged from 16 to 67 years, and follow-up scans were acquired between 1 and 13 years after the baseline scan. Differences between brain age and chronological age (“brain age gap”) and between schizophrenia score and healthy reference score (“schizophrenia gap”) were calculated. Accelerated brain aging was calculated from changes in brain age gap between two consecutive measurements. The age prediction model was validated in an independent sample.Results:In schizophrenia patients, brain age was significantly greater than chronological age at baseline (+3.36 years) and progressively increased during follow-up (+1.24 years in addition to the baseline gap). The acceleration of brain aging was not constant: it decreased from 2.5 years/year just after illness onset to about the normal rate (1 year/year) approximately 5 years after illness onset. The schizophrenia gap also increased during follow-up, but more pronounced variability in brain abnormalities at follow-up rendered this increase nonsignificant.Conclusions:The progressive brain loss in schizophrenia appears to reflect two different processes: one relatively homogeneous, reflecting accelerated aging of the brain and related to various measures of outcome, and a more variable one, possibly reflecting individual variation and medication use. Differentiating between these two processes may not only elucidate the various factors influencing brain loss in schizophrenia, but also assist in individualizing treatment.
Although structural brain alterations in schizophrenia have been demonstrated extensively, their quantitative distribution has not been studied over the last 14 years despite advances in ...neuroimaging. Moreover, a volumetric meta-analysis has not been conducted in antipsychotic-naive patients. Therefore, meta-analysis on cross-sectional volumetric brain alterations in both medicated and antipsychotic-naive patients was conducted. Three hundred seventeen studies published from September 1, 1998 to January 1, 2012 comprising over 9000 patients were selected for meta-analysis, including 33 studies in antipsychotic-naive patients. In addition to effect sizes, potential modifying factors such as duration of illness, sex composition, current antipsychotic dose, and intelligence quotient matching status of participants were extracted where available. In the sample of medicated schizophrenia patients (n = 8327), intracranial and total brain volume was significantly decreased by 2.0% (effect size d = -0.17) and 2.6% (d = -0.30), respectively. Largest effect sizes were observed for gray matter structures, with effect sizes ranging from -0.22 to -0.58. In the sample of antipsychotic-naive patients (n = 771), volume reductions in caudate nucleus (d = -0.38) and thalamus (d = -0.68) were more pronounced than in medicated patients. White matter volume was decreased to a similar extent in both groups, while gray matter loss was less extensive in antipsychotic-naive patients. Gray matter reduction was associated with longer duration of illness and higher dose of antipsychotic medication at time of scanning. Therefore, brain loss in schizophrenia is related to a combination of (early) neurodevelopmental processes-reflected in intracranial volume reduction-as well as illness progression.
IMPORTANCE The human brain forms a large-scale structural network of regions and interregional pathways. Recent studies have reported the existence of a selective set of highly central and ...interconnected hub regions that may play a crucial role in the brain's integrative processes, together forming a central backbone for global brain communication. Abnormal brain connectivity may have a key role in the pathophysiology of schizophrenia. OBJECTIVE To examine the structure of the rich club in schizophrenia and its role in global functional brain dynamics. DESIGN Structural diffusion tensor imaging and resting-state functional magnetic resonance imaging were performed in patients with schizophrenia and matched healthy controls. SETTING Department of Psychiatry, Rudolf Magnus Institute of Neuroscience, University Medical Center Utrecht, Utrecht, the Netherlands. PARTICIPANTS Forty-eight patients and 45 healthy controls participated in the study. An independent replication data set of 41 patients and 51 healthy controls was included to replicate and validate significant findings. MAIN OUTCOME(S) AND MEASURES Measures of rich club organization, connectivity density of rich club connections and connections linking peripheral regions to brain hubs, measures of global brain network efficiency, and measures of coupling between brain structure and functional dynamics. RESULTS Rich club organization between high-degree hub nodes was significantly affected in patients, together with a reduced density of rich club connections predominantly comprising the white matter pathways that link the midline frontal, parietal, and insular hub regions. This reduction in rich club density was found to be associated with lower levels of global communication capacity, a relationship that was absent for other white matter pathways. In addition, patients had an increase in the strength of structural connectivity–functional connectivity coupling. CONCLUSIONS Our findings provide novel biological evidence that schizophrenia is characterized by a selective disruption of brain connectivity among central hub regions of the brain, potentially leading to reduced communication capacity and altered functional brain dynamics.
Lifestyle interventions are important to improve the mental and physical health outcomes of people with mental illness. However, referring patients to lifestyle interventions is still not a common ...practice for mental healthcare professionals (MHCPs) and their own lifestyle habits may impact this. The aim of this study was to investigate MHCPs' personal lifestyle habits, their lifestyle history and referral practices, and if these are associated with their lifestyle habits, gender, and profession.
In this cross-sectional study, an online questionnaire was distributed across relevant MHCP's in The Netherlands. Ordinal regression analyses on lifestyle habits, gender, profession, and lifestyle history and referral practices were conducted.
A total of the 1,607 included MHCPs, 87.6% finds that lifestyle should be part of every psychiatric treatment, but depending on which lifestyle factor, 55.1-84.0% take a lifestyle history, 29.7-41.1% refer to interventions, and less than half (44.2%) of smoking patients are advised to quit. MHCPs who find their lifestyle important, who are physically more active, females, and MHCPs with a nursing background take more lifestyle histories and refer more often. Compared to current smokers, MHCPs who never or formerly smoked have higher odds (2.64 and 3.40, respectively,
< 0.001) to advice patients to quit smoking.
This study indicates that MHCPs' personal lifestyle habits, gender, and profession affect their clinical lifestyle practices, and thereby the translation of compelling evidence on lifestyle psychiatry to improved healthcare for patients.
Due to increased cardiometabolic risks and premature mortality in people with severe mental illness (SMI), monitoring cardiometabolic health is considered essential. We aimed to analyse screening ...rates and prevalences of cardiometabolic risks in routine mental healthcare and its associations with patient and disease characteristics.
We collected screening data in SMI from three mental healthcare institutions in the Netherlands, using most complete data on the five main metabolic syndrome (MetS) criteria (waist circumference, blood pressure, HDL-cholesterol, triglycerides, fasting blood glucose) within a 30-day timeframe in 2019/2020. We determined screened patients' cardiometabolic risks and analysed associations with patient and disease characteristics using multiple logistic regression.
In 5037 patients, screening rates ranged from 28.8% (waist circumference) to 76.4% (fasting blood glucose) within 2019–2020, and 7.6% had a complete measurement of all five MetS criteria. Older patients, men and patients with psychotic disorders had higher odds of being screened. Without regarding medication use, risk prevalences ranged from 29.6% (fasting blood glucose) to 56.8% (blood pressure), and 48.6% had MetS. Gender and age were particularly associated with odds for individual risk factors. Cardiometabolic risk was present regardless of illness severity and did generally not differ substantially between diagnoses, in−/outpatients and institutions.
Despite increased urgency and guideline development for cardiometabolic health in SMI last decades, screening rates are still low, and the MetS prevalence across screened patients is almost twice that of the general population. More intensive implementation strategies are needed to translate policies into action to improve cardiometabolic health in SMI.
•Screening rates on cardiometabolic risk factors in people with SMI were low.•Elderly, men and people with psychosis had higher odds of being screened.•Metabolic syndrome prevalence was almost twice as high as in the general population.•Gender and age were particularly associated with odds for individual risk factors.•Risk was largely independent of disease severity, treatment setting and diagnoses.
Background Schizophrenia is a brain disease involving progressive loss of gray matter of unknown cause. Most likely, this loss reflects neuronal damage, which should, in turn, be accompanied by ...microglia activation. Microglia activation can be quantified in vivo using (R) -11 CPK11195 and positron emission tomography (PET). The purpose of this study was to investigate whether microglia activation occurs in patients with recent-onset schizophrenia. Methods Ten patients with recent-onset schizophrenia and 10 age-matched healthy control subjects were included. A fully quantitative (R) -11 CPK11195 PET scan was performed on all subjects, including arterial sampling to generate a metabolite-corrected input curve. Results Compared with control subjects, binding potential of (R) -11 CPK11195 in total gray matter was increased in patients with schizophrenia. There were no differences in other PET parameters. Conclusions Activated microglia are present in schizophrenia patients within the first 5 years of disease onset. This suggests that, in this period, neuronal injury is present and that neuronal damage may be involved in the loss of gray matter associated with this disease. Microglia may form a novel target for neuroprotective therapies in schizophrenia.
Normal brain-aging occurs at all structural levels. Excessive pathophysiological changes in the brain, beyond the normal one, are implicated in the etiology of brain disorders such as severe forms of ...the schizophrenia spectrum and dementia. To account for brain-aging in health and disease, it is critical to study the age-dependent trajectories of brain biomarkers at various levels and among different age groups.
The intracranial volume (ICV) is a key biological marker, and changes in the ICV during the lifespan can teach us about the biology of development, aging, and gene X environment interactions. However, whether ICV changes with age in adulthood is not resolved.
Applying a semi-automatic in-house-built algorithm for ICV extraction on T1w MR brain scans in the Dutch longitudinal cohort (GROUP), we measured ICV changes. Individuals between the ages of 16 and 55 years were scanned up to three consecutive times with 3.32±0.32 years between consecutive scans (N = 482, 359, 302). Using the extracted ICVs, we calculated ICV longitudinal aging-trajectories based on three analysis methods; direct calculation of ICV differences between the first and the last scan, fitting all ICV measurements of individuals to a straight line, and applying a global linear mixed model fitting. We report statistically significant increase in the ICV in adulthood until the fourth decade of life (average change +0.03%/y, or about 0.5 ml/y, at age 20), and decrease in the ICV afterward (−0.09%/y, or about −1.2 ml/y, at age 55). To account for previous cross-sectional reports of ICV changes, we analyzed the same data using a cross-sectional approach. Our cross-sectional analysis detected ICV changes consistent with the previously reported cross-sectional effect. However, the reported amount of cross-sectional changes within this age range was significantly larger than the longitudinal changes. We attribute the cross-sectional results to a generational effect.
In conclusion, the human intracranial volume does not stay constant during adulthood but instead shows a small increase during young adulthood and a decrease thereafter from the fourth decade of life. The age-related changes in the longitudinalmeasure are smaller than those reported using cross-sectional approaches and unlikely to affect structural brain imaging studies correcting for intracranial volume considerably. As to the possible mechanisms involved, this awaits further study, although thickening of the meninges and skull bones have been proposed, as well as a smaller amount of brain fluids addition above the overall loss of brain tissue.
Display omitted
•The ICV was measured in a longitudinal cohort with 3 consecutive scans.•These values were used to model ICV development during young and middle adulthood.•Our main results show that the ICV continues to change during life.•Meaning: the ICV continues to grow during young adulthood.•Subsequently, during middle adulthood the ICV starts to decline.
The purpose of this study is to create a model that can classify schizophrenia patients and healthy controls based on whole brain gray matter densities (voxel-based morphometry, VBM) from structural ...magnetic resonance imaging (MRI) scans. In addition, we investigated the stability of the accuracy of the models, when built with different sample sizes. Using a support vector machine, we built a model from 239 subjects (128 patients and 111 healthy controls) and classified 71.4% correct (leave-one-out). We replicated and validated this result by testing the unaltered model on a completely independent sample of 277 subjects (155 patients and 122 healthy controls), scanned with a different scanner. The classification rate of the validation sample was 70.4%. The model's discriminative pattern showed, amongst other differences, gray matter density decreases in frontal and superior temporal lobes and hippocampus in schizophrenia patients with respect to healthy controls and increases in gray matter density in basal ganglia and left occipital lobe and. Larger training samples gave more reliable models: Models based on sample sizes smaller than N=130 should be considered unstable and can even score below chance.
► We used VBM (sMRI) to separate individuals with schizophrenia from healthy controls. ► A support vector machine model trained on a large sample (N=239) gave 71% accuracy. ► Application of the model to a replication sample (N=277) validated this result: 70%. ► Larger amounts of training subjects gave higher accuracy and more stable models.
Abstract Individuals with psychotic disorders often lead sedentary lives, heightening the risk of developing forward head posture. Forward head posture affects upper cervical vertebrae, raising the ...likelihood of daily discomforts like skeletal misalignment, neck pain, and reduced cardiorespiratory fitness. Improving cardiorespiratory fitness in psychotic disorders is relevant, given its proven benefits in enhancing physical and mental health. This study investigates forward head posture by measuring craniovertebral angles in psychotic disorders and the relationship with reduced cardiorespiratory fitness. To determine whether forward head posture is specific to psychotic disorders, we also included individuals with autism spectrum disorder and healthy controls. Among 85 participants (32 psychotic disorders, 26 autism spectrum disorder, 27 healthy controls), photogrammetric quantification revealed a significantly lower mean craniocervical angle in psychotic disorders compared to autism spectrum disorder ( p = < 0.02) and the healthy control group ( p = < 0.01). Reduced craniovertebral angle is related to diminished cardiorespiratory fitness in psychosis (R 2 = 0.45, p = < 0.01) but not in other control groups. This study found reduced craniovertebral angles, indicating forward head posture in psychotic disorders. Moreover, this relates to diminished cardiorespiratory fitness. Further research is needed to examine the underlying causes and to investigate whether this can be reversed through physical therapy.
PDF
