Search

Clozapine, an antipsychotic, is associated with increased susceptibility to infection with COVID-19, compared to other antipsychotics. Here, we investigate associations between clozapine treatment and increased risk of adverse outcomes of COVID-19, namely COVID-related hospitalisation, intensive care treatment, and death, among patients taking antipsychotics with schizophrenia-spectrum disorders. Using the clinical records of South London and Maudsley NHS Foundation Trust, we identified 157 individuals who had an ICD-10 diagnosis of schizophrenia-spectrum disorders, were taking antipsychotics (clozapine or other antipsychotics) at the time of COVID-19 pandemic in the UK and had a laboratory-confirmed COVID-19 infection. The following health outcomes were measured: COVID-related hospitalisation, COVID-related intensive care treatment and death. We tested associations between clozapine treatment and each outcome using logistic regression models, adjusting for gender, age, ethnicity, neighbourhood deprivation, obesity, smoking status, diabetes, asthma, bronchitis and hypertension using propensity scores. Of the 157 individuals who developed COVID-19 while on antipsychotics (clozapine or other antipsychotics), there were 28% COVID-related hospitalisations, 8% COVID-related intensive care treatments and 8% deaths of any cause during the 28 days follow-up period. Among those taking clozapine, there were 25% COVID-related hospitalisations, 7% COVID-related intensive care treatments and 7% deaths. In both unadjusted and adjusted analyses, we found no significant association between clozapine and any of the outcomes. Thus, we found no evidence that patients with clozapine treatment at time of COVID-19 infection had increased risk of hospitalisation, intensive care treatment or death, compared to non-clozapine antipsychotic-treated patients. However, further research should be considered in larger samples to confirm this.•schizophrenia•clozapine•Antipsychotic agents•COVID-19•SARS-CoV-2

Background: A proportion of people with treatment-resistant schizophrenia fail to show improvement on clozapine treatment. Knowledge of the sociodemographic and clinical factors predicting clozapine response may be useful in developing personalised approaches to treatment. Methods: This retrospective cohort study used data from the electronic health records of the South London and Maudsley (SLaM) hospital between 2007 and 2011. Using the Least Absolute Shrinkage and Selection Operator (LASSO) regression statistical learning approach, we examined 35 sociodemographic and clinical factors’ predictive ability of response to clozapine at 3 months of treatment. Response was assessed by the level of change in the severity of the symptoms using the Clinical Global Impression (CGI) scale. Results: We identified 242 service-users with a treatment-resistant psychotic disorder who had their first trial of clozapine and continued the treatment for at least 3 months. The LASSO regression identified three predictors of response to clozapine: higher severity of illness at baseline, female gender and having a comorbid mood disorder. These factors are estimated to explain 18% of the variance in clozapine response. The model’s optimism-corrected calibration slope was 1.37, suggesting that the model will underfit when applied to new data. Conclusions: These findings suggest that women, people with a comorbid mood disorder and those who are most ill at baseline respond better to clozapine. However, the accuracy of the internally validated and recalibrated model was low. Therefore, future research should indicate whether a prediction model developed by including routinely collected data, in combination with biological information, presents adequate predictive ability to be applied in clinical settings.

The filamentous and unicellular algae of the class Zygnematophyceae are the closest algal relatives of land plants. Inferring the properties of the last common ancestor shared by these algae and land plants allows us to identify decisive traits that enabled the conquest of land by plants. We sequenced four genomes of filamentous Zygnematophyceae (three strains ofZygnema circumcarinatumand one strain ofZ. cylindricum) and generated chromosome-scale assemblies for all strains of the emerging model systemZ. circumcarinatum. Comparative genomic analyses reveal expanded genes for signaling cascades, environmental response, and intracellular trafficking that we associate with multicellularity. Gene family analyses suggest that Zygnematophyceae share all the major enzymes with land plants for cell wall polysaccharide synthesis, degradation, and modifications; most of the enzymes for cell wall innovations, especially for polysaccharide backbone synthesis, were gained more than 700 million years ago. In Zygnematophyceae, these enzyme families expanded, forming co-expressed modules. Transcriptomic profiling of over 19 growth conditions combined with co-expression network analyses uncover cohorts of genes that unite environmental signaling with multicellular developmental programs. Our data shed light on a molecular chassis that balances environmental response and growth modulation across more than 600 million years of streptophyte evolution.HIGHLIGHTSGenomes of four filamentous algae (Zygnema) sisters to land plantsZygnemaare rich in genes for multicellular growth and environmental acclimation: signaling, lipid modification, and transportCell wall innovations: diversification of hexameric rosette cellulose synthase in ZygnematophyceaeCo-expression networks reveal conserved modules for balancing growth and acclimation

Despite associations between alcohol use and suicidal acts, little research measures prognoses of alcohol-using patients treated by Crisis Resolution Teams (CRTs), an intensive community-based intervention. We estimated the association of alcohol use amongst patients accepted following suicidal acts or ideation in four London-based Crisis Resolution Teams, with death-by-any-cause or recontact with crisis care. We analysed the electronic health records of 1615 CRT patients accepted following suicidal acts or ideation over 38 months, following STROBE guidelines. Using logistic regression we estimated the association of alcohol use (indicated by risk-assessment, AUDIT, or ICD-10 diagnosis) with death-or-recontact at (i) 30-days and (ii) 1-year after treatment start, adjusted for age, sex, ethnicity, psychiatric diagnosis, and severity of need. Hazardous, harmful, or dependent drinking was identified in 270 cases at baseline (16.7%); 73 (4.5%) were alcohol dependent. By 1-year, 622 patients (38.5%) had recontacted crisis care or died. After adjustment, alcohol use at a hazardous, harmful, or dependent level was not associated with increased odds of death-or-recontact at 30-days (AOR 1.17, 95%CI 0.73, 1.88) or 1-year (AOR 1.17, 95%CI 0.85, 1.60). Patients with hazardous, harmful, and dependent alcohol use are a small proportion of CRT patients, despite being more commonly encountered in emergency settings from which patients may be referred to CRTs, indicating a potential gap in provision. Those who are included in CRTs are not at increased risk of death-or-recontact within 1 year of treatment, suggesting that their inclusion can work, at least in a sample with predominantly hazardous or harmful alcohol use.

Objective: Although frequently reported in psychosis, obsessive-compulsive symptoms (OCS) are often not recognized and thus undertreated. We aimed to estimate the prevalence of OCS and obsessive-compulsive disorder (OCD) in patients with schizophrenia, schizoaffective disorder, or bipolar disorder in clinical records and identify clinical associations of OCS co-occurrence. Methods: Data were retrieved from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre case register. The study population was restricted to individuals diagnosed with schizophrenia (ICD F20.x), schizoaffective disorder (ICD F25.x), or bipolar disorder (ICD F31.x) between 2007 and 2015. OCS and OCD were ascertained from structural fields and via Natural Language Processing software applied to free-text records. Clinical characteristics were obtained from Health of the Nation Outcome Scales for the analyses on associations between clinical characteristics and OCS/OCD status using logistic regressions with confounders considered. Results: 22,551 cases of schizophrenia, schizoaffective disorder, or bipolar disorder were identified in the observation window. Among these, 5,179 (24.0%) were identified as having OCS (including an OCD diagnosis) and 2,574 (11.9%) specifically with comorbid OCD. OCS/OCD was associated with an increased likelihood of recorded aggressive behavior (OR = 1.18; 95% CI, 1.10-1.26), cognitive problems (OR = 1.21; 95% CI, 1.13-1.30), hallucinations and delusions (OR = 1.11; 95% CI, 1.04-1.20), and physical problems (OR = 1.17; 95% CI, 1.09-1.26). Conclusions: OCS and OCD are frequently recorded for patients with schizophrenia, schizoaffective disorder, and bipolar disorder and are associated with more severe psychiatric clinical characteristics. Automated information extraction tools hold potential to improve recognition and treatment of co-occurring OCS/OCD for psychosis.

BackgroundStudies show ethnic inequalities in rates of involuntary admission and types of clinical care (such as psychological therapies). However, few studies have investigated if there is a relationship between clinical care practices and ethnic inequalities in involuntary admission.AimsThis study investigated the impact of ethnicity and clinical care on involuntary admission and the potential mediation effects of prior clinical care.MethodIn this retrospective cohort study, we used data from the electronic records of the South London and Maudsley NHS Foundation Trust and identified patients with a first hospital admission between January 2008 and May 2021. Logistic regression and mediation analyses were used to investigate the association between ethnicity and involuntary admission, and whether clinical care, in the 12 months preceding admission, mediates the association.ResultsCompared with White British people, higher odds of involuntary admission were observed among 10 of 14 minority ethnic groups; with more than twice the odds observed among people of Asian Chinese, of Asian Bangladeshi and of any Black background. There were some ethnic differences in clinical care prior to admission, but these had a minimal impact on the inequalities in involuntary admission. More out-patient appointments and home treatment were associated with higher odds of involuntary admission, whereas psychological therapies and having a care plan were associated with reduced odds of involuntary admission.ConclusionsEthnic inequalities in involuntary admission persist after accounting for potential mediating effects of several types and frequencies of clinical care. Promoting access to psychological therapies and ensuring that care plans are in place may reduce involuntary admissions.

Background: There is evidence of heterogeneity within treatment-resistant schizophrenia (TRS), with some people not responding to antipsychotic treatment from illness onset and others becoming treatment-resistant after an initial response period. These groups may have different aetiologies. Aim: This study investigates sociodemographic and clinical correlates of early onset of TRS. Method: Employing a retrospective cohort design, we do a secondary analysis of data from a cohort of people with TRS attending the South London and Maudsley. Regression analyses were conducted to identify the correlates of the length of treatment to TRS. Predictors included the following: gender, age, ethnicity, problems with positive symptoms, problems with activities of daily living, psychiatric comorbidities, involuntary hospitalisation and treatment with long-acting injectable antipsychotics. Results: In a cohort of 164 people with TRS (60% were men), the median length of treatment to TRS was 3 years and 8 months. We observed no cut-off on the length of treatment until TRS presentation differentiating between early and late TRS (i.e. no bimodal distribution). Having mild to very severe problems with hallucinations and delusions at the treatment start was associated with earlier TRS (~19 months earlier). In sensitivity analyses, including only complete cases (subject to selection bias), treatment with a long-acting injectable antipsychotic was additionally associated with later TRS (~15 months later). Conclusion: Our findings do not support a clear separation between early and late TRS but rather a continuum of the length of treatment before TRS onset. Having mild to very severe problems with positive symptoms at treatment start predicts earlier onset of TRS.

Clozapine is the only licenced medication for treating treatment-resistant schizophrenia. Previous studies have suggested unequal rates of clozapine treatment by ethnicity among individuals with schizophrenia-spectrum disorders. One previous review has investigated this topic but was restricted to studies from the USA. This current review aims to synthesise the international literature regarding ethnic disparities in clozapine prescription amongst individuals with schizophrenia-spectrum disorders. We searched CINAHL, PubMed, Medline, Embase, APA PsycINFO and Open Grey and reviewed studies reporting on the proportion of service-users prescribed clozapine separately for different ethnic groups, in individuals with a primary diagnosis of schizophrenia or any schizophrenia-spectrum disorders. A narrative synthesis was conducted to integrate information from included studies. The review was registered in PROSPERO (Number: CRD42020221731). From 24 studies, there is strong, consistent evidence that Black and Hispanic service-users in the UK and the USA are significantly less likely to receive clozapine than White/Caucasian service-users after controlling for multiple demographic and clinical potential confounders. In New Zealand, Māori service-users were reported to be more likely to receive clozapine than those of White/European ethnicity. There is mixed evidence regarding Asian service-users in the UK. The mentioned disparities were observed in studies with TRS and non-TRS cohorts. The results imply that access to clozapine treatment varies among ethnic groups. These findings raise an ethical concern as they suggest a compromise of the standards of care in schizophrenia treatment practices. Interventions are needed to reduce clozapine prescribing disparities among ethnic communities.

Background Since the recent conflicts in Iraq and Afghanistan, the short-term focus of military healthcare research has been on the consequences of deployment for mental health and on those wounded or injured in combat. Now that these conflicts have ended for the UK Armed Forces, it is important to consider the longer term physical and mental health consequences, and just as importantly, the links between these. The aims of this study were to determine the most common physical conditions requiring a hospital admission in UK military personnel and whether they were more common in personnel with a mental health condition, smokers, and/or those misusing alcohol compared to those without. Methods Data linkage of a prospective UK military cohort study to electronic admitted patient care records for England, Wales and Scotland. Nine thousand nine hundred ninety military personnel completed phase 2 of a military cohort study (56% response rate, data collected from 2007 to 2009), with analyses restricted to 86% of whom provided consent for linkage to healthcare records (n = 8602). Ninety percent were male and the mean age at phase 2 was 36 years. The outcome was physical non communicable diseases (NCDs) requiring a hospital admission which occurred after phase 2 of the cohort when the mental health, smoking and alcohol use exposure variables had been assessed until the end of March 2014. Results The most common NCDs requiring a hospital admission were gastrointestinal disorders 5.62% (95% Confidence Intervals (CI) 5.04, 6.19) and joint disorders 5.60% (95% CI 5.02, 6.18). Number of NCDs requiring a hospital admission was significantly higher in those with a common mental disorder (Hazard ratio (HR) 1.40 (95% CI 1.16–1.68), post-traumatic stress disorder (HR 1.78 (95% CI 1.32–2.40)) and in current smokers (HR 1.35 (95% CI 1.12–1.64) compared to those without the disorder, and non-smokers, respectively. Conclusions Military personnel with a mental health problem are more likely to have an inpatient hospital admission for NCDs compared to those without, evidencing the clear links between physical and mental health in this 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 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.

Summary We describe the incidence of suicidality (2007–2017) in people with depression treated by secondary mental healthcare services at South London and Maudsley NHS Trust (n = 26 412). We estimated yearly incidence of ‘suicidal ideation’ and ‘high risk of suicide’ from structured and free-text fields of the Clinical Record Interactive Search system. The incidence of suicidal ideation increased from 0.6 (2007) to 1 cases (2017) per 1000 population. The incidence of high risk of suicide, based on risk forms, varied between 0.06 and 0.50 cases per 1000 adult population (2008–2017). Electronic health records provide the opportunity to examine suicidality on a large scale, but the impact of service-related changes in the use of structured risk assessment should be considered.

Aureobasidium pullulans is an extremotolerant, cosmopolitan yeast-like fungus that successfully colonises vastly different ecological niches. The species is widely used in biotechnology and successfully applied as a commercial biocontrol agent against postharvest diseases and fireblight. However, the exact mechanisms that are responsible for its antagonistic activity against diverse plant pathogens are not known at the molecular level. Thus, it is difficult to optimise and improve the biocontrol applications of this species. As a foundation for elucidating biocontrol mechanisms, we have de novo assembled a high-quality reference genome of a strongly antagonistic A. pullulans strain, performed dual RNA-seq experiments, and analysed proteins secreted during the interaction with the plant pathogen Fusarium oxysporum. Based on the genome annotation, potential biocontrol genes were predicted to encode secreted hydrolases or to be part of secondary metabolite clusters (e.g., NRPS-like, NRPS, T1PKS, terpene, and β-lactone clusters). Transcriptome and secretome analyses defined a subset of 79 A. pullulans genes (among the 10,925 annotated genes) that were transcriptionally upregulated or exclusively detected at the protein level during the competition with F. oxysporum. These potential biocontrol genes comprised predicted secreted hydrolases such as glycosylases, esterases, and proteases, as well as genes encoding enzymes, which are predicted to be involved in the synthesis of secondary metabolites. This study highlights the value of a sequential approach starting with genome mining and consecutive transcriptome and secretome analyses in order to identify a limited number of potential target genes for detailed, functional analyses.

Global, large-scale surveys of phylogenetically diverse plant and lichen hosts have revealed an extremely high richness of endophytes in the Xylariales, one of the largest clades of filamentous fungi and a significant source of novel secondary metabolites (SMs). Endophytes may produce host protective antimicrobial or insecticidal SMs, as well as compounds that facilitate symbiotic establishment through suppression or degradation of host immune response, but the ecological roles of most SMs are unknown. Here we characterized metabolic gene clusters in 96 genomes of endophytes and closely related saprotrophs and pathogens in two clades of Xylariales (Xylariaceae s.l. and Hypoxylaceae). Hundreds of genes appear horizontally transferred to xylarialean fungi from distantly related fungi and bacteria, including numerous genes in secondary metabolite gene clusters (SMGCs). Although all xylarialean genomes contain hyperabundant SMGCs, we show that increased gene duplications, horizontal gene transfers (HGTs), and SMGC content in Xylariaceae s.l. taxa are linked to greater phylogenetic host breadth, larger biogeographic distributions, and increased capacity for lignocellulose decomposition compared to Hypoxylaceae taxa. Overall, our results suggest that xylarialean endophytes capable of dual ecological modes (symbiotic and saprotrophic) experience greater selection to diversify SMGCs to both increase competitiveness within microbial communities and facilitate diverse symbiotic interactions.

BackgroundClozapine, an antipsychotic, is associated with increased susceptibility to infection with COVID-19, compared to other antipsychotics.AimsTo investigate associations between clozapine treatment and increased risk of adverse outcomes of COVID-19, namely COVID-related hospitalisation and intensive care treatment, and death, among patients taking antipsychotics with schizophrenia-spectrum disorders.MethodUsing data from South London and Maudsley NHS Foundation Trust (SLAM) clinical records, via the Clinical Record Interactive Search system, we identified 157 individuals who had an ICD-10 diagnosis of schizophrenia-spectrum disorders, were taking antipsychotics at the time of the COVID-19 pandemic in the UK, and had a laboratory-confirmed COVID-19 infection. The following health outcomes were measured: COVID-related hospitalisation, COVID-related intensive care treatment death. We tested associations between clozapine treatment and each outcome using logistic regression models, adjusting for gender, age, ethnicity, neighbourhood deprivation, obesity, smoking status, diabetes, asthma, bronchitis and hypertension using propensity scores.ResultsIn the 157 individuals who developed COVID while on antipsychotics, there were 44 COVID-related hospitalisations, 13 COVID-related intensive care treatments and 13 deaths of any cause during the follow-up period. In the unadjusted analysis, there was no significant association between clozapine and any of the outcomes and there remained no associations following adjusting for the confounding variables.ConclusionsIn our sample of patients with COVID-19 and schizophrenia-spectrum disorders, we found no evidence that clozapine treatment puts patients at increased risk of hospitalisation, intensive care treatment or death, compared to any other antipsychotic treatment. However, further research should be considered in larger samples to confirm this.Conflict of interestRDH has received research funding from Roche, Pfizer, Janssen, and Lundbeck. DFF has received research funding from Janssen and Lundbeck. JHM has received research funding from Lundbeck. JTT has received research funding from Bristol-Meyers-Squibb. RS declares research support in the last 36 months from Janssen, GSK and Takeda.Ethics statementThe research was conducted under ethical approval reference 18/SC/0372 from Oxfordshire Research Ethics Committee C.

Background Although no drugs are licensed for the treatment of personality disorder, pharmacological treatment in clinical practice remains common. Aims This study aimed to estimate the prevalence of psychotropic drug use and associations with psychological service use among people with personality disorder. Method Using data from a large, anonymised mental healthcare database, we identified all adult patients with a diagnosis of personality disorder and ascertained psychotropic medication use between 1 August 2015 and 1 February 2016. Multivariable logistic regression models were constructed, adjusting for sociodemographic, clinical and service use factors, to examine the association between psychological services use and psychotropic medication prescribing. Results Of 3366 identified patients, 2029 (60.3%) were prescribed some form of psychotropic medication. Patients using psychological services were significantly less likely to be prescribed psychotropic medication (adjusted odds ratio 0.48, 95% CI 0.39–0.59, PP = 0.169) and multi-class psychotropic use (adjusted odds ratio 0.80, 95% CI 0.60–1.07, P = 0.133) between patients who did and did not use psychological services. Conclusions Psychotropic medication prescribing is common in patients with personality disorder, but significantly less likely in those who have used psychological services. This does not appear to be explained by differences in demographic, clinical and service use characteristics. There is a need to develop clear prescribing guidelines and conduct research in clinical settings to examine medication effectiveness for this population.

Background Gender disparities in treatment are apparent across many areas of healthcare. There has been little research into whether clozapine prescription, the first-line treatment for treatment-resistant schizophrenia (TRS), is affected by patient gender. Methods This retrospective cohort study identified 2244 patients with TRS within the South London and Maudsley NHS Trust, by using a bespoke method validated against a gold-standard, manually coded, dataset of TRS cases. The outcome and exposures were identified from the free-text using natural language processing applications (including machine learning and rules-based approaches) and from information entered in structured fields. Multivariable logistic regression was carried out to calculate the odds ratios for clozapine prescription according to patients' gender, and adjusting for numerous potential confounders including sociodemographic, clinical (e.g., psychiatric comorbidities and substance use), neutropenia, functional factors (e.g., problems with occupation), and clinical monitoring. Results Clozapine was prescribed to 77% of the women and 85% of the men with TRS. Women had reduced odds of being prescribed clozapine as compared to men after adjusting for all factors included in the present study (adjusted OR: 0.66; 95% CI 0.44–0.97; p = 0.037). Conclusion Women with TRS are less likely to be prescribed clozapine than men with TRS, even when considering the effects of multiple clinical and functional factors. This finding suggests there could be gender bias in clozapine prescription, which carries ramifications for the relatively poorer care of women with TRS regarding many outcomes such as increased hospitalisation, mortality, and poorer quality of life.

Alcohol use is a multidimensional risk factor for suicidal behaviour. However, suicide prevention strategies often take 'one-size-fits-all' approaches to alcohol use, reflecting an evidence base built on unidimensional measures. Latent Class Analysis can use a range of measures to differentiate distinct patterns of alcohol using behaviour and their associated risks.We analysed Electronic Health Record data from 650 suicidal adults detained for up to 36 h using police powers (Section 136 of the Mental Health Act 1983, amended 2007) to facilitate psychiatric assessment at a Health-Based Place of Safety, a dedicated emergency psychiatric care centre in London, UK. We conducted a Latent Class Analysis of alcohol using behaviours at first detention, and used multivariable logistic regression to estimate the association of each identified latent class with subsequent death or recontact with emergency psychiatric care over a median follow-up of 490 days, adjusting for sex, age and past-year psychiatric diagnosis.Three classes of alcohol use were identified: low risk drinkers, heavy episodic drinkers and dependent drinkers. The dependent drinking class had twice the odds of death or recontact with emergency psychiatric care as the low risk drinking class (OR 2.32, 95 %CI 1.62-3.32, p 0.001). Conversely, the heavy episodic drinking class was associated with lower odds of death or recontact than the low risk drinking class (OR 0.66, 95 %CI 0.53-0.81, p 0.001).The risk of adverse outcomes after a suicide attempt are not uniform for different alcohol use classes. Clinical assessment and suicide prevention efforts should be tailored accordingly.

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.

BACKGROUND: Patient-reported outcome measures (PROMs) are important tools to inform patients, clinicians and policy-makers about clinical need and the effectiveness of any given treatment. Consistent PROM use can promote early symptom detection, help identify unexpected treatment responses and improve therapeutic engagement. Very few studies have examined associations between patient characteristics and PROM data collection.METHODS: We used the electronic mental health records for 28,382 children and young people (aged 4-17 years) accessing Child and Adolescent Mental Health Services (CAMHS) across four South London boroughs between the 1st of January 2008 to the 1st of October 2017. We examined the completion rates of the caregiver Strengths and Difficulties Questionnaire (SDQ), a ubiquitous PROM for CAMHS at baseline and 6-month follow-up.RESULTS AND CONCLUSIONS: SDQs were present for approximately 40% (n = 11,212) of the sample at baseline, and from these, only 8% (n = 928) had a follow-up SDQ. Patterns of unequal PROM collection by sociodemographic factors were identified: males were more likely (aOR 1.07, 95% CI 1.01-1.13), whilst older age (aOR 0.87, 95% CI 0.87-0.88), Black (aOR 0.79 95% CI 0.74-0.84) and Asian ethnicity (aOR 0.75 95% CI 0.66-0.86) relative to White ethnicity, and residence within the most deprived neighbourhood (aOR 0.87 95% CI 0.80-0.94) were less likely to have a record of baseline SDQ. Similar results were found in the sub-group (n = 11,212) with follow-up SDQ collection. Our findings indicate systematic differences in the currently available PROMS data and highlights which groups require increased focus if we are to gain equitable PROM collection. We need to ensure representative PROM collection for all individuals accessing treatment, regardless of ethnic or socioeconomic background; biased data have adverse ramifications for policy and service level decision-making.

Background: Computer-modelling approaches have the potential to predict the interactions between different antipsychotics and provide guidance for polypharmacy. Aims: To evaluate the accuracy of the quantitative systems pharmacology platform to predict parkinsonism side-effects in patients prescribed antipsychotic polypharmacy. Methods: Using anonymized data from South London and Maudsley NHS Foundation Trust electronic health records we applied quantitative systems pharmacology, a neurophysiology-based computer model of humanized neuronal circuits, to predict the risk for parkinsonism symptoms in patients with schizophrenia prescribed two concomitant antipsychotics. The performance of the quantitative systems pharmacology model was compared with the performance of simple parameters such as: combination of affinity constants (1/Ksum); sum of D2R occupancies (D2R) and chlorpromazine equivalent dose. Results: We identified 832 patients with schizophrenia who were receiving two antipsychotics for six or more months, between 1 January 2007 and 31 December 2014. The area under the receiver operating characteristic (AUROC) curve for the quantitative systems pharmacology model was 0.66 (p = 0.01), while AUROCs for D2R, 1/Ksum and chlorpromazine equivalent dose were 0.52 (p = 0.350), 0.53 (p = 0.347) and 0.52 (p = 0.330) respectively. Conclusion: Our results indicate that quantitative systems pharmacology has the potential to predict the risk of parkinsonism associated with antipsychotic polypharmacy from minimal source information, and thus might have potential decision-support applicability in clinical settings.

ObjectivesTo investigate the association between long‐term antipsychotic polypharmacy use and mortality; and determine whether this risk varies by cause of death and antipsychotic dose.MethodsUsing data from a large anonymised mental healthcare database, we identified all adult patients with serious mental illness (SMI) who had been prescribed a single antipsychotic or polypharmacy, for six or more months between 2007 and 2014. Multivariable Cox regression models were constructed, adjusting for sociodemographic, socioeconomic, clinical factors and smoking, to examine the association between APP use and the risk of death.ResultsWe identified 10 945 adults with SMI who had been prescribed long‐term antipsychotic monotherapy (76.9%) or APP (23.1%). Patients on long‐term APP had a small elevated risk of mortality, which was significant in some but not all models. The adjusted hazard ratios for death from natural and unnatural causes associated with APP were 1.2 (0.9–1.4, P = 0.111) and 1.1 (0.7–1.9, P = 0.619) respectively. The strengths of the associations between APP and mortality outcomes were similar after further adjusting for % BNF antipsychotic dose (P = 0.031) or olanzapine equivalence (P = 0.088).ConclusionThe findings suggest that the effect of long‐term APP on mortality is not clear‐cut, with limited evidence to indicate an association, even after controlling for the effect of dose.

BackgroundSerious mental illness (SMI, including schizophrenia, schizoaffective disorder, and bipolar disorder) is associated with worse general health. However, admissions to general hospitals have received little investigation. We sought to delineate frequencies of and causes for non-psychiatric hospital admissions in SMI and compare with the general population in the same area.MethodsRecords of 18 380 individuals with SMI aged ⩾20 years in southeast London were linked to hospitalisation data. Age- and gender-standardised admission ratios (SARs) were calculated by primary discharge diagnoses in the 10th edition of the World Health Organization International Classification of Diseases (ICD-10) codes, referencing geographic catchment data.ResultsCommonest discharge diagnosis categories in the SMI cohort were urinary conditions, digestive conditions, unclassified symptoms, neoplasms, and respiratory conditions. SARs were raised for most major categories, except neoplasms for a significantly lower risk. Hospitalisation risks were specifically higher for poisoning and external causes, injury, endocrine/metabolic conditions, haematological, neurological, dermatological, infectious and non-specific (‘Z-code’) causes. The five commonest specific ICD-10 diagnoses at discharge were ‘chronic renal failure’ (N18), a non-specific code (Z04), ‘dental caries’ (K02), ‘other disorders of the urinary system’ (N39), and ‘pain in throat and chest’ (R07), all of which were higher than expected (SARs ranging 1.57–6.66).ConclusionA range of reasons for non-psychiatric hospitalisation in SMI is apparent, with self-harm, self-neglect and/or reduced healthcare access, and medically unexplained symptoms as potential underlying explanations.

Aims: To investigate clustering of all-cause and overdose deaths after a transfer of patients and their care to alternative treatment provider and after the end of opioid substitution therapy (OST) in opioid-dependent individuals in specialist addiction treatment. Design, Setting and Participants: Mortality data were identified within a sample of 5,445 patients with opioid use disorder who had received OST treatment between 1st April 2008 and 31st December 2013 from a large mental healthcare provider in United Kingdom. We investigated the circumstances and distribution of the 332 deaths identified within the observation window with a specific focus on overdose deaths (n=103) after a planned discharge, drop-out and transfer between services. Measurements: Crude mortality rates for overdose mortality 7/14/28/180 days after the end of treatment/transfer for overdose mortality. Findings: Of 47 individuals who died from overdose after having been transferred between services, 9 died in the first 2 weeks (crude mortality rate [CMR] 136.4, 64.3 – 243.1 95% CI) and a further 5 died in the first month post-transfer (CMR 79.5, 44.2 – 129.7 95% CI). Of the 32 individuals who died from overdose after planned OST cessation, 5 died in the first 2 weeks (CMR 151.5, 51.1 – 319.0 95% CI) and a further 4 died in the first month post discharge (CMR 82.6, 38.4 – 151.0 95% CI). Conclusions: In the UK, opioid-dependent people who are transferred to an alternative treatment provider for continuation of their opioid substitution therapy experience high overdose mortality rates, with substantially higher rates in the first month (especially first 14 days) following transfer.

Objectives The aim of this study was to determine if there was an association between being discharged on antipsychotic polypharmacy (APP) and risk of readmission into secondary mental health care. Methods Using data from the South London and Maudsley (SLAM) case register, service users with serious mental illness (SMI), discharged between 1st January 2007 and 31th December 2014, were followed up for 6 months. Patients were classified as receiving either monotherapy or polypharmacy at index discharge. Multivariable Cox regression models were constructed, adjusting for sociodemographic, socioeconomic, clinical and service use factors. Results We identified 5523 adults who had been admitted at least once to SLAM, of whom 1355 (24.5%) were readmitted into secondary mental health care. In total, 15% (n = 826) of patients were discharged on APP and 85% (n = 4697) on monotherapy. Of these, 30.9% (n = 255) and 23.4% (n = 1100) were readmitted respectively. Being discharged on APP was associated with a significantly increased risk of readmission, in comparison to patients discharged on monotherapy (HR = 1.4, 1.2–1.7, p

Summary Trends in detention under the Mental Health Act 1983 in two major London secondary mental healthcare providers were explored using patient-level data in a historical cohort study between 2007–2008 and 2016–2017. An increase in the number of detention episodes initiated per fiscal year was observed at both sites. The rise was accompanied by an increase in the number of active patients; the proportion of active patients detained per year remained relatively stable. Findings suggest that the rise in the number of detentions reflects the rise of the number of people receiving secondary mental healthcare.

Obsessive and Compulsive Symptoms (OCS) or Obsessive Compulsive Disorder (OCD) in the context of schizophrenia or related disorders are of clinical importance as these are associated with a range of adverse outcomes. Natural Language Processing (NLP) applied to Electronic Health Records (EHRs) presents an opportunity to create large datasets to facilitate research in this area. This is a challenging endeavour however, because of the wide range of ways in which these symptoms are recorded, and the overlap of terms used to describe OCS with those used to describe other conditions. We developed an NLP algorithm to extract OCS information from a large mental healthcare EHR data resource at the South London and Maudsley NHS Foundation Trust using its Clinical Record Interactive Search (CRIS) facility. We extracted documents from individuals who had received a diagnosis of schizophrenia, schizoaffective disorder, or bipolar disorder. These text documents, annotated by human coders, were used for developing and refining the NLP algorithm (600 documents) with an additional set reserved for final validation (300 documents). The developed NLP algorithm utilized a rules-based approach to identify each of symptoms associated with OCS, and then combined them to determine the overall number of instances of OCS. After its implementation, the algorithm was shown to identify OCS with a precision and recall (with 95% confidence intervals) of 0.77 (0.65–0.86) and 0.67 (0.55–0.77) respectively. The development of this application demonstrated the potential to extract complex symptomatic data from mental healthcare EHRs using NLP to facilitate further analyses of these clinical symptoms and their relevance for prognosis and intervention response.

BACKGROUND: Treatment with paliperidone palmitate (PP) has been shown to reduce hospitalisation, however its effect on broader service use remains unknown. Our objectives were to describe and compare the health care professional (HCP) use of patients treated with 1-monthly PP before and after its initiation. METHODS: Data were sourced from South London and Maudsley (SLAM) electronic health records on patients diagnosed with schizophrenia, who had received 1-monthly PP for at least 365 days. We employed two mirrored image analyses to determine the number and frequency of HCP contacts in the 12 months before and after PP initiation: 1) excluding all inpatient days at the time of initiation; 2) excluding only the post-initiation days for that stay. More specifically, we looked at face-to-face, telephone contacts, days spent as an inpatient and number of active days in the service. RESULTS: Of 664 patients who had received PP (mean age 42 years), 60.1% were male, 60.1% of black ethnicity, 78.5% single, and 82.7% unemployed; 56.5% of initiations occurred during inpatient episodes. The two mirror image analyses yielded similar RESULTS: following PP initiation, inpatient bed-days were lower (mean (SD)) with the number of bed-days before and after initiation respectively: 31.6 (52.0) and 21.1 (52.9) in model 1; 45.1 (64.0) and 21.1 (52.9) in model 2; both p

The prevalence of negative symptoms (NS) at first episode of early-onset psychosis (EOP), and their effect on psychosis prognosis is unclear. In a sample of 638 children with EOP (aged 10–17 y, 51% male), we assessed (1) the prevalence of NS at first presentation to mental health services and (2) whether NS predicted eventual development of multiple treatment failure (MTF) prior to the age of 18 (defined by initiation of a third trial of novel antipsychotic due to prior insufficient response, intolerable adverse-effects or non-adherence). Data were extracted from the electronic health records held by child inpatient and community-based services in South London, United Kingdom. Natural Language Processing tools were used to measure the presence of Marder Factor NS and antipsychotic use. The association between presenting with ≥2 NS and the development of MTF over a 5-year period was modeled using Cox regression. Out of the 638 children, 37.5% showed ≥2 NS at first presentation, and 124 (19.3%) developed MTF prior to the age of 18. The presence of NS at first episode was significantly associated with MTF (adjusted hazard ratio 1.62, 95% CI 1.07–2.46; P = .02) after controlling for a number of potential confounders including psychosis diagnostic classification, positive symptoms, comorbid depression, and family history of psychosis. Other factors associated with MTF included comorbid autism spectrum disorder, older age at first presentation, Black ethnicity, and family history of psychosis. In EOP, NS at first episode are prevalent and may help identify a subset of children at higher risk of responding poorly to antipsychotics.

Rationale: Antipsychotic polypharmacy (APP) is commonly used in schizophrenia despite a lack of robust evidence for efficacy, as well as evidence of increased rates of adverse drug reactions and mortality. Objectives: We sought to examine APP and the use of other adjunctive medications in patients with treatment-resistant schizophrenic disorders (ICD-10 diagnoses F20–F29) immediately prior to clozapine initiation, and to investigate clinical and sociodemographic factors associated with APP use in this setting. Methods: Analysis of case notes from 310 patients receiving their first course of clozapine at the South London and Maudsley NHS Trust (SLaM) was undertaken using the Clinical Record Interactive Search (CRIS) case register. Medication taken immediately prior to clozapine initiation was recorded, and global clinical severity was assessed at time points throughout the year prior to medication assessment using the Clinical Global Impression – Severity scale (CGI-S). Logistic regression was used to investigate factors associated with APP. Results: The point prevalence of APP prior to clozapine initiation was 13.6% ( n=42), with 32.6% of subjects prescribed adjuvant psychotropic medications. APP was associated with increasing number of adjuvant medications (odds ratio (OR) 1.97, 95% confidence interval (CI) 1.27–3.06), concurrent depot antipsychotic prescription (OR 2.64, CI 1.24–5.62), concurrent antidepressant prescription (OR 4.40, CI 1.82–10.63) and a CGI-S over the previous year within the two middle quartiles (Quartile 2 vs 1 OR 6.19, CI 1.81–21.10; Quartile 3 vs 1 OR 4.45, CI 1.29–15.37; Quartile 4 vs 1 OR 1.88, CI 0.45–7.13). Conclusions: APP and augmentation of antipsychotics with antidepressants, mood stabilizers and benzodiazepines are being employed in treatment-resistant schizophrenia prior to clozapine. The conservative APP rate observed may have been influenced by an initiative within SLaM that reduced APP rates during the study window. Efforts to reduce the use of poorly evidenced prescribing should focus on adjuvant medications as well as APP.