Obstetric complications and psychopathology in schizophrenia: A systematic review and meta-analysis.

Schizophrenia (SZ) is a severe mental health condition involving gene-environment interactions, with obstetric complications (OCs) conferring an elevated risk for the disease. Current research suggests that OCs may exacerbate SZ symptoms. This study conducted a systematic review and meta-analysis to comprehensively evaluate differences in psychopathology between individuals with and without exposure to OCs in relation to SZ and related disorders. We systematically searched PubMed, PsycINFO, and SCOPUS to identify eligible studies. A total of 4091 records were retrieved through systematic and citation searches. 14 studies were included in the review, and 12 met the criteria for meta-analysis, involving 2992 patients. The analysis revealed that SZ patients who had been exposed to OCs exhibited significantly higher levels of positive symptoms (SMD=0.10, 95 %CI=0.01,0.20; p=0.03), general psychopathology (SMD=0.37, 95 %CI=0.22,0.52; p<0.001), total clinical symptomatology (SMD=0.44, 95 %CI=0.24,0.64; p<0.001) and depressive symptoms (SMD=0.47, 95 %CI=0.09,0.84; p=0.01). No significant differences were found in negative symptomatology and functioning. Our results suggest that OCs are not only associated with an increased risk of developing psychosis but with more severe symptomatology.

A Bayesian analysis of heart rate variability changes over acute episodes of bipolar disorder.

Bipolar disorder (BD) involves autonomic nervous system dysfunction, detectable through heart rate variability (HRV). HRV is a promising biomarker, but its dynamics during acute mania or depression episodes are poorly understood. Using a Bayesian approach, we developed a probabilistic model of HRV changes in BD, measured by the natural logarithm of the Root Mean Square of Successive RR interval Differences (lnRMSSD). Patients were assessed three to four times from episode onset to euthymia. Unlike previous studies, which used only two assessments, our model allowed for more accurate tracking of changes. Results showed strong evidence for a positive lnRMSSD change during symptom resolution (95.175% probability of positive direction), though the sample size limited the precision of this effect (95% Highest Density Interval [-0.0366, 0.4706], with a Region of Practical Equivalence: [-0.05; 0.05]). Episode polarity did not significantly influence lnRMSSD changes.

Sex matters: Differences in prodromes, clinical and neuropsychological features in individuals with a first episode mania or psychosis.

OBJECTIVE: This study was aimed at identifying sex differences in patients presenting a first episode mania (FEM) or psychosis (FEP) to help shaping early treatment strategies focused on sex differences. METHODS: Patients with a FEM or FEP underwent a clinical, neuropsychological (neurocognitive functions and emotional intelligence) and functional assessment. Performance on those variables was compared between groups through general linear model, with sex and group (FEM vs FEP) as main effects and group by sex interactions. RESULTS: The total sample included 113 patients: FEM = 72 (45.83 % females) and FEP = 41 (46.34 % females). There were significant main effects for group (not for sex) for most of the clinical features (depressive, negative and positive symptoms) and psychosocial functioning (χ2 = 8.815, p = 0.003). As for neuropsychological performance, there were significant main effects for sex and group. Females performed better than males in verbal memory (χ2 = 9.038, p = 0.003) and obtained a higher emotional intelligence quotient (χ2 = 13.20, p < 0.001). On the contrary, males obtained better results in working memory (χ2 = 7.627, p = 0.006). FEP patients significantly underperformed FEM patients in most cognitive domains. There were significant group by sex interactions for few neuropsychological variables, namely processing speed (χ2 = 4.559, p = 0.033) and verbal fluency (χ2 = 8.913, p = 0.003). LIMITATIONS: Differences between sexes were evaluated, but the influence of gender was not considered. Retrospective evaluation of prodromes and substance use. No healthy control group comparator. CONCLUSION: The main finding is the presence of significant sex effect and group by sex interaction on specific neurocognitive cognition and emotional intelligence measures. Tailored sex-based early treatment strategies might be implemented.

Sex differences in prolactin levels and clinical outcomes in patients with a first psychotic episode.

AIM: To analyze the clinical, neurocognitive, and functional impact of prolactin levels according to sex in patients with a First Episode Psychosis (FEP). METHODS: We measured prolactin levels in 221 non-affective FEP patients treated with antipsychotics (AP) and 224 healthy controls, at baseline and 2-year follow-up. We examined whether the relationships between clinical and functional variables were mediated by prolactin, controlling for antipsychotic use, according to sex. RESULTS: Prolactin levels were higher in patients when compared to controls at both time points. Baseline factors associated with prolactin were chlorpromazine equivalents, attention, and executive functioning. In the FEP group, prolactin levels were associated with functioning and diminished expression in males, and with working memory in females. Prolactin levels (p=0.0134) played a role as a mediator between negative symptomatology (p=0.086) and functional outcome (p=0.008) only in FEP male patients at baseline. CONCLUSIONS: Prolactin plays a role in the functionality and clinical symptomatology of FEP patients. Our results suggest that pharmacological counselling in patients with hyperprolactinemia at baseline and negative symptomatology might improve their functional and clinical outcomes.

Identifying digital biomarkers of illness activity and treatment response in bipolar disorder with a novel wearable device (TIMEBASE): protocol for a pragmatic observational clinical study.

BACKGROUND: Bipolar disorder is highly prevalent and consists of biphasic recurrent mood episodes of mania and depression, which translate into altered mood, sleep and activity alongside their physiological expressions. AIMS: The IdenTifying dIgital bioMarkers of illnEss activity and treatment response in BipolAr diSordEr with a novel wearable device (TIMEBASE) project aims to identify digital biomarkers of illness activity and treatment response in bipolar disorder. METHOD: We designed a longitudinal observational study including 84 individuals. Group A comprises people with acute episode of mania (n = 12), depression (n = 12 with bipolar disorder and n = 12 with major depressive disorder (MDD)) and bipolar disorder with mixed features (n = 12). Physiological data will be recorded during 48 h with a research-grade wearable (Empatica E4) across four consecutive time points (acute, response, remission and episode recovery). Group B comprises 12 people with euthymic bipolar disorder and 12 with MDD, and group C comprises 12 healthy controls who will be recorded cross-sectionally. Psychopathological symptoms, disease severity, functioning and physical activity will be assessed with standardised psychometric scales. Physiological data will include acceleration, temperature, blood volume pulse, heart rate and electrodermal activity. Machine learning models will be developed to link physiological data to illness activity and treatment response. Generalisation performance will be tested in data from unseen patients. RESULTS: Recruitment is ongoing. CONCLUSIONS: This project should contribute to understanding the pathophysiology of affective disorders. The potential digital biomarkers of illness activity and treatment response in bipolar disorder could be implemented in a real-world clinical setting for clinical monitoring and identification of prodromal symptoms. This would allow early intervention and prevention of affective relapses, as well as personalisation of treatment.

Wearable Data From Subjects Playing Super Mario, Taking University Exams, or Performing Physical Exercise Help Detect Acute Mood Disorder Episodes via Self-Supervised Learning: Prospective, Exploratory, Observational Study.

BACKGROUND: Personal sensing, leveraging data passively and near-continuously collected with wearables from patients in their ecological environment, is a promising paradigm to monitor mood disorders (MDs), a major determinant of the worldwide disease burden. However, collecting and annotating wearable data is resource intensive. Studies of this kind can thus typically afford to recruit only a few dozen patients. This constitutes one of the major obstacles to applying modern supervised machine learning techniques to MD detection. OBJECTIVE: In this paper, we overcame this data bottleneck and advanced the detection of acute MD episodes from wearables' data on the back of recent advances in self-supervised learning (SSL). This approach leverages unlabeled data to learn representations during pretraining, subsequently exploited for a supervised task. METHODS: We collected open access data sets recording with the Empatica E4 wristband spanning different, unrelated to MD monitoring, personal sensing tasks-from emotion recognition in Super Mario players to stress detection in undergraduates-and devised a preprocessing pipeline performing on-/off-body detection, sleep/wake detection, segmentation, and (optionally) feature extraction. With 161 E4-recorded subjects, we introduced E4SelfLearning, the largest-to-date open access collection, and its preprocessing pipeline. We developed a novel E4-tailored transformer (E4mer) architecture, serving as the blueprint for both SSL and fully supervised learning; we assessed whether and under which conditions self-supervised pretraining led to an improvement over fully supervised baselines (ie, the fully supervised E4mer and pre-deep learning algorithms) in detecting acute MD episodes from recording segments taken in 64 (n=32, 50%, acute, n=32, 50%, stable) patients. RESULTS: SSL significantly outperformed fully supervised pipelines using either our novel E4mer or extreme gradient boosting (XGBoost): n=3353 (81.23%) against n=3110 (75.35%; E4mer) and n=2973 (72.02%; XGBoost) correctly classified recording segments from a total of 4128 segments. SSL performance was strongly associated with the specific surrogate task used for pretraining, as well as with unlabeled data availability. CONCLUSIONS: We showed that SSL, a paradigm where a model is pretrained on unlabeled data with no need for human annotations before deployment on the supervised target task of interest, helps overcome the annotation bottleneck; the choice of the pretraining surrogate task and the size of unlabeled data for pretraining are key determinants of SSL success. We introduced E4mer, which can be used for SSL, and shared the E4SelfLearning collection, along with its preprocessing pipeline, which can foster and expedite future research into SSL for personal sensing.

Sleep-wake variations of electrodermal activity in bipolar disorder.

BACKGROUND: Affective states influence the sympathetic nervous system, inducing variations in electrodermal activity (EDA), however, EDA association with bipolar disorder (BD) remains uncertain in real-world settings due to confounders like physical activity and temperature. We analysed EDA separately during sleep and wakefulness due to varying confounders and potential differences in mood state discrimination capacities. METHODS: We monitored EDA from 102 participants with BD including 35 manic, 29 depressive, 38 euthymic patients, and 38 healthy controls (HC), for 48 h. Fifteen EDA features were inferred by mixed-effect models for repeated measures considering sleep state, group and covariates. RESULTS: Thirteen EDA feature models were significantly influenced by sleep state, notably including phasic peaks (p < 0.001). During wakefulness, phasic peaks showed different values for mania (M [SD] = 6.49 [5.74, 7.23]), euthymia (5.89 [4.83, 6.94]), HC (3.04 [1.65, 4.42]), and depression (3.00 [2.07, 3.92]). Four phasic features during wakefulness better discriminated between HC and mania or euthymia, and between depression and euthymia or mania, compared to sleep. Mixed symptoms, average skin temperature, and anticholinergic medication affected the models, while sex and age did not. CONCLUSION: EDA measured from awake recordings better distinguished between BD states than sleep recordings, when controlled by confounders.

Blood Cell Count Ratios at Baseline are Associated with Initial Clinical Response to Clozapine in Treatment-Resistant, Clozapine-Naïve, Schizophrenia-Spectrum Disorder.

BACKGROUND: Clozapine is the recommended treatment for managing treatment-resistant schizophrenia (TRS), and immunological mechanisms may be involved in its unique antipsychotic efficacy. This study investigated whether baseline immune abnormalities measured with blood cell count ratios can predict the clinical response after initiating treatment with clozapine in patients with clozapine naïve TRS. METHODS: A longitudinal design was developed, involving 32 patients diagnosed with treatment-resistant, clozapine-naïve schizophrenia-spectrum disorder. Patients were evaluated at baseline before clozapine starting and 8 weeks of follow-up. Psychopathological status and immune abnormalities (blood cell count ratios: neutrophil-lymphocyte ratio [NLR], monocyte-lymphocyte ratio [MLR], platelet-lymphocyte ratio [PLR] and basophil-lymphocyte ratio [BLR]) were evaluated in each visit. RESULTS: Baseline NLR (b=- 0.364; p=0.041) and MLR (b =- 0.400; p=0.023) predicted the change in positive symptoms over the 8-week period. Patients who exhibited a clinical response showed higher baseline NLR (2.38±0.96 vs. 1.75±0.83; p=0.040) and MLR (0.21±0.06 vs. 0.17±0.02; p=0.044) compared to non-responders. In the ROC analysis, the threshold points to distinguish between responders and non-responders were approximately 1.62 for NLR and 0.144 for MLR, yielding AUC values of 0.714 and 0.712, respectively. No statistically significant differences were observed in the blood cell count ratios from baseline to the 8-week follow-up. CONCLUSION: Our study emphasizes the potential clinical significance of baseline NLR and MLR levels as predictors of initial clozapine treatment response in patients with TRS. Future studies with larger sample sizes and longer follow-up periods should replicate our findings.

Cognitive reserve moderates the relationship between childhood maltreatment, objective and subjective cognition, and psychosocial functioning in individuals with first-episode psychosis.

OBJECTIVE: This study aimed to assess the relationship between childhood maltreatment (CM), objective and subjective cognition, and psychosocial functioning in adults with first-episode psychosis (FEP) by examining the moderating role of cognitive reserve (CR). A secondary objective was to explore whether unique CM subtypes (physical and/or emotional abuse, sexual abuse, physical and/or emotional neglect) were driving this relationship. METHOD: Sixty-six individuals with FEP (Mage = 27.3, SD = 7.2 years, 47% male) completed a comprehensive neuropsychological test battery, the Cognitive Complaints in Bipolar Disorder Rating Assessment (COBRA), the Functioning Assessment Short Test (FAST), the Childhood Trauma Questionnaire (CTQ), and the Cognitive Reserve Assessment Scale in Health (CRASH). Linear regression analyses were conducted to evaluate the interaction effect of CR between CM and cognitive and psychosocial variables, controlling for age, sex, and social desirability (CTQ-denial-minimization). RESULTS: In adults with FEP overall CM interacted with CR to predict COBRA-subjective cognitive complaints, but not neurocognitive or psychosocial functioning. Sexual abuse and physical neglect interacted with CR to predict verbal memory. Most of the CM subtypes interacted with CR to predict FAST-leisure time, whereas only emotional neglect interacted with CR to predict FAST-interpersonal relationships. Overall, greater CR was related to better functioning. CONCLUSIONS: The current results indicate that associations between specific CM subtypes, subjective and objective cognition, and psychosocial domains are moderated through CR with greater functioning. Early interventions focused on CR seeking to improve cognitive and psychosocial outcomes, with emphasis on improving subjective cognitive functions would be beneficial for individuals with FEP and CM. (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Automated mood disorder symptoms monitoring from multivariate time-series sensory data: getting the full picture beyond a single number.

Mood disorders (MDs) are among the leading causes of disease burden worldwide. Limited specialized care availability remains a major bottleneck thus hindering pre-emptive interventions. MDs manifest with changes in mood, sleep, and motor activity, observable in ecological physiological recordings thanks to recent advances in wearable technology. Therefore, near-continuous and passive collection of physiological data from wearables in daily life, analyzable with machine learning (ML), could mitigate this problem, bringing MDs monitoring outside the clinician's office. Previous works predict a single label, either the disease state or a psychometric scale total score. However, clinical practice suggests that the same label may underlie different symptom profiles, requiring specific treatments. Here we bridge this gap by proposing a new task: inferring all items in HDRS and YMRS, the two most widely used standardized scales for assessing MDs symptoms, using physiological data from wearables. To that end, we develop a deep learning pipeline to score the symptoms of a large cohort of MD patients and show that agreement between predictions and assessments by an expert clinician is clinically significant (quadratic Cohen's κ and macro-average F1 score both of 0.609). While doing so, we investigate several solutions to the ML challenges associated with this task, including multi-task learning, class imbalance, ordinal target variables, and subject-invariant representations. Lastly, we illustrate the importance of testing on out-of-distribution samples.

Anthropometry in antipsychotic-naïve first-episode psychosis patients: An exploratory approach to the role of environmental early life events in two independent samples.

BACKGROUND: Patients with schizophrenia exhibit a reduced life expectancy mainly due to medical-related pathologies which might have been initiated due to stressful events during fetal development. Indeed, intra-uterus growth patterns predict anthropometric measures in adulthood, describing risk factors for schizophrenia and metabolic disorders. We aim to evaluate anthropometric values in two cohorts of antipsychotic-naïve first-episode episode psychosis (FEP) and correlated them with surrogate markers of the fetal environment such as birth weight (BW) and season of birth. METHODS: BW, season of birth, and anthropometric values from 2 cohorts of FEP patients (Barcelona and Santander) were evaluated. In cohort B, 91 patients, and 110 controls while in cohort S, 644 and 235 were included respectively. RESULTS: Patients were shorter, slimmer, and with lower BMI compared with controls. In both cohorts, patients, and female patients born in winter displayed the shortest height. Regarding BW, height was significantly associated with the interaction of diagnosis and BW in the whole sample and the male subsample. CONCLUSIONS: Our results confirm reduced anthropometric features in FEP at onset while suggesting the influence of winter birth and BW, highlighting the role of early life events in the later outcome of FEP with sex differences.

Nurse-led lifestyle intervention in a cohort of schizophrenia patients treated with clozapine.

Patients diagnosed with schizophrenia are characterized by early mortality compared to the general population. The main cause of this premature death reflects medical complications linked to metabolic syndrome (MetS). The use of antipsychotics such as clozapine is associated with weight gain and metabolic disturbances in certain predisposed individuals. Non-pharmacological interventions for weight control have become a key element for secondary prevention in the health of patients diagnosed with schizophrenia. Here, we aim to evaluate the physical health effects of a nurse-led non-pharmacological intervention program in patients with a diagnosis of schizophrenia treated with clozapine. Thirty-one outpatients from the outpatient clinical facility of Hospital Clinic in Barcelona, Spain diagnosed with schizophrenia and other psychotic disorders receiving clozapine treatment were enrolled in a prospective interventional study, comprising an 8-week group program of therapeutic education in a healthy lifestyle. MetS factors, physical activity, diet, and lifestyle were evaluated at baseline, post-intervention (8 weeks), and 3 months after the program. Weight, body mass index, high-density lipoprotein cholesterol, and diet patterns displayed significant differences post-intervention and after 3 months, while only waist, hip perimeter, and lifestyle improved post-intervention. Our results suggest the effectiveness of the lifestyle intervention in patients under clozapine treatment despite its long-time differential effect. Strategies to prevent weight gain and metabolic decline will help prevent premature cardiometabolic disease in this vulnerable population.

Meta-analysis of the effects of adjuvant drugs in co-occurring bipolar and substance use disorder.

BACKGROUND: Individuals with bipolar disorder (BD) often have co-occurring substance use disorders (SUDs), which substantially impoverish the course of illness. Despite the importance of this dual diagnosis, the evidence of the efficacy and safety of adjuvant treatments is mostly unknown. OBJECTIVE: To perform a meta-analysis to evaluate the efficacy and safety of adjuvant drugs in patients with co-occurring BD and SUD. METHODS: We searched PubMed, Scopus, and Web of Knowledge until 30th April 2022 for randomized clinical trials (RCT) evaluating the efficacy and safety of adjuvant drugs compared to placebo in patients with a dual diagnosis of BD and SUD. We meta-analyzed the effect of adjuvant drugs on general outcomes (illness severity, mania, depression, anxiety, abstinence, substance craving, substance use, gamma-GT, adherence, and adverse events) and used the results to objectively assess the quality of the evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) approach. For completeness, we also report the specific effects of specific adjuvant drugs in patients with specific substance disorders. RESULTS: We included 15 RCT studies (9 alcohol, 3 cocaine, 2 nicotine, and 1 cannabis) comprising 628 patients allocated to treatment and 622 to placebo. There was low-quality evidence that adjuvant drugs may reduce illness severity (g=-0.25, 95% CI: -0.44, -0.06), and very-low quality evidence that they may decrease substance use (g=-0.23, 95% CI: -0.44, -0.02) and increase substance abstinence (g=0.21, 95% CI: 0.04, 0.38). DISCUSSION: There is low-quality evidence that adjuvant drugs may help reduce illness severity, probably via facilitating abstinence and lower substance use. However, the evidence is weak; thus, these results should be considered cautiously until better evidence exists.

Obstetric complications and clinical presentation in first episode of psychosis.

OBJECTIVE: Psychotic disorders exhibit a complex aetiology that combines genetic and environmental factors. Among the latter, obstetric complications (OCs) have been widely studied as risk factors, but it is not yet well understood how OCs relate to the heterogeneous presentations of psychotic disorders. We assessed the clinical phenotypes of individuals with a first episode of psychosis (FEP) in relation to the presence of OCs. METHODS: Two-hundred seventy-seven patients with an FEP were assessed for OCs using the Lewis-Murray scale, with data stratified into three subscales depending on the timing and the characteristics of the obstetric event, namely: complications of pregnancy, abnormal foetal growth and development and difficulties in delivery. We also considered other two groups: any complications during the pregnancy period and all OCs taken altogether. Patients were clinically evaluated with the Positive and Negative Syndrome Scale for schizophrenia. RESULTS: Total OCs and difficulties in delivery were related to more severe psychopathology, and this remained significant after co-varying for age, sex, traumatic experiences, antipsychotic dosage and cannabis use. CONCLUSIONS: Our results highlight the relevance of OCs for the clinical presentation of psychosis. Describing the timing of the OCs is essential in understanding the heterogeneity of the clinical presentation.

Exploring Digital Biomarkers of Illness Activity in Mood Episodes: Hypotheses Generating and Model Development Study.

BACKGROUND: Depressive and manic episodes within bipolar disorder (BD) and major depressive disorder (MDD) involve altered mood, sleep, and activity, alongside physiological alterations wearables can capture. OBJECTIVE: Firstly, we explored whether physiological wearable data could predict (aim 1) the severity of an acute affective episode at the intra-individual level and (aim 2) the polarity of an acute affective episode and euthymia among different individuals. Secondarily, we explored which physiological data were related to prior predictions, generalization across patients, and associations between affective symptoms and physiological data. METHODS: We conducted a prospective exploratory observational study including patients with BD and MDD on acute affective episodes (manic, depressed, and mixed) whose physiological data were recorded using a research-grade wearable (Empatica E4) across 3 consecutive time points (acute, response, and remission of episode). Euthymic patients and healthy controls were recorded during a single session (approximately 48 h). Manic and depressive symptoms were assessed using standardized psychometric scales. Physiological wearable data included the following channels: acceleration (ACC), skin temperature, blood volume pulse, heart rate (HR), and electrodermal activity (EDA). Invalid physiological data were removed using a rule-based filter, and channels were time aligned at 1-second time units and segmented at window lengths of 32 seconds, as best-performing parameters. We developed deep learning predictive models, assessed the channels' individual contribution using permutation feature importance analysis, and computed physiological data to psychometric scales' items normalized mutual information (NMI). We present a novel, fully automated method for the preprocessing and analysis of physiological data from a research-grade wearable device, including a viable supervised learning pipeline for time-series analyses. RESULTS: Overall, 35 sessions (1512 hours) from 12 patients (manic, depressed, mixed, and euthymic) and 7 healthy controls (mean age 39.7, SD 12.6 years; 6/19, 32% female) were analyzed. The severity of mood episodes was predicted with moderate (62%-85%) accuracies (aim 1), and their polarity with moderate (70%) accuracy (aim 2). The most relevant features for the former tasks were ACC, EDA, and HR. There was a fair agreement in feature importance across classification tasks (Kendall W=0.383). Generalization of the former models on unseen patients was of overall low accuracy, except for the intra-individual models. ACC was associated with "increased motor activity" (NMI>0.55), "insomnia" (NMI=0.6), and "motor inhibition" (NMI=0.75). EDA was associated with "aggressive behavior" (NMI=1.0) and "psychic anxiety" (NMI=0.52). CONCLUSIONS: Physiological data from wearables show potential to identify mood episodes and specific symptoms of mania and depression quantitatively, both in BD and MDD. Motor activity and stress-related physiological data (EDA and HR) stand out as potential digital biomarkers for predicting mania and depression, respectively. These findings represent a promising pathway toward personalized psychiatry, in which physiological wearable data could allow the early identification and intervention of mood episodes.

Risk of suicide attempt repetition after an index attempt: A systematic review and meta-analysis.

OBJECTIVES: To estimate the risk of suicide attempt repetition among individuals with an index attempt. It also aims to study the role of risk factors and prevention programme in repetition. METHODS: This systematic review and meta-analysis was conducted in keeping with the PRISMA 2020 guidelines. Studies on attempt repetition (both cohort studies and intervention studies) were searched from inception to 2022. RESULTS: A total of 110 studies comprising 248,829 attempters was reviewed. The overall repetition rate was 0.20 (0.17, 0.22). Repetition risk linearly increased over time. A higher risk of attempt repetition was associated with female sex and index attempts in which self-cutting methods were used. Moreover, a mental disorder diagnosis was associated with an increasing repetition risk (OR = 2.02, p < .01). The delivery of a preventive programme reduced the repetition risk, OR = 0.76, p < .05; however, this effect was significant for psychotherapy interventions, OR = 0.38, p < .01. CONCLUSION: One in five suicide attempters will engage in a new suicide attempt. An elevated repetition risk is associated with being female, more severe index methods and psychiatric disorder diagnosis. Preventive programmes, particularly psychotherapy, may contribute to reducing repetition risk and eventually save lives.

The impact of the Catalonia Suicide Risk Code (CSRC) in a tertiary hospital: Reduction in hospitalizations and emergency room visits for any reason but not for suicide attempt.

INTRODUCTION: Suicide attempts represent a public health concern. The objective of this study is to describe the clinical characteristics of patients visiting an emergency room for a suicide attempt and included in a suicide prevention program, the Catalonia Suicide Risk Code (CSRC), particularly focusing on the follow-up evaluations. MATERIALS AND METHODS: The CSRC program is divided in 3 phases: (1) alert and activation, (2) proactive telephone and face-to-face follow-up and (3) comprehensive preventive health monitoring. This is the analysis of the sample of patients attempting or intending suicide who were seen at a tertiary hospital in Barcelona, and their 1-year follow-up outcome. RESULTS: Three hundred and sixty-five patients were included. In 15% of the cases, there was no previous psychiatric history but in the majority of cases, a previous psychiatric diagnosis was present. The most common type of suicide attempt was by drug overdose (84%). Up to 66.6% of the patients attended the scheduled follow-up visit in the CSRC program. A significant reduction in the proportion of patients visiting the emergency room for any reason (but not specifically for a suicide attempt) and being hospitalized in the first semester in comparison with the second six months after the CSRC activation (30.1% versus 19.9%, p=0.006; 14.1% versus 5.8%, p=0.002) was observed. CONCLUSIONS: The clinical risk factors and the findings of the CSRC helped in the characterization of suicide attempters. The CSRC may contribute to reduce hospitalizations and the use of mental health care resources, at least in the short-term.

Maternity in women with schizophrenia and schizoaffective disorder.

PURPOSE: Maternity rates in women with schizophrenia have tripled in the past decades, with a current percentage similar to the general population (50-60%). However, mothers with schizophrenia present higher rates of single marital status, and social dysfunction than the general population. In addition, the incidence of unplanned pregnancy, abortions, miscarriages and obstetric complications is higher. This study aimed to describe variables related to maternity in this population. METHODS: One-hundred and ninety-two outpatient women diagnosed with schizophrenia and schizoaffective disorders were included (DSM-IV-TR criteria) in a two-site study. Psychosocial risk factors, demographic variables and clinical features were recorded in the same visit. Non-parametric tests were used in order to describe variables for likelihood offspring in psychotic women. RESULTS: One-hundred and forty-seven (76.6%) women suffered from schizophrenia and 45 (23.4%) schizoaffective disorder. Psychotic mothers used to be married/having a partner and presented a later onset of the illness (over 36 years old) compared to non-mothers. In addition, mothers generally presented pregnancy before the onset of illness. Regarding obstetric complications, around the 80% of the sample presented at least one obstetric complication. Although desire or wish of pregnancy was reported in 66.3% of the mothers, rates of planned pregnancy were 25% and only the 47.9% were currently taking care of their children with their husband/partner. CONCLUSION: Maternity rate is high in this population. This study highlights the need to promote reproductive health care for women with mental disorders and to consider their reproductive life plan. Later onset of disease and being married are potential predictors of maternity in our sample of women with a schizophrenia and schizoaffective disorders while only the half were caring their children at the moment of the evaluation.

The effect of early life events on glucose levels in first-episode psychosis.

First episode of psychosis (FEP) patients display a wide variety of metabolic disturbances at onset, which might underlie these patients' increased morbidity and early mortality. Glycemic abnormalities have been previously related to pharmacological agents; however, recent research highlights the impact of early life events. Birth weight (BW), an indirect marker of the fetal environment, has been related to glucose abnormalities in the general population over time. We aim to evaluate if BW correlates with glucose values in a sample of FEP patients treated with different antipsychotics. Two hundred and thirty-six patients were included and evaluated for clinical and metabolic variables at baseline and at 2, 6, 12, and 24 months of follow-up. Pearson correlations and linear mixed model analysis were conducted to analyze the data. Antipsychotic treatment was grouped due to its metabolic risk profile. In our sample of FEP patients, BW was negatively correlated with glucose values at 24 months of follow-up [r=-0.167, p=0.037]. BW showed a trend towards significance in the association with glucose values over the 24-month period (F=3.22; p=0.073) despite other confounders such as age, time, sex, body mass index, antipsychotic type, and chlorpromazine dosage. This finding suggests that BW is involved in the evolution of glucose values over time in a cohort of patients with an FEP, independently of the type of pharmacological agent used in treatment. Our results highlight the importance of early life events in the later metabolic outcome of patients.

Obstetric complications and cognition in schizophrenia: a systematic review and meta-analysis.

BACKGROUND: Schizophrenia (SZ) is a complex brain disorder linked to cognitive and neurostructural abnormalities that involves genetic and environmental factors with obstetric complications (OCs) at birth conferring a high risk for the disease. Indeed, current research in the general population describes the deleterious effect of OCs on cognitive performance in adulthood. With this rationale, we aim to review the relationship between OCs and cognition in SZ and related psychotic disorders. METHODS: A systematic review and meta-analysis describing cognitive function and OCs in patients with SZ and related disorders were conducted. PubMed, EmBase, SCOPUS, and the Cochrane Library were systematically searched to identify eligible studies up to January 2022. We calculated the effect sizes (Hedges' g) of cognitive domains within each study and quantified the proportion of between-study variability using the I2 statistic. Homogeneity was assessed using the Q-statistic (X2). The study was registered on PROSPERO (CRD42018094238). RESULTS: A total of 4124 studies were retrieved, with 10 studies meeting inclusion criteria for the systematic review and eight for meta-analysis. SZ subjects with OCs showed poor verbal memory [Hedges' g = -0.89 (95% CI -1.41 to -0.37), p < 0.001] and working memory performance [Hedges' g = -1.47 (95% CI -2.89 to -0.06), p = 0.01] in a random-effect model compared to those without OCs. CONCLUSIONS: OCs appear to have a moderate impact on specific cognitive such as working memory and verbal memory. Our findings suggest that OCs are associated with brain development and might underlie the cognitive abnormalities described at onset of psychosis.