Early warning signals observed in motor activity preceding mood state change in bipolar disorder.

INTRODUCTION: Alterations in motor activity are well-established symptoms of bipolar disorder, and time series of motor activity can be considered complex dynamical systems. In such systems, early warning signals (EWS) occur in a critical transition period preceding a sudden shift (tipping point) in the system. EWS are statistical observations occurring due to a system's declining ability to maintain homeostasis when approaching a tipping point. The aim was to identify critical transition periods preceding bipolar mood state changes. METHODS: Participants with a validated bipolar diagnosis were included to a one-year follow-up study, with repeated assessments of the participants' mood. Motor activity was recorded continuously by a wrist-worn actigraph. Participants assessed to have relapsed during follow-up were analyzed. Recognized EWS features were extracted from the motor activity data and analyzed by an unsupervised change point detection algorithm, capable of processing multi-dimensional data and developed to identify when the statistical property of a time series changes. RESULTS: Of 49 participants, four depressive and four hypomanic/manic relapses among six individuals occurred, recording actigraphy for 23.8 ± 0.2 h/day, for 39.8 ± 4.6 days. The algorithm detected change points in the time series and identified critical transition periods spanning 13.5 ± 7.2 days. For depressions 11.4 ± 1.8, and hypomania/mania 15.6 ± 10.2 days. CONCLUSION: The change point detection algorithm seems capable of recognizing impending mood episodes in continuous flowing data streams. Hence, we present an innovative method for forecasting approaching relapses to improve the clinical management of bipolar disorder.

Seroprevalence of SARS-CoV-2 antibodies in a prospective cohort of patients admitted to an acute psychiatric ward in Norway during the initial months of the COVID-19 pandemic.

BACKGROUND: The severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) that causes coronavirus disease 2019 (COVID-19) spread around the world during the first part of 2020. The purpose of the study was to assess the prevalence of SARS-CoV-2 infection among patients acutely admitted to the Psychiatric Clinic, Haukeland University Hospital. METHODS: Serum tests to assess for antibodies to SARS-CoV-2 were administered at admission to the clinic together with a questionnaire on symptoms and demographical information. Further information was obtained from the medical records. RESULTS: The cumulative seroprevalence in the 266 participants was 0.75%, the cumulative reported cases in the Norwegian general population was 0.61% at the end of the inclusion period of the study. Twenty-five percent of participants had risk factors for a serious course of COVID-19. There was a low prevalence of cohabitation and only 20% had their main income derived from ordinary salaries (not welfare). CONCLUSION: The prevalence of SARS-CoV-2 infection in a sample of patients acutely admitted to the Psychiatric Clinic, Haukeland University Hospital, was comparable to reported cases in the general population. A possible link to governmental and municipal restrictions, general low workplace participation and cohabitation is discussed.

Seroprevalence of SARS-CoV-2 antibodies is comparable to the general population.Twenty-five percent of patients had elevated risk for a serious course of COVID-19 because of somatic conditions.Fifty-seven percent lived alone, 17% with one other person in the household.Twenty percent had regular salary as the main income source for the last three months before admission.

Association between C-reactive protein levels and antipsychotic treatment during 12 months follow-up period after acute psychosis.

BACKGROUND: A potential role of inflammatory pathways in the pathology of schizophrenia has been suggested for at least a subgroup of patients. Elevated levels of the inflammatory marker C-reactive protein (CRP) have been observed, with associations to pathogenesis and symptoms. The current evidence regarding effects of antipsychotics on CRP levels is ambiguous. OBJECTIVES: To examine and compare the influence on CRP levels of three pharmacologically diverse new generation antipsychotics during a one-year follow-up in schizophrenia spectrum disorder. METHODS: In a multicenter, pragmatic and rater-blinded randomized trial, the effects of amisulpride, aripiprazole and olanzapine were compared in 128 patients with schizophrenia spectrum disorder. All had positive symptoms of psychosis at study entry. Clinical and laboratory assessments including the measurement of CRP levels were conducted at baseline, and 1, 3, 6, 12, 26, 39, and 52 weeks thereafter. RESULTS: For all antipsychotic drugs analysed together, there was an increase in CRP levels during the one-year follow-up. Aripiprazole, as opposed to amisulpride and olanzapine, was associated with a reduced CRP level after one week, after which the CRP level caught up with the other drugs. Compared to those previously exposed to antipsychotic drugs, antipsychotic-naïve patients had lower CRP levels at all follow-up time points, but with the same temporal patterns of change. CONCLUSION: Treatment with amisulpride, aripiprazole and olanzapine showed different effects on CRP levels in patients with schizophrenia spectrum disorders, modified by previous antipsychotics exposure status. This finding suggests that antipsychotic drugs may vary with respect to their influence on pro-inflammatory pathways. TRIAL REGISTRATION: ClinicalTrials.gov ID: NCT01446328; URL: http://www. CLINICALTRIALS: gov/.

Amisulpride, aripiprazole, and olanzapine in patients with schizophrenia-spectrum disorders (BeSt InTro): a pragmatic, rater-blind, semi-randomised trial.

BACKGROUND: Amisulpride, aripiprazole, and olanzapine are first-line atypical antipsychotics that have not previously been compared head-to-head in a pragmatic trial. We aimed to compare the efficacy and safety of these agents in a controlled trial. METHODS: This pragmatic, rater-blind, randomised controlled trial was done in three academic centres of psychiatry in Norway, and one in Austria. Eligible patients were aged 18 years or older, met ICD-10 criteria for schizophrenia-spectrum disorders (F20-29), and had symptoms of active psychosis. Eligible patients were randomly assigned to receive oral amisulpride, aripiprazole, or olanzapine. Treatment allocation was open to patients and staff, and starting dose, treatment changes, and adjustments were left to the discretion of the treating physician. Computer-generated randomisation lists for each study centre were prepared by independent statisticians. Patients were followed up for 52 weeks after random assignment, during which assessments were done 8 times by researchers masked to treatment. The primary outcome was reduction of the Positive And Negative Syndrome Scale (PANSS) total score at 52 weeks, and primary analyses were done in the intention-to-treat population. This trial is registered with ClinicalTrials.gov, number NCT01446328. FINDINGS: Between Oct 20, 2011, and Dec 30, 2016, we assessed 359 patients for eligibility. 215 patients were excluded (107 did not meet inclusion criteria, 82 declined to participate, 26 other reasons). 144 patients (mean baseline PANSS total estimated score 78·4 [SD 1·4]) were randomly assigned 1:1:1 to receive amisulpride (44 patients), aripiprazole (48 patients) or olanzapine (52 patients). After 52 weeks, the patients allocated to amisulpride had a PANSS total score reduction of 32·7 points (SD 3·1) compared with 21·9 points reduction with aripiprazole (SD 3·9, p=0·027) and 23·3 points with olanzapine (2·9, p=0·025). We observed weight gain and increases of serum lipids and prolactin in all groups. 26 serious adverse events (SAEs) among 20 patients were registered (four [9%] of 44 patients allocated to amisulpride, ten [21%] of 48 patients allocated to aripiprazole, and six [12%] of 52 patients allocated to olanzapine), with no statistically significant differences between the study drugs. 17 (65%) of the 26 SAEs occurred during the use of the study drug, with readmission or protracted hospital admission accounting for 13 SAEs. One death by suicide, one unspecified death, and one life-threatening accident occurred during follow-up, after cessation of treatment. INTERPRETATION: Amisulpride was more efficacious than aripiprazole or olanzapine for reducing the PANSS total scores in adults with schizophrenia-spectrum disorders. Side-effect differences among the groups were generally small. This study supports the notion that clinically relevant efficacy differences exist between antipsychotic drugs. Future research should aim to compare first-line antipsychotics directly in pragmatic clinical trials that reflect everyday clinical practice. FUNDING: The Research Council of Norway, the Western Norway Regional Health Trust, and participating hospitals and universities.

Applying machine learning in motor activity time series of depressed bipolar and unipolar patients compared to healthy controls.

Current practice of assessing mood episodes in affective disorders largely depends on subjective observations combined with semi-structured clinical rating scales. Motor activity is an objective observation of the inner physiological state expressed in behavior patterns. Alterations of motor activity are essential features of bipolar and unipolar depression. The aim was to investigate if objective measures of motor activity can aid existing diagnostic practice, by applying machine-learning techniques to analyze activity patterns in depressed patients and healthy controls. Random Forrest, Deep Neural Network and Convolutional Neural Network algorithms were used to analyze 14 days of actigraph recorded motor activity from 23 depressed patients and 32 healthy controls. Statistical features analyzed in the dataset were mean activity, standard deviation of mean activity and proportion of zero activity. Various techniques to handle data imbalance were applied, and to ensure generalizability and avoid overfitting a Leave-One-User-Out validation strategy was utilized. All outcomes reports as measures of accuracy for binary tests. A Deep Neural Network combined with SMOTE class balancing technique performed a cut above the rest with a true positive rate of 0.82 (sensitivity) and a true negative rate of 0.84 (specificity). Accuracy was 0.84 and the Matthews Correlation Coefficient 0.65. Misclassifications appear related to data overlapping among the classes, so an appropriate future approach will be to compare mood states intra-individualistically. In summary, machine-learning techniques present promising abilities in discriminating between depressed patients and healthy controls in motor activity time series.

Predictors of treatment satisfaction in antipsychotic-naïve and previously medicated patients with acute-phase psychosis.

Background: Treatment satisfaction predicts treatment adherence and long-term outcome for patients with psychosis. It is therefore important to understand the underpinnings of patient satisfaction in psychosis treatment for optimal treatment delivery. Aims: To examine the associations between satisfaction and level and change in positive symptoms, insight, depression and side effects of antipsychotics in previously medicated and antipsychotic-naïve patients. Method: Data derive from a randomised trial, with 226 respondents at baseline and 104 at follow-up. The measures were the positive subscale and insight item from the Positive and Negative Syndrome Scale, Calgary Depression Scale, the UKU Consumer Satisfaction Rating Scale, and the UKU side effects scale. Structural equation modelling was used to test the model. The full information maximum likelihood estimator used all available data. Results: In the sample of 226 patients, 67.3% were male and 44.2% were antipsychotic-naïve. The mean age was 34.1 years. For previously medicated patients, satisfaction was predicted by level of insight (b = -2.21, ß = -0.42) and reduction in positive symptoms (b = -0.56, ß = -0.39). For antipsychotic-naïve patients, satisfaction was predicted by level and change of insight (b = -2.21, ß = -0.46), change in depression (b = -0.37, ß = -0.26) and side effects (b = -0.15, ß = -0.30). All predictors were significant at the 0.05 level. Conclusion: Reducing positive symptoms and side effects are important to enhance patient satisfaction. However, improving insight and reducing depression are more important in antipsychotic-naïve patients.