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Background: Antipsychotic treatment resistance affects up to a third of individuals with schizophrenia, with recent research finding systematic biological differences between antipsychotic resistant and responsive patients. Our aim was to determine whether cognitive impairment at first episode significantly differs between future antipsychotic responders and resistant cases. Methods: Analysis of data from seven international cohorts of first-episode psychosis (FEP) with cognitive data at baseline (N = 683) and follow-up data on antipsychotic treatment response: 605 treatment responsive and 78 treatment resistant cases. Cognitive measures were grouped into seven cognitive domains based on the preexisting literature. We ran multiple imputation for missing data and used logistic regression to test for associations between cognitive performance at FEP and treatment resistant status at follow-up. Results: On average patients who were future classified as treatment resistant reported poorer performance across most cognitive domains at baseline. Univariate logistic regressions showed that antipsychotic treatment resistance cases had significantly poorer IQ/general cognitive functioning at FEP (OR = 0.70, p = .003). These findings remained significant after adjusting for additional variables in multivariable analyses (OR = 0.76, p = .049). Conclusions: Although replication in larger studies is required, it appears that deficits in IQ/general cognitive functioning at first episode are associated with future treatment resistance. Cognitive variables may be able to provide further insight into neurodevelopmental factors associated with treatment resistance or act as early predictors of treatment resistance, which could allow prompt identification of refractory illness and timely interventions. Funding: This work was supported by a Stratified Medicine Programme grant to J.H.M from the Medical Research Council (grant number MR/L011794/1 which funded the research and supported S.E.S., A.F.P., R.M.M., J.T.R.W. & J.H.M.) E.M’s PhD is funded by the MRC-doctoral training partnership studentship in Biomedical Sciences at King’s College London. J.H.M, E.K, R.M.M are part funded by the National Institute for Health Research (NIHR) Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. A.P.K. is funded by the NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London. O.A. is further funded by an NIHR Post-Doctoral Fellowship (PDF2018-11-ST2-020). The views expressed are those of the authors and not necessarily those of the NHS, the MRC, the NIHR or the Department of Health. E.M.J. is supported by the UCL/UCLH Biomedical Research Centre. The AESOP (London, UK) cohort was funded by the UK Medical Research Council (Ref: G0500817). The Bologna (Italy) cohort was funded by the European Community’s Seventh Framework Program under grant agreement (agreement No. HEALTH-F2-2010–241909, Project EU-GEI). The GAP (London, UK) cohort was funded by the UK National Institute of Health Research (NIHR) Specialist Biomedical Research Centre for Mental Health, South London and Maudsley NHS Mental Health Foundation Trust (SLaM) and the Institute of Psychiatry, Psychology, and Neuroscience at King’s College London; Psychiatry Research Trust; Maudsley Charity Research Fund; and the European Community’s Seventh Framework Program grant (agreement No. HEALTH-F2-2009-241909, Project EU-GEI). The Oslo (Norway) cohort was funded by the Stiftelsen KG Jebsen, Research Council of Norway (#223273, under the Centers of Excellence funding scheme, and #300309, #283798) and the South-Eastern Norway Regional Health Authority (#2006233, #2006258, #2011085, #2014102, #2015088, #2017-112). The Paris (France) cohort was funded by European Community’s Seventh Framework Program grant (agreement No. HEALTHF2-2010–241909, Project EU-GEI). The Santander (Spain) cohort was funded by the following grants (to B.C.F): Instituto de Salud Carlos III, FIS 00/3095, PI020499, PI050427, PI060507, Plan Nacional de Drogas Research Grant 2005-Orden sco/3246/2004, and SENY Fundatio Research Grant CI 2005-0308007, Fundacion Marques de Valdecilla A/02/07 and API07/011. SAF2016-76046-R and SAF2013-46292-R (MINECO and FEDER). The West London (UK) cohort was funded The Wellcome Trust (Grant Numbers: 042025; 052247; 064607).

BackgroundTreatment-resistant schizophrenia (TRS) is associated with high levels of functional impairment, healthcare usage and societal costs. Cross-sectional studies may overestimate TRS rates because of selection bias.AimsWe aimed to quantify TRS rates by using first-episode cohorts to improve resource allocation and clozapine access.MethodWe undertook a systematic review of TRS rates among people with first-episode psychosis and schizophrenia, with a minimum follow-up of 8 weeks. We searched PubMed, PsycINFO, EMBASE, CINAHL and the Cochrane Database of Systematic Reviews, and meta-analysed TRS rates from included studies.ResultsTwelve studies were included, totalling 11 958 participants; six studies were of high quality. The rate of TRS was 22.8% (95% CI 19.1–27.0%, P < 0.001) among all first-episode cohorts and 24.4% (95% CI 19.5–30.0%, P < 0.001) among first-episode schizophrenia cohorts. Subgroup sensitivity analyses by location of recruitment, TRS definition, study quality, time of data collection and retrospective versus prospective data collection did not lead to statistically significant differences in heterogeneity. In a meta-regression, duration of follow-up and percentage drop-out did not significantly affect the overall TRS rate. Men were 1.57 times more likely to develop TRS than women (95% CI 1.11–2.21, P = 0.010).ConclusionsAlmost a quarter of people with first-episode psychosis or schizophrenia will develop TRS in the early stages of treatment. When including people with schizophrenia who relapse despite initial response and continuous treatment, rates of TRS may be as high as a third. These high rates of TRS highlight the need for improved access to clozapine and psychosocial supports.

The variability in the response to antipsychotic medication in schizophrenia may reflect between-patient differences in neurobiology. Recent cross-sectional neuroimaging studies suggest that a poorer therapeutic response is associated with relatively normal striatal dopamine synthesis capacity but elevated anterior cingulate cortex (ACC) glutamate levels. We sought to test whether these measures can differentiate patients with psychosis who are antipsychotic responsive from those who are antipsychotic nonresponsive in a multicenter cross-sectional study. 1H-magnetic resonance spectroscopy (1H-MRS) was used to measure glutamate levels (Glucorr) in the ACC and in the right striatum in 92 patients across 4 sites (48 responders [R] and 44 nonresponders [NR]). In 54 patients at 2 sites (25 R and 29 NR), we additionally acquired 3,4-dihydroxy-6-[18F]fluoro-l-phenylalanine (18F-DOPA) positron emission tomography (PET) to index striatal dopamine function (Kicer, min−1). The mean ACC Glucorr was higher in the NR than the R group after adjustment for age and sex (F1,80 = 4.27; P = .04). This was associated with an area under the curve for the group discrimination of 0.59. There were no group differences in striatal dopamine function or striatal Glucorr. The results provide partial further support for a role of ACC glutamate, but not striatal dopamine synthesis, in determining the nature of the response to antipsychotic medication. The low discriminative accuracy might be improved in groups with greater clinical separation or increased in future studies that focus on the antipsychotic response at an earlier stage of the disorder and integrate other candidate predictive biomarkers. Greater harmonization of multicenter PET and 1H-MRS may also improve sensitivity.

Treatment-resistant schizophrenia, affecting approximately 20–30% of patients with schizophrenia, has a high burden both for patients and healthcare services. There is a need to identify treatment resistance earlier in the course of the illness, in order that effective treatment, such as clozapine, can be offered promptly. We conducted a systemic literature review of prospective longitudinal studies with the aim of identifying predictors of treatment-resistant schizophrenia from the first episode. From the 545 results screened, we identified 12 published studies where data at the first episode was used to predict treatment resistance. Younger age of onset was the most consistent predictor of treatment resistance. We discuss the gaps in the literature and how future prediction models can identify predictors of treatment response more robustly.

Background Clozapine is the only effective medication for treatment-resistant schizophrenia; however, its mechanism of action remains unclear. The present study explored whether its effectiveness is related to changes in hematological measures after clozapine initiation. Methods Patients with treatment-resistant schizophrenia commenced on clozapine between January 2007 and December 2014 by the United Kingdom’s largest mental health trust were identified from electronic patient records. Hematological data from these patients were obtained from a monitoring registry. White blood cell, neutrophil, and platelet count were assessed at baseline and during the early phase of clozapine treatment. Clozapine response at 3 months was defined as “much,” or “very much” improved on the seven-point Clinical Global Impression—Improvement (CGI-I) subscale. Results In the total sample (n = 188), clozapine initiation was associated with a significant transient increase (peaking in weeks 3 to 4) in white blood cell, neutrophil, and platelet count (P < 0.001). There were 112 (59.6%) patients that responded to treatment; however, none of the hematological factors assessed at baseline, nor changes in these factors, were directly associated with treatment response. Implications Clozapine treatment is associated with transient hematological changes during the first month of treatment; however, there was no evidence that these were related to the therapeutic response.

BackgroundClozapine, an antipsychotic with unique efficacy in treatment-resistant psychosis, is associated with increased susceptibility to infection, including pneumonia.AimsTo investigate associations between clozapine treatment and increased risk of COVID-19 infection in patients with schizophrenia-spectrum disorders who are receiving antipsychotic medications in a geographically defined population in London, UK.MethodUsing information from South London and Maudsley NHS Foundation Trust (SLAM) clinical records, via the Clinical Record Interactive Search system, we identified 6309 individuals who had an ICD-10 diagnosis of schizophrenia-spectrum disorders and were taking antipsychotics at the time of the COVID-19 pandemic onset in the UK. People who were on clozapine treatment were compared with those on any other antipsychotic treatment for risk of contracting COVID-19 between 1 March and 18 May 2020. We tested associations between clozapine treatment and COVID-19 infection, adjusting for gender, age, ethnicity, body mass index (BMI), smoking status and SLAM service use.ResultsOf 6309 participants, 102 tested positive for COVID-19. Individuals who were on clozapine had increased risk of COVID-19 infection compared with those who were on other antipsychotic medication (unadjusted hazard ratio HR = 2.62, 95% CI 1.73–3.96), which was attenuated after adjusting for potential confounders, including clinical contact (adjusted HR = 1.76, 95% CI 1.14–2.72).ConclusionsThese findings provide support for the hypothesis that clozapine treatment is associated with an increased risk of COVID-19 infection. Further research will be needed in other samples to confirm this association. Potential clinical implications are discussed.

Background\ud Peripheral immune markers have previously been linked to a poor response to antipsychotic medication and more severe negative symptoms at the onset of psychosis. The present study investigated the association of blood cytokines and complement markers with the presence of antipsychotic non-response and symptom severity in patients with psychosis.\ud \ud Methods\ud This cross-sectional study recruited 94 patients with schizophrenia and other psychoses, of whom 47 were defined as antipsychotic responders and 47 as antipsychotic non-responders. In all subjects we measured plasma levels of cytokines (IL-1β, IL-2, IL-4, IL-6, IL-8, IL-10, IL-12p70, IL-13, TNF-α, and IFN-γ), complement markers (C1-inhibitor, C3, C4, C3a, C3b, Bb, factor D, C5a, terminal complement complex) and high sensitivity C-reactive protein (hsCRP). Symptom severity was recorded using the Positive and Negative Syndrome scale for Schizophrenia (PANSS). Binary logistic regression tested each immune marker as predictor of response status while covarying for relevant socio-demographic variables. Correlation analyses tested the association between immune markers and the severity of symptoms.\ud \ud Results\ud Interleukin (IL)-8 significantly predicted antipsychotic non-response (OR=24.70, 95% CI, 1.35–453.23, p = 0.03). Other immune markers were not associated with antipsychotic response. IL-6, IL-8, IL-10 and TNF-α significantly positively correlated with negative psychotic symptoms.\ud \ud Conclusions\ud Higher levels of IL-8 are associated with a poor response to antipsychotic treatment. Increased cytokines levels are specifically associated with more severe negative symptoms in patients with schizophrenia and other psychoses.

Background Sleep and circadian rhythm disturbances in schizophrenia are common, but incompletely characterized. We aimed to describe and compare the magnitude and heterogeneity of sleep-circadian alterations in remitted schizophrenia and compare them with those in interepisode bipolar disorder. Methods EMBASE, Medline, and PsycINFO were searched for case–control studies reporting actigraphic parameters in remitted schizophrenia or bipolar disorder. Standardized and absolute mean differences between patients and controls were quantified using Hedges’ g, and patient–control differences in variability were quantified using the mean-scaled coefficient of variation ratio (CVR). A wald-type test compared effect sizes between disorders. Results Thirty studies reporting on 967 patients and 803 controls were included. Compared with controls, both schizophrenia and bipolar groups had significantly longer total sleep time (mean difference [minutes] [95% confidence interval {CI}] = 99.9 [66.8, 133.1] and 31.1 [19.3, 42.9], respectively), time in bed (mean difference = 77.8 [13.7, 142.0] and 50.3 [20.3, 80.3]), but also greater sleep latency (16.5 [6.1, 27.0] and 2.6 [0.5, 4.6]) and reduced motor activity (standardized mean difference [95% CI] = −0.86 [−1.22, −0.51] and −0.75 [−1.20, −0.29]). Effect sizes were significantly greater in schizophrenia compared with the bipolar disorder group for total sleep time, sleep latency, and wake after sleep onset. CVR was significantly elevated in both diagnoses for total sleep time, time in bed, and relative amplitude. Conclusions In both disorders, longer overall sleep duration, but also disturbed initiation, continuity, and reduced motor activity were found. Common, modifiable factors may be associated with these sleep-circadian phenotypes and advocate for further development of transdiagnostic interventions that target them.

Introduction Little is known about predictors of clinical response to clozapine treatment in treatment-resistant psychosis. Most published cohorts are small, providing inconsistent results. We aimed to identify baseline clinical predictors of future clinical response in patients who initiate clozapine treatment, mainly focusing on the effect of age, duration of illness, baseline clinical symptoms and homelessness. Methodology Retrospective cohort of patients with treatment-resistant schizophrenia, aged between 15 and 60 years, that initiated clozapine between 2014 and 2017. Sociodemographic characteristics, years from illness diagnosis, and clinical presentation before the initiation of clozapine were collected and analyzed. All-cause discontinuation at two years follow-up was used as the primary measure of clozapine response. Results 261 patients were included with a median age at illness diagnosis of 23 years old (IQR 19-29) and a median age at clozapine initiation of 25 (IQR: 21–33). 72.33% (183/253) continued clozapine after two years follow-up. Being homeless was associated to higher clozapine non-adherence, with an OR of 2.78 (95%CI 1.051–7.38) (p = 0.039, controlled by gender). Older age at clozapine initiation and longer delay from first schizophrenia diagnosis to clozapine initiation were also associated with higher clozapine non-adherence, with each year increasing the odds of discontinuation by 1.043 (95%CI 1.02–1.07; p = 0.001) and OR 1.092 (95%CI 1.01–1.18;p = 0.032) respectively. Conclusion Starting clozapine in younger patients or shortly after schizophrenia diagnosis were associated with better adherence.

Clozapine is the only antipsychotic that is effective in treatment-resistant schizophrenia. However, in certain clinical situations, such as the emergence of serious adverse effects, it is necessary to discontinue clozapine. Stopping clozapine treatment poses a particular challenge due to the risk of psychotic relapse, as well as the development of withdrawal symptoms. Despite these challenges for the clinician, there is currently no formal guidance on how to safely to discontinue clozapine. We assessed the feasibility of developing evidence-based recommendations for (1) minimizing the risk of withdrawal symptoms, (2) managing withdrawal phenomena, and (3) commencing alternatives treatment when clozapine is discontinued. We then evaluated the recommendations against the Appraisal of Guidelines for Research and Evaluation (AGREE) II criteria. We produced 19 recommendations. The majority of these recommendation were evidence-based, although the strength of some recommendations was limited by a reliance of studies of medium to low quality. We discuss next steps in the refinement and validation of an evidence-based guideline for stopping clozapine and identify key outstanding questions.

Background:Clozapine is the only medication licenced for treating patients with treatment-refractory schizophrenia. However, there are no evidence-based guidelines as to the optimal plasma level of clozapine to aim for, and their association with clinical and functional outcome.Objective:We assessed the relationship between clinical and functional outcome measures and blood concentrations of clozapine among patients with treatment-refractory psychosis.Methods:Data were reviewed in 82 patients with treatment-refractory psychosis admitted to a specialised tertiary-level service and treated with clozapine. Analysis focussed on the relationship between clozapine and norclozapine plasma concentrations and the patient’s clinical symptoms and functional status.Results:Clinical symptom improvement was positively correlated with norclozapine plasma concentrations and inversely correlated with clozapine to norclozapine plasma concentrations ratio. Clozapine concentrations showed a bimodal association with clinical improvement (peaks around 350 and 660 ng/ml). Clinical symptom improvement correlated with functional outcomes, although there was no significant correlation between the latter and clozapine or norclozapine plasma concentrations.Conclusion:Clozapine treatment was associated with optimal clinical improvement at two different peak plasma concentrations around 350 and 650 ng/ml. Clinical improvement was associated with functional outcome; however, functionality was not directly associated with clozapine concentrations. A subset of patients may require higher clozapine plasma concentrations to achieve clinical improvement.

BackgroundDiscrepancies between the National Institute for Health and Care Excellence (NICE) schizophrenia guideline recommendations and current clinical practice in the UK have been reported.AimsWe aim to assess whether it is cost-effective to improve adherence to the NICE schizophrenia guideline recommendations, compared with current practice.MethodA previously developed whole-disease model for schizophrenia, using the discrete event simulation method, was adapted to assess the cost and health impacts of adherence to the NICE recommendations. Three scenarios to improve adherence to the clinical guidelines were modelled: universal provision of cognitive–behavioural therapy for patients at clinical high risk of psychosis, universal provision of family intervention for patients with first-episode psychosis and prompt provision of clozapine for patients with treatment-resistant schizophrenia. The primary outcomes were lifetime costs and quality-adjusted life-years gained.ResultsThe results suggest full adherence to the guideline recommendations would decrease cost and improve quality-adjusted life-years. Based on the NICE willingness-to-pay threshold of £20 000–£30 000 per quality-adjusted life-year gained, prompt provision of clozapine for patients with treatment-resistant schizophrenia results in the greatest net monetary benefit, followed by universal provision of cognitive–behavioural therapy for patients at clinical high risk of psychosis, and universal provision of family intervention for patients with first-episode psychosis.ConclusionsOur results suggest that adherence to guideline recommendations would decrease cost and improve quality-adjusted life-years. Greater investment is needed to improve guideline adherence and therefore improve patient quality of life and realise potential cost savings.

There has been much recent debate concerning the relative clinical utility of symptom dimensions versus conventional diagnostic categories in patients with psychosis. We investigated whether symptom dimensions rated at presentation for first-episode psychosis (FEP) better predicted time to first remission than categorical diagnosis over a four-year follow-up. The sample comprised 193 FEP patients aged 18-65. years who presented to psychiatric services in South London, UK, between 2006 and 2010. Psychopathology was assessed at baseline with the Positive and Negative Syndrome Scale and five symptom dimensions were derived using Wallwork/Fortgang's model; baseline diagnoses were grouped using DSM-IV codes. Time to start of first remission was ascertained from clinical records. The Bayesian Information Criterion (BIC) was used to find the best fitting accelerated failure time model of dimensions, diagnoses and time to first remission. Sixty percent of patients remitted over the four years following first presentation to psychiatric services, and the average time to start of first remission was 18.3. weeks (SD = 26.0, median = 8). The positive (BIC = 166.26), excited (BIC = 167.30) and disorganised/concrete (BIC = 168.77) symptom dimensions, and a diagnosis of schizophrenia (BIC = 166.91) predicted time to first remission. However, a combination of the DSM-IV diagnosis of schizophrenia with all five symptom dimensions led to the best fitting model (BIC = 164.35). Combining categorical diagnosis with symptom dimension scores in FEP patients improved the accuracy of predicting time to first remission. Thus our data suggest that the decision to consign symptom dimensions to an annexe in DSM-5 should be reconsidered at the earliest opportunity.

Background: neuropsychological investigations can help untangle the aetiological and phenomenological heterogeneity of schizophrenia but have scarcely been employed in the context of treatment-resistant (TR) schizophrenia. No population-based study has examined neuropsychological function in the first-episode of TR psychosis. Methods: we report baseline neuropsychological findings from a longitudinal, population-based study of first-episode psychosis, which followed up cases from index admission to 10 years. At the 10-year follow up patients were classified as treatment responsive or TR after reconstructing their entire case histories. Of 145 cases with neuropsychological data at baseline, 113 were classified as treatment responsive, and 32 as TR at the 10-year follow-up. Results: compared with 257 community controls, both case groups showed baseline deficits in three composite neuropsychological scores, derived from principal component analysis: verbal intelligence and fluency, visuospatial ability and executive function, and verbal memory and learning (p valuesâ 0.001). Compared with treatment responders, TR cases showed deficits in verbal intelligence and fluency, both in the extended psychosis sample (t =-2.32; p = 0.022) and in the schizophrenia diagnostic subgroup (t =-2.49; p = 0.017). Similar relative deficits in the TR cases emerged in sub-/sensitivity analyses excluding patients with delayed-onset treatment resistance (p values, Medical Research Council UK (MRC); National Institute for Health Research (NIHR); Wellcome Trust; European Union (European Union); Horizon 2020; European Community's Seventh Framework Program; Stanley Medical Research Institute

BackgroundCo-occurrence of common mental disorders (CMD) with psychotic experiences is well-known. There is little research on the public mental health relevance of concurrent psychotic experiences for service use, suicidality, and poor physical health. We aim to: (1) describe the distribution of psychotic experiences co-occurring with a range of non-psychotic psychiatric disorders [CMD, depressive episode, anxiety disorder, probable post-traumatic stress disorder (PTSD), and personality dysfunction], and (2) examine associations of concurrent psychotic experiences with secondary mental healthcare use, psychological treatment use for CMD, lifetime suicide attempts, and poor self-rated health.MethodsWe linked a prospective cross-sectional community health survey with a mental healthcare provider database. For each non-psychotic psychiatric disorder, patients with concurrent psychotic experiences were compared to those without psychotic experiences on use of secondary mental healthcare, psychological treatment for CMD, suicide attempt, physical functioning, and a composite multimorbidity score, using logistic regression and Cox regressions.ResultsIn all disorders except for anxiety disorder, concurrent psychotic experiences were accompanied by a greater odds of all outcomes (odds ratios) for a unit change in composite multimorbidity score ranged between 2.21 [95% confidence interval (CI) 1.49–3.27] and 3.46 (95% CI 1.52–7.85). Hazard ratios for secondary mental health service use for non-psychotic disorders with concurrent psychotic experiences, ranged from 0.53 (95% CI 0.15–1.86) for anxiety disorders with psychotic experiences to 4.99 (95% CI 1.22–20.44) among those with PTSD with psychotic experiences.ConclusionsCo-occurring psychotic experiences indicate greater public mental health burden, suggesting psychotic experiences could be a marker for future preventive strategies improving public mental health.

Clozapine is the only licensed pharmacotherapy for treatment-resistant schizophrenia. However, response to clozapine is variable. Understanding the demographic and clinical features associated with response to clozapine may be useful for patient stratification for clinical trials or for identifying patients for earlier initiation of clozapine. We systematically reviewed the literature to investigate clinical and demographic factors associated with variation in clozapine response in treatment-resistant patients with schizophrenia spectrum disorders. Subsequently, we performed a random-effects meta-analysis to evaluate differences in duration of illness, age at clozapine initiation, age of illness onset, body weight and years of education between clozapine responders and non-responders. Thirty-one articles were eligible for qualitative review and 17 of these were quantitatively reviewed. Shorter duration of illness, later illness onset, younger age at clozapine initiation, fewer hospitalisations and fewer antipsychotic trials prior to clozapine initiation showed a trend to be significantly associated with a better response to clozapine. Meta-analysis of seven studies, totalling 313 subjects, found that clozapine responders had a significantly shorter duration of illness compared to clozapine non-responders [g = 0.31; 95% confidence interval (CI) 0.06–0.56; p = 0.01]. The results imply that a delay in clozapine treatment may result in a poorer response and that a focus on prompt treatment with clozapine is warranted.

BackgroundSleep disruption is a common precursor to deterioration and relapse in people living with psychotic disorders. Understanding the temporal relationship between sleep and psychopathology is important for identifying and developing interventions which target key variables that contribute to relapse.MethodsWe used a purpose-built digital platform to sample self-reported sleep and psychopathology variables over 1 year, in 36 individuals with schizophrenia. Once-daily measures of sleep duration and sleep quality, and fluctuations in psychopathology (positive and negative affect, cognition and psychotic symptoms) were captured. We examined the temporal relationship between these variables using the Differential Time-Varying Effect (DTVEM) hybrid exploratory-confirmatory model.ResultsPoorer sleep quality and shorter sleep duration maximally predicted deterioration in psychosis symptoms over the subsequent 1–8 and 1–12 days, respectively. These relationships were also mediated by negative affect and cognitive symptoms. Psychopathology variables also predicted sleep quality, but not sleep duration, and the effect sizes were smaller and of shorter lag duration.ConclusionsReduced sleep duration and poorer sleep quality anticipate the exacerbation of psychotic symptoms by approximately 1–2 weeks, and negative affect and cognitive symptoms mediate this relationship. We also observed a reciprocal relationship that was of shorter duration and smaller magnitude. Sleep disturbance may play a causal role in symptom exacerbation and relapse, and represents an important and tractable target for intervention. It warrants greater attention as an early warning sign of deterioration, and low-burden, user-friendly digital tools may play a role in its early detection.

Background Treatment-resistant schizophrenia is a major disabling illness which often proves challenging to manage in a secondary care setting. The National Psychosis Unit (NPU) is a specialised tertiary in-patient facility that provides evidence-based, personalised, multidisciplinary interventions for complex treatment-resistant psychosis, in order to reduce the risk of readmission and long-term care costs. Aims This study aimed to assess the long-term effectiveness of treatment at the NPU by considering naturalistic outcome measures. Method Using a mirror image design, we compared the numbers of psychiatric and general hospital admissions, in-patient days, acuity of placement, number of psychotropic medications and dose of antipsychotic medication prescribed before and following NPU admission. Data were obtained from the Clinical Records Interactive Search system, an anonymised database sourced from the South London and Maudsley NHS Trust electronic records, and by means of anonymous linkage to the Hospital Episode Statistics system. Results Compared with the 2 years before NPU admission, patients had fewer mental health admissions (1.65 ± 1.44 v. 0.87 ± 0.99, z = 5.594, P < 0.0001) and less mental health bed usage (335.31 ± 272.67 v. 199.42 ± 261.96, z = 5.195 P < 0.0001) after NPU admission. Total in-patient days in physical health hospitals and total number of in-patient days were also significantly reduced (16.51 ± 85.77 v. 2.83 ± 17.38, z = 2.046, P = 0.0408; 351.82 ± 269.09 v. 202.25 ± 261.05, z = 5.621, P < 0.0001). The reduction in level of support required after treatment at the NPU was statistically significant (z = −8.099, P < 0.0001). Conclusions This study demonstrates the long-term effectiveness of a tertiary service specialising in treatment-resistant psychosis.

BackgroundCognitive impairments in childhood are associated with increased risk of schizophrenia in later life, but the extent to which poor academic achievement is associated with the disorder is unclear.MethodsMajor databases were searched for articles published in English up to 31 December 2019. We conducted random-effects meta-analyses to: (1) compare general academic and mathematics achievement in youth who later developed schizophrenia and those who did not; (2) to examine the association between education level achieved and adult-onset schizophrenia; and, (3) compare general academic achievement in youth at-risk for schizophrenia and typically developing peers. Meta-regression models examined the effects of type of academic assessment, educational system, age at assessment, measurement of educational level attained, school leaving age, and study quality on academic achievement and education level among individuals with schizophrenia.ResultsMeta-analyses, comprising data of over four million individuals, found that: (1) by age 16 years, those who later developed schizophrenia had poorer general academic (Cohen's d = −0.29, p ⩽ 0.0001) and mathematics achievement (d = −0.23, p = 0.01) than those who did not; (2) individuals with schizophrenia were less likely to enter higher education (odds ratio = 0.49, p ⩽ 0.0001); and, (3) youth reporting psychotic-like experiences and youth with a family history of schizophrenia had lower general academic achievement (d = −0.54, p ⩽ 0.0001; d = −0.39, p ⩽ 0.0001, respectively). Meta-regression analyses determined no effect modifiers.DiscussionDespite significant heterogeneity across studies, various routinely collected indices of academic achievement can identify premorbid cognitive dysfunction among individuals who are vulnerable for schizophrenia, potentially aiding the early identification of risk in the population.

BackgroundClozapine, an antipsychotic with unique efficacy in treatment resistant psychosis, is associated with increased susceptibility to infection, including pneumonia.AimsTo investigate associations between clozapine treatment and increased risk of COVID-19 in patients with schizophrenia-spectrum disorders who are receiving antipsychotic medications, using electronic health records data, in a geographically defined population in London.MethodUsing information from South London and Maudsley NHS Foundation Trust (SLAM) clinical records, via the Clinical Record Interactive Search system, we identified 6,309 individuals who had an ICD-10 diagnosis of schizophrenia-spectrum disorders and were taking antipsychotics at the time on the COVID-19 pandemic onset in the UK. People who were on clozapine treatment were compared with those on any other antipsychotic treatment for risk of contracting COVID-19 between 1 March and 18 May 2020. We tested associations between clozapine treatment and COVID-19 infection, adjusting for gender, age, ethnicity, BMI, smoking status, and SLAM service use.ResultsOf 6,309 patients, 102 tested positive for COVID-19. Individuals who were on clozapine had increased risk of COVID-19 compared with those who were on other antipsychotic medication (unadjusted HR = 2.62 (95% CI 1.73 - 3.96), which was attenuated after adjusting for potential confounders, including clinical contact (adjusted hazard ratio HR=1.76, 95% CI 1.14 - 2.72).ConclusionsThese findings provide support for the hypothesis that clozapine treatment is associated with an increased risk of COVID-19. Further research will be needed in other samples to confirm this association. Potential clinical implications are discussed.

ObjectivePsychosis - a complex and heterogeneous neuropsychiatric condition characterized by hallucinations and delusions - is a common feature of schizophrenia. There is evidence for altered DNA methylation (DNAm) associated with schizophrenia in both brain and peripheral tissues. We aimed to undertake a systematic analysis of variable DNAm associated with psychosis, schizophrenia, and treatment-resistant schizophrenia, also exploring measures of biological ageing, smoking, and blood cell composition derived from DNAm data to identify molecular biomarkers of disease.MethodsWe quantified DNAm across the genome in blood samples from 4,483 participants from seven case-control cohorts including patients with schizophrenia or first-episode psychosis. Measures of biological age, cellular composition and smoking status were derived from DNAm data using established algorithms. DNAm and derived measures were analyzed within each cohort and the results combined by meta-analysis.ResultsPsychosis cases were characterized by significant differences in measures of blood cell proportions and elevated smoking exposure derived from the DNAm data, with the largest differences seen in treatment-resistant schizophrenia patients. DNAm at 95 CpG sites was significantly different between psychosis cases and controls, with 1,048 differentially methylated positions (DMPs) identified between schizophrenia cases and controls. Schizophrenia-associated DMPs colocalize to regions identified in genetic association studies, with genes annotated to these sites enriched for pathways relevant to disease. Finally, a number of the schizophrenia associated differences were only present in the treatment-resistant schizophrenia subgroup.ConclusionsWe show that DNAm data can be leveraged to derive measures of blood cell counts and smoking that are strongly associated with psychosis. Our DNAm meta-analysis identified multiple DMPs associated with both psychosis and a more refined diagnosis of schizophrenia, with evidence for differential methylation associated with treatment-resistant schizophrenia that potentially reflects exposure to clozapine.

Schizophrenia is a severe mental illness affecting several domains of cognition and behaviour. The illness most frequently becomes manifest in early adulthood, and often follows a chronic course. It is associated with high morbidity and mortality, and is a leading contributor to disease burden, health and social care costs throughout the world. Antipsychotics are the mainstay of treatment but are limited by significant adverse effects, and therapeutic options for many patients remain inadequate. Schizophrenia is associated with a range of adverse physical health outcomes, which can be compounded by lifestyle factors including substance use, barriers in accessing healthcare and the adverse effects of treatment. Psychological and social interventions are a crucial element of patient care, particularly in alleviating negative symptoms. Current theories view schizophrenia as a disorder of early brain development, with interacting genetic and environmental risk factors.

BackgroundThere is growing interest in the potential for wearable and mobile devices to deliver clinically relevant information in real-world contexts. However, there is limited information on their acceptability and barriers to long-term use in people living with psychosis. ObjectiveThis study aimed to describe the development, implementation, feasibility, acceptability, and user experiences of the Sleepsight platform, which harnesses consumer wearable devices and smartphones for the passive and unobtrusive capture of sleep and rest-activity profiles in people with schizophrenia living in their homes. MethodsA total of 15 outpatients with a diagnosis of schizophrenia used a consumer wrist-worn device and smartphone to continuously and remotely gather rest-activity profiles over 2 months. Once-daily sleep and self-rated symptom diaries were also collected via a smartphone app. Adherence with the devices and smartphone app, end-of-study user experiences, and agreement between subjective and objective sleep measures were analyzed. Thresholds for acceptability were set at a wear time or diary response rate of 70% or greater. ResultsOverall, 14 out of 15 participants completed the study. In individuals with a mild to moderate symptom severity at baseline (mean total Positive and Negative Syndrome Scale score 58.4 [SD 14.4]), we demonstrated high rates of engagement with the wearable device (all participants meeting acceptability criteria), sleep diary, and symptom diary (93% and 86% meeting criteria, respectively), with negative symptoms being associated with lower diary completion rate. The end-of-study usability and acceptability questionnaire and qualitative analysis identified facilitators and barriers to long-term use, and paranoia with study devices was not a significant barrier to engagement. Comparison between sleep diary and wearable estimated sleep times showed good correspondence (ρ=0.50, P

BACKGROUND: Neuropsychological investigations can help untangle the aetiological and phenomenological heterogeneity of schizophrenia but have scarcely been employed in the context of treatment-resistant (TR) schizophrenia. No population-based study has examined neuropsychological function in the first-episode of TR psychosis. METHODS: We report baseline neuropsychological findings from a longitudinal, population-based study of first-episode psychosis, which followed up cases from index admission to 10 years. At the 10-year follow up patients were classified as treatment responsive or TR after reconstructing their entire case histories. Of 145 cases with neuropsychological data at baseline, 113 were classified as treatment responsive, and 32 as TR at the 10-year follow-up. RESULTS: Compared with 257 community controls, both case groups showed baseline deficits in three composite neuropsychological scores, derived from principal component analysis: verbal intelligence and fluency, visuospatial ability and executive function, and verbal memory and learning (p values⩽0.001). Compared with treatment responders, TR cases showed deficits in verbal intelligence and fluency, both in the extended psychosis sample (t = -2.32; p = 0.022) and in the schizophrenia diagnostic subgroup (t = -2.49; p = 0.017). Similar relative deficits in the TR cases emerged in sub-/sensitivity analyses excluding patients with delayed-onset treatment resistance (p values

BACKGROUND: Within clinical services, there can be a delay of years before patients with psychosis, who do not respond to antipsychotic medication, receive a diagnosis of treatment resistant schizophrenia (TRS). There is a need to identify these patients earlier within the course of their illness and expedite their access to specialist treatment. The aim of this project was to use data, available when patients first present to clinical services, to predict TRS. METHODS: We used existing prospective first-episode psychosis studies from across Europe (STRATA-G Consortium; N=2274, TRS=370 (16.27%)) and tested two statistical models: the first to find associations with TRS and the second to identify predictors of TRS. After using existing literature to perform variable selection, we ran a logistic regression to identify variables associated with TRS within our sample. We included all variables within a ‘Least Absolute Shrinkage and regression Operator’ (LASSO) logistic regression, tuned by bootstrapping to identify predictors of TRS. We report the LASSO predictive model that corresponds to the penalty which returns the area under the curve (AUC) within one standard error (1SE) of the maximum AUC. Internal validation of the LASSO model performance was run via bootstrap optimism-correction. RESULTS: In our multivariable logistic regression model, younger age of onset and less years in education were significantly associated with the odds of being TRS. The predictive model selected younger age of onset, less years in education, basic education vs. higher education, presence of a lifetime relationship vs. absence of a lifetime relationship, smoking vs. not smoking, poorer functioning measured using the Global Assessment of Functioning (GAF), and mode of onset between one and six months vs. longer than six months, as predictors of TRS. For a risk threshold of 50%, the AUC was 0.776 and the model had an accuracy of 83.9% (95% confidence interval: 82.3%, 85.4%). The sensitivity (correct identification of TRS) was 2.70%, with a positive predictive value of 58.82%, and the specificity (correct identification of responders) was 99.63% with a negative predictive value 84.05%. DISCUSSION: Our logistic regression model replicated previously published work on factors associated with TRS. Our prediction model performed well, but, due to the small proportion of TRS cases in our sample, was more accurate at identifying responders than patients with TRS. The predictors selected by our model highlight new areas in which to investigate the aetiology of TRS. We have also emphasised the difference between statistical models designed to test associations and those designed to predict outcomes.

BACKGROUND: Although the association between psychotic illness and cigarette smoking is well known, it is not clear why people with psychosis are more likely to smoke than are the general population. First, we carried out a systematic review and meta-analysis aimed to test the hypothesis that a) daily tobacco use is associated with an increased risk of psychotic illness in both case-control and prospective studies, and b) smoking is associated with an earlier age at onset of psychotic illness. Secondly, we carried out two case-control studies aimed to derive an estimate of the prevalence of smoking in patients presenting with their first episode of psychosis. The first was the GAP study carried out in South London, the second was the EU-GEI multi-site study carried out across 16 sites in Europe and Brazil. METHODS: First, we searched Embase, Medline, and PsycINFO and selected observational studies in which rates of smoking were reported in people with psychotic disorders, compared with controls. We calculated the weighted mean difference for age at onset of psychosis and age at initiation of smoking. For categorical outcomes, we calculated odds ratios from cross-sectional studies and risk ratios from prospective studies. Secondly, in the GAP study, we interviewed 596 people with their first episode of psychosis and 333 healthy controls representative of the local population. In the EU-GEI study, we interviewed 1,150 patients with first episode psychosis and 1,350 healthy controls. In both all subjects were interviewed in detail about their recreational drug use including tobacco use. In the EU-GEI study approximately one half of the cases and controls also underwent an EWAS examination of epigenetics in peripheral blood. RESULTS: 61 studies met inclusion criteria for the systematic review, and the overall sample included 14,555 tobacco users and 273,162 non-users. The prevalence of smoking in patients presenting with their first episode of psychosis was 0·57 (95% CI 0·52-0·62; p

Background Little is known about patients with a first episode of psychosis (FEP) who had first presented to prodromal services with an “at risk mental state” (ARMS) before making the transition to psychosis. We set out to identify the proportion of patients with a FEP who had first presented to prodromal services in the ARMS state, and to compare these FEP patients with FEP patients who did not have prior contact with prodromal services. Methods In this study information on 338 patients aged ≤37 years who presented to mental health services between 2010 and 2012 with a FEP was examined. The data on pathways to care, clinical and socio-demographic characteristics were extracted from the Biomedical Research Council Case Register for the South London and Maudsley NHS Trust. Results Over 2 years, 14 (4.1% of n = 338) young adults presented with FEP and had been seen previously by the prodromal services. These ARMS patients were more likely to enter their pathway to psychiatric care via referral from General Practice, be born in the UK and to have had an insidious mode of illness onset than FEP patients without prior contact with the prodromal services. Conclusions In the current pathways to care configuration, prodromal services are likely to prevent only a few at-risk individuals from transitioning to psychosis even if effective preventative treatments become available. Electronic supplementary material The online version of this article (doi:10.1186/s12888-017-1468-y) contains supplementary material, which is available to authorized users.

BackgroundThe association between cigarette smoking and psychosis remains unexplained, but could relate to causal effects in both directions, confounding by socioeconomic factors, such as ethnicity, or use of other substances, including cannabis. Few studies have evaluated the association between cigarettes and psychotic experiences (PEs) in diverse, inner-city populations, or relationships with number of cigarettes consumed.MethodsWe assessed associations and dose–response relationships between cigarette smoking and PEs in a cross-sectional survey of household residents (n= 1680) in South East London, using logistic regression to adjust for cannabis use, other illicit substances, and socioeconomic factors, including ethnicity.ResultsWe found association between any PEs and daily cigarette smoking, which remained following adjustment for age, gender, ethnicity, cannabis and use of illicit stimulant drugs (fully adjusted odds ratio 1.47, 95% confidence interval 1.01–2.15). Fully adjusted estimates for the association, and with number of PEs, increased with number of cigarettes smoked daily, implying a dose–response effect (p= 0.001 and ConclusionsIn this diverse epidemiological sample, association between smoking and PEs was not explained by confounders such as cannabis or illicit drugs. Daily cigarette consumption showed a dose–response relationship with the odds of reporting PEs, and of reporting a greater number of PEs. There was no difference in odds of reporting PEs between ex-smokers and never-smokers, raising the possibility that the increase in PEs associated with smoking may be reversible.

Both substance use and poor medication adherence are associated with poor outcome in psychosis. To clarify the contributions of substance use and poor medication adherence to poor outcome in the year following a first episode of psychosis, 205 patients were evaluated for use of tobacco, alcohol, cannabis and stimulants at their psychosis onset, and in a 1-year follow-up. Data on medication adherence and symptom remission were also collected. Patients had high rates of overall substance use before (37-65%) and after psychosis onset (45-66%). 44% showed poor medication adherence and 55% did not reach remission from psychosis. Nicotine dependence and cannabis use after psychosis onset significantly predicted both poor medication adherence and non-remission, and poor medication adherence mediated the effects of these substances on non-remission. In conclusion, medication adherence lies on the causal pathway between nicotine dependence and cannabis on the one hand and non-remission on the other.

Key Points Question Which interventions are cost-effective for the prevention and treatment of schizophrenia? Findings In this decision analytical model using a simulated cohort of 200 000 individuals, the following interventions were found to be cost-effective: practice as usual plus cognitive behavioral therapy for individuals at clinical high risk of psychosis; a mix of hospital admission and crisis resolution and home treatment team for individuals with acute psychosis; receipt of amisulpride, risperidone, or olanzapine combined with family intervention for individuals with first-episode psychosis; and receipt of clozapine for individuals with treatment-resistant schizophrenia. Meaning The results of this study suggest that cost savings and/or additional quality-adjusted life years may be gained by replacing current interventions with more cost-effective interventions., This decision analytical model develops a whole-disease model for schizophrenia and uses it to inform resource allocation decisions across the entire care pathway for schizophrenia in the UK., Importance The existing economic models for schizophrenia often have 3 limitations; namely, they do not cover nonpharmacologic interventions, they report inconsistent conclusions for antipsychotics, and they have poor methodologic quality. Objectives To develop a whole-disease model for schizophrenia and use it to inform resource allocation decisions across the entire care pathway for schizophrenia in the UK. Design, Setting, and Participants This decision analytical model used a whole-disease model to simulate the entire disease and treatment pathway among a simulated cohort of 200 000 individuals at clinical high risk of psychoses or with a diagnosis of psychosis or schizophrenia being treated in primary, secondary, and tertiary care in the UK. Data were collected March 2016 to December 2018 and analyzed December 2018 to April 2019. Exposures The whole-disease model used discrete event simulation; its structure and input data were informed by published literature and expert opinion. Analyses were conducted from the perspective of the National Health Service and Personal Social Services over a lifetime horizon. Key interventions assessed included cognitive behavioral therapy, antipsychotic medication, family intervention, inpatient care, and crisis resolution and home treatment team. Main Outcomes and Measures Life-time costs and quality-adjusted life-years. Results In the simulated cohort of 200 000 individuals (mean [SD] age, 23.5 [5.1] years; 120 800 [60.4%] men), 66 400 (33.2%) were not at risk of psychosis, 69 800 (34.9%) were at clinical high risk of psychosis, and 63 800 (31.9%) had psychosis. The results of the whole-disease model suggest the following interventions are likely to be cost-effective at a willingness-to-pay threshold of £20 000 ($25 552) per quality-adjusted life-year: practice as usual plus cognitive behavioral therapy for individuals at clinical high risk of psychosis (probability vs practice as usual alone, 0.96); a mix of hospital admission and crisis resolution and home treatment team for individuals with acute psychosis (probability vs hospital admission alone, 0.99); amisulpride (probability vs all other antipsychotics, 0.39), risperidone (probability vs all other antipsychotics, 0.30), or olanzapine (probability vs all other antipsychotics, 0.17) combined with family intervention for individuals with first-episode psychosis (probability vs family intervention or medication alone, 0.58); and clozapine for individuals with treatment-resistant schizophrenia (probability vs other medications, 0.81). Conclusions and Relevance The results of this study suggest that the current schizophrenia service configuration is not optimal. Cost savings and/or additional quality-adjusted life-years may be gained by replacing current interventions with more cost-effective interventions.

Background Clozapine is the only medication approved for those patients with schizophrenia who do not achieve a clinical response to standard antipsychotic treatment, yet it is still underused. Furthermore, in the case of a partial or minimal response to clozapine treatment, there is no clarity on the next pharmacologic intervention. Methods The National Psychosis Service is a tertiary referral inpatient unit for individuals with refractory psychosis. Data from 2 pooled data sets (for a total of 325 medical records) were analyzed for treatment trajectories between admission and discharge (2001-2016). Effectiveness of pharmacologic treatment was determined using change in symptoms, assessed using the Operational Criteria (OPCRIT) system applied retrospectively to the medical records. Analysis was focused on identifying the optimal medication regimens impacting clinical status during the admission. Results Less than a quarter of the patients were on clozapine treatment at the time of admission; this rate increased to 63.4% at the time of discharge. Initiating clozapine during admission (n = 136) was associated with a 47.9% reduction of symptoms as reflected by their OPCRIT score. In cases in which clozapine monotherapy did not achieve sufficient improvement in symptoms, the most effective clozapine augmentation strategy was adding amisulpride (n = 22, 60.8% reduction of symptoms), followed by adding a mood stabilizer (n = 36, 53.7% reduction). A less favorable option was addition of quetiapine (n = 15, 26.7% reduction). Conclusions Many people with longer-term and complex refractory illness do respond to clozapine treatment with suitable augmentation strategies when necessary. Furthermore, it is possible to advance clozapine prescribing in these complex patients when they are supported by a skilled and dedicated multidisciplinary team. The optimal therapeutic approach relies on confirmation of diagnosis and compliance and optimization of clozapine dose using therapeutic drug monitoring, followed by augmentation of clozapine with amisulpride or mood stabilizers. There is some preliminary evidence suggesting that augmentation strategies may impact differentially depending on the symptom profile.

© Cambridge University Press 2018Â This is an Open Access article, distributed under the terms of the Creative Commons Attribution licence (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted re-use, distribution, and reproduction in any medium, provided the original work is properly cited. © Cambridge University Press 2018. Background Neuropsychological investigations can help untangle the aetiological and phenomenological heterogeneity of schizophrenia but have scarcely been employed in the context of treatment-resistant (TR) schizophrenia. No population-based study has examined neuropsychological function in the first-episode of TR psychosis.Methods We report baseline neuropsychological findings from a longitudinal, population-based study of first-episode psychosis, which followed up cases from index admission to 10 years. At the 10-year follow up patients were classified as treatment responsive or TR after reconstructing their entire case histories. Of 145 cases with neuropsychological data at baseline, 113 were classified as treatment responsive, and 32 as TR at the 10-year follow-up.Results Compared with 257 community controls, both case groups showed baseline deficits in three composite neuropsychological scores, derived from principal component analysis: verbal intelligence and fluency, visuospatial ability and executive function, and verbal memory and learning (p valuesâ 0.001). Compared with treatment responders, TR cases showed deficits in verbal intelligence and fluency, both in the extended psychosis sample (t =-2.32; p = 0.022) and in the schizophrenia diagnostic subgroup (t =-2.49; p = 0.017). Similar relative deficits in the TR cases emerged in sub-/sensitivity analyses excluding patients with delayed-onset treatment resistance (p values

Daily smoking has been associated with a greater risk of psychosis. However, we are still lacking studies to adjust for baseline psychotic experiences and other substance use. We examined associations between daily smoking and psychosis risk in a 15-year follow-up while accounting for these covariates in a prospective sample (N = 6081) from the Northern Finland Birth Cohort 1986.Self-report questionnaires on psychotic experiences (PROD-screen), tobacco smoking and other substance use were completed when the cohort members were 15-16 years old. Tobacco smoking was categorized into three groups (non-smokers, 1-9 cigarettes and ≥10 cigarettes/day). Psychosis diagnoses were obtained from national registers until the age of 30 years.Subjects in heaviest smoking category were at increased risk of subsequent psychosis (unadjusted HR = 3.15; 95% CI 1.94-5.13). When adjusted for baseline psychotic experiences the association persisted (HR = 2.87; 1.76-4.68) and remained significant even after adjustments for multiple known risk factors such as cannabis use, frequent alcohol use, other illicit substance use, parental substance abuse, and psychosis. Furthermore, number of smoked cigarettes increased psychosis risk in a dose-response manner (adjusted OR = 1.05; 1.01-1.08).Heavy tobacco smoking in adolescence was associated with a greater risk for psychosis even after adjustment for confounders.

BackgroundClozapine remains the only evidence-based antipsychotic for treatment-resistant schizophrenia (TRS). The ability to predict which patients with their first onset of schizophrenia would subsequently meet criteria for treatment resistance (TR) could help to diminish the severe functional disability which may ensue if TR is not recognized and correctly treated.MethodThis is a 5-year longitudinal assessment of clinical outcomes in a cohort of 246 first-episode schizophrenia spectrum patients recruited as part of the NIHR Genetics and Psychosis (GAP) study conducted in South London from 2005 to 2010. We examined the relationship between baseline demographic and clinical measures and the emergence of TR. TR status was determined from a review of electronic case records. We assessed for associations with early-, and late-onset TR, and non-TR, and differences between those TR patients treated with clozapine and those who were not.ResultsSeventy per cent (n= 56) of TR patients, and 23% of the total study population (n= 246) were treatment resistant from illness onset. Those who met criteria for TR during the first 5 years of illness were more likely to have an early age of first contact for psychosis (ConclusionsFor the majority of the TR group, antipsychotic TR is present from illness onset, necessitating increased consideration for the earlier use of clozapine.

SleepSight is a novel approach to detecting early signs of relapse in psychosis, thereby allowing targeted intervention for relapse prevention. The system uses a wireless-enabled wearable device and smartphone to collect longitudinal accelerometry, heart-rate, ambient light and smartphone usage patterns from patients living in their homes. These data are encrypted and sent via the mobile data network to a secure server for real-Time analysis, using the Purple Robot mobile application. This study tested feasibility and acceptability of the SleepSight system in 15 participants with a diagnosis of schizophrenia. Patient recruitment and data collection was completed in January 2016, at the South London and Maudsley NHS Foundation Trust (SLaM), the largest mental health service provider in the EU. The project is a unique multidisciplinary collaboration between the NIHR Biomedical Research Centre for Mental Health, the Institute of Psychiatry, Psychology and Neuroscience, and the National Health Service.

Cigarette smoking is strongly associated with psychotic disorders such as schizophrenia. For several decades it was assumed that the relationship could be explained by reverse causation; that smoking was secondary to the illness itself, either through self-medication or a process of institutionalization, or was entirely explained by confounding by cannabis use or social factors. However, studies have exposed that such hypotheses cannot fully explain the association, and more recently a bidirectional relationship has been proposed wherein cigarette smoking may be causally related to risk of psychosis, possibly via a shared genetic liability to smoking and psychosis. We review the evidence for these candidate explanations, using findings from the latest epidemiological, neuroimaging, genetic and preclinical work.