South London And Maudsley Research Articles

T127. GENDER DIFFERENCES IN CLINICAL PRESENTATION AND ILLICIT SUBSTANCE USE DURING FIRST EPISODE PSYCHOSIS: AN ELECTRONIC CASE REGISTER NATURAL LANGUAGE PROCESSING ANALYSIS

BackgroundGender differences in the clinical presentation of first episode psychosis (FEP) and its relationship to illicit substance use are inconclusive and underexplored. We conducted an electronic health record (EHR) study applying natural language processing (NLP) techniques to investigate gender differences in psychiatric symptoms when controlling for age, ethnicity, and illicit substance use.MethodsData were extracted from EHRs of 3,340 people presenting to the South London and Maudsley (SLaM) NHS Trust between April 2007 and March 2017 with FEP. Logistic regression was used to examine gender differences in presentation of 42 psychiatric symptoms, grouped into positive, negative, depressive, mania and disorganisation symptoms. We controlled for age of onset, ethnicity and illicit substance use (cocaine, amphetamine, MDMA or cannabis) and adjusted p-values for multiple comparisons.ResultsPatients were predominantly male (62%). Eight symptoms were more prevalent in males (poverty of thought, negative symptoms, social withdrawal, poverty of speech, aggression, grandiosity, paranoia and agitation), and thirteen in females (tearfulness, low energy, reduced appetite, low mood, pressured speech, mood instability, flight of ideas, guilt, mutism, insomnia, poor concentration, tangentiality and elation), before adjustment for age, ethnicity and substance use. Male patients were significantly more likely to experience negative symptoms than females (e.g. poverty of thought, OR 1.85, 95% CI 1.33 to 2.62); female patients showed increased likelihood of depressive and manic symptoms (e.g. tearfulness, 0.30, 0.26 to 0.35). Male patients were significantly more likely to misuse amphetamines, cannabis and cocaine (e.g. cannabis, OR 3.18, 2.75 to 3.70). All significant differences survived controls for age and ethnicity. After adjustment for illicit substance use gender differences in aggression, agitation, paranoia and grandiosity became insignificant (p > 0.05). However, adjustment for illicit substance use resulted in increased strength of gender associations with negative, manic and depression symptoms.DiscussionThere are clear gender differences in the clinical presentation of FEP which are modified by exposure to illicit substances. These findings highlight a need to better understand the impact of gender on clinical presentation and treatment outcomes in psychosis, and to ensure that clinicians are aware of how gender differences in presentation could be modified by illicit substance use.

T109. TRAVERSING THE TRANSDIAGNOSTIC GAP BETWEEN DEPRESSION, MANIA AND PSYCHOSIS WITH NATURAL LANGUAGE PROCESSING

BackgroundThe biological, clinical and social factors which underpin the aetiology of psychotic disorders are known to overlap between different ICD-10/DSM-5 diagnostic categories. A transdiagnostic approach to investigate clinical phenotype may enable a better understanding of pathophysiology at individual patient level. We applied natural language processing (NLP) tools to electronic health record (EHR) data from patients presenting with an ICD-10 diagnosis of unipolar depression to determine if symptoms at diagnosis could predict subsequent onset of a bipolar or psychotic disorder.MethodsData were obtained from 20,582 adults presenting with unipolar depression (ICD-10 F32 or F33, excluding F32.3 and F33.3) to the South London and Maudsley (SLaM) NHS Foundation Trust between April 2006 and March 2018.Natural language processing (NLP) techniques were used to extract data on 21 mood and affective symptoms from free text clinical assessments documented in the period -3/+3 months from the date of the diagnosis of unipolar depression. We obtained descriptive analyses of demographics and symptom prevalence.Symptoms were categorised into four groups: 1. Depressive (low mood, anhedonia, feelings of guilt, hopelessness, helplessness, psychomotor retardation, worthlessness, tearfulness, low energy), 2. Manic (elation, grandiosity, pressured speech, flight of ideas), 3. Biological symptoms (insomnia, disturbed sleep, low appetite, weight loss, poor concentration) and 4. Emotional/behavioural symptoms (mood instability, agitation, irritability). The symptom network structure was estimated using the Enhanced Least Absolute Shrinkage and Selection Operation procedure. We assessed network stability via a case-dropping bootstrapping procedure.We investigated associations between each of the four symptom groups and clinical outcomes using multivariable Cox regression to predict five-year risk of bipolar disorder (ICD-10 F30/F31) or a psychotic disorder (ICD-10 F2*).ResultsOf all patients presenting with unipolar depression, 19,569 (95.1%) had at least one documented depressive symptom, 16,199 (78.7%) had at least one biological symptom, 10,006 (48.6%) had at least one emotional/behavioural symptom, and 1,372 (6.67%) had at least one manic symptom. Patients with at least one manic symptom were significantly more likely to be male (OR: 1.25 (95% CI 1.12 - 1.40), p < 0.001) and less likely to be of Black (OR: 0.80 (0.68 - 0.93), p = 0.004) or Other ethnicity (OR: 0.78 (0.66 - 0.91), p = 0.003). Elation was the most commonly reported manic symptom (3.17%). Network analysis revealed that the presence of manic symptoms was associated with co-occurrence of agitation, irritability and mood instability. Agitation was the most central symptom in terms of strength, betweenness and expected influence. The resulting network remained stable after dropping up to 33% of cases from the sample.1,861 (9.04%) patients who initially presented with unipolar depression subsequently developed a mania/bipolar disorder or psychotic disorder within 5 years. The presence of at least one manic (HR: 1.71, 1.50 – 1.97), biological (HR: 1.33, 1.16 – 1.53) or emotional (HR: 1.91, 1.73 – 2.13) symptom was associated with significantly increased risk of onset of a bipolar or psychotic disorder.DiscussionWe found that patients with unipolar depression have a heterogenous clinical phenotype with a significant proportion going on to develop a bipolar or psychotic disorder within 5 years. Symptoms extracted from the EHR using NLP were predictive of subsequent onset of a bipolar or psychotic disorder. A transdiagnostic approach to defining clinical phenotype may help to better predict subsequent clinical outcomes.

Real-World Clinical Outcomes Two Years After Transition to Psychosis in Individuals at Clinical High Risk: Electronic Health Record Cohort Study.

The objective of this study is to describe the 2-year real-world clinical outcomes after transition to psychosis in patients at clinical high-risk. The study used the clinical electronic health record cohort study including all patients receiving a first index primary diagnosis of nonorganic International Classification of Diseases (ICD)-10 psychotic disorder within the early psychosis pathway in the South London and Maudsley (SLaM) National Health Service (NHS) Trust from 2001 to 2017. Outcomes encompassed: cumulative probability (at 3, 6, 12, and 24 months) of receiving a first (1) treatment with antipsychotic, (2) informal admission, (3) compulsory admission, and (4) treatment with clozapine and (5) numbers of days spent in hospital (at 12 and 24 months) in patients transitioning to psychosis from clinical high-risk services (Outreach and Support in south London; OASIS) compared to other first-episode groups. Analyses included logistic and 0-inflated negative binomial regressions. In the study, 1561 patients were included; those who had initially been managed by OASIS and had subsequently transitioned to a first episode of psychosis (n = 130) were more likely to receive antipsychotic medication (at 3, 6, and 24 months; all P < .023), to be admitted informally (at all timepoints, all P < .004) and on a compulsory basis (at all timepoints, all P < .013), and to have spent more time in hospital (all timepoints, all P < .007) than first-episode patients who were already psychotic when seen by the OASIS service (n = 310), or presented to early intervention services (n = 1121). The likelihood of receiving clozapine was similar across all groups (at 12/24 months, all P < .101). Transition to psychosis from a clinical high-risk state is associated with severe real-world clinical outcomes. Prevention of transition to psychosis should remain a core target of future research. The study protocol was registered on www.researchregistry.com; researchregistry5039).

Safe prescribing in cognitively vulnerable patients: the use of the anticholinergic effect on cognition (AEC) tool in older adult mental health services.

Aims and methodMedication with anticholinergic action is associated with potentially serious adverse effects in older people. We present an evaluation of a novel anticholinergic burden scale introduced into routine practice in older adult services in the South London and Maudsley (SLaM) NHS Foundation Trust. Our aim was to assess whether this tool improved the accurate identification of anticholinergic medication and guided safer prescribing in cognitively vulnerable older people. RESULTS: The introduction of the anticholinergic effect on cognition (AEC) tool into clinical practice led to an increase in the identification and reporting to general practitioners of anticholinergic medication from 11 to 85% of cases (P = 0.0015).Clinical implicationsApplication of the AEC tool led to improved detection of anticholinergic medication and advice to primary care on when a medication review is necessary. This is an important step towards improving the safety of prescribing in this patient group.Declaration of interestSLaM NHS Foundation Trust owns both the app and IP for Medichec.

Transdiagnostic Individualized Clinically Based Risk Calculator for the Detection of Individuals at Risk and the Prediction of Psychosis: Model Refinement Including Nonlinear Effects of Age.

Background: The first rate-limiting step for primary indicated prevention of psychosis is the detection of young people who may be at risk. The ability of specialized clinics to detect individuals at risk for psychosis is limited. A clinically based, individualized, transdiagnostic risk calculator has been developed and externally validated to improve the detection of individuals at risk in secondary mental health care. This calculator employs core sociodemographic and clinical predictors, including age, which is defined in linear terms. Recent evidence has suggested a nonlinear impact of age on the probability of psychosis onset. Aim: To define at a meta-analytical level the function linking age and probability of psychosis onset. To incorporate this function in a refined version of the transdiagnostic risk calculator and to test its prognostic performance, compared to the original specification. Design: Secondary analyses on a previously published meta-analysis and clinical register-based cohort study based on 2008–2015 routine secondary mental health care in South London and Maudsley (SLaM) National Health Service (NHS) Foundation Trust. Participants: All patients receiving a first index diagnosis of non-organic/non-psychotic mental disorder within SLaM NHS Trust in the period 2008–2015. Main outcome measure: Prognostic accuracy (Harrell’s C). Results: A total of 91,199 patients receiving a first index diagnosis of non-organic and non-psychotic mental disorder within SLaM NHS Trust were included in the derivation (33,820) or external validation (54,716) datasets. The mean follow-up was 1,588 days. The meta-analytical estimates showed that a second-degree fractional polynomial model with power (−2, −1: age1 = age−2 and age2 = age−1) was the best-fitting model (P < 0.001). The refined model that included this function showed an excellent prognostic accuracy in the external validation (Harrell’s C = 0.805, 95% CI from 0.790 to 0.819), which was statistically higher than the original model, although of modest magnitude (Harrell’s C change = 0.0136, 95% CIs from 0.006 to 0.021, P < 0.001). Conclusions: The use of a refined version of the clinically based, individualized, transdiagnostic risk calculator, which allows for nonlinearity in the association between age and risk of psychosis onset, may offer a modestly improved prognostic performance. This calculator may be particularly useful in young individuals at risk of developing psychosis who access secondary mental health care.

Psychiatric comorbidity as a risk factor for mortality in people with anorexia nervosa.

Anorexia nervosa (AN) is found associated with increased mortality. Frequent comorbidities of AN include substance use disorders (SUD), affective disorders (AD) and personality disorders (PD). We investigated the influence of these psychiatric comorbidities on all-cause mortality with demographic and socioeconomic factors considered as confounders in the observation window between January 2007 and March 2016 for 1970 people with AN, using data from the case register of the South London and Maudsley (SLaM) NHS Foundation Trust, an almost monopoly-secondary mental healthcare service provider in southeast London. We retrieved data from its Clinical Records Interactive Search (CRIS) system as data source. Mortality was ascertained through nationwide tracing by the UK Office for National Statistics (ONS) linked to CRIS database on a monthly basis. A total of 43 people with AN died during the observation period. Standardized Mortality Ratio (SMR) with England and Wales population in 2012 as standard population for our study cohort was 5.21 (95% CI 3.77, 7.02). In univariate analyses, the comorbidity of SUD or PD was found to significantly increase the relative risks of mortality (HRs = 3.10, 95% CI 1.21, 7.92; and 2.58, 95% CI 1.23, 5.40, respectively). After adjustment for demographic and socioeconomic covariates as confounders, moderately but not significantly elevated risks were identified for SUD (adjusted HR = 1.39, 95% CI 0.53, 3.65) and PD (adjusted HR = 1.58, 95% CI 0.70, 3.56). These results suggest an elevated mortality in people with AN, which might be, at least partially, explained by the existence of the comorbidities SUD or PD.

Transdiagnostic Risk Calculator for the Automatic Detection of Individuals at Risk and the Prediction of Psychosis: Second Replication in an Independent National Health Service Trust.

BackgroundThe benefits of indicated primary prevention among individuals at Clinical High Risk for Psychosis (CHR-P) are limited by the difficulty in detecting these individuals. To overcome this problem, a transdiagnostic, clinically based, individualized risk calculator has recently been developed and subjected to a first external validation in 2 different catchment areas of the South London and Maudsley (SLaM) NHS Trust.MethodsSecond external validation of real world, real-time electronic clinical register-based cohort study. All individuals who received a first ICD-10 index diagnosis of nonorganic and nonpsychotic mental disorder within the Camden and Islington (C&I) NHS Trust between 2009 and 2016 were included. The model previously validated included age, gender, ethnicity, age by gender, and ICD-10 index diagnosis to predict the development of any ICD-10 nonorganic psychosis. The model’s performance was measured using Harrell’s C-index.ResultsThis study included a total of 13702 patients with an average age of 40 (range 16–99), 52% were female, and most were of white ethnicity (64%). There were no CHR-P or child/adolescent services in the C&I Trust. The C&I and SLaM Trust samples also differed significantly in terms of age, gender, ethnicity, and distribution of index diagnosis. Despite these significant differences, the original model retained an acceptable predictive performance (Harrell’s C of 0.73), which is comparable to that of CHR-P tools currently recommended for clinical use.ConclusionsThis risk calculator may pragmatically support an improved transdiagnostic detection of at-risk individuals and psychosis prediction even in NHS Trusts in the United Kingdom where CHR-P services are not provided.

Long term outcomes of acute and transient psychotic disorders: The missed opportunity of preventive interventions

BackgroundAcute and transient psychotic disorders (ATPD) are characterized by an acute onset and a remitting course, and overlap with subgroups of the clinical high-risk state for psychosis. The long-term course and outcomes of ATPD are not completely clear. MethodsElectronic health record-based retrospective cohort study, including all patients who received a first index diagnosis of ATPD (F23, ICD-10) within the South London and Maudsley (SLaM) National Health Service Trust, between 1 st April 2006 and 15th June 2017. The primary outcome was risk of developing persistent psychotic disorders, defined as the development of any ICD-10 diagnoses of non-organic psychotic disorders. Cumulative risk of psychosis onset was estimated through Kaplan-Meier failure functions (non-competing risks) and Greenwood confidence intervals. ResultsA total of 3074 patients receiving a first index diagnosis of ATPD (F23, ICD-10) within SLaM were included. The mean follow-up was 1495 days. After 8-year, 1883 cases (61.26%) retained the index diagnosis of ATPD; the remaining developed psychosis. The cumulative incidence (Kaplan-Meier failure function) of risk of developing any ICD-10 non-organic psychotic disorder was 16.10% at 1-year (95%CI 14.83–17.47%), 28.41% at 2-year (95%CI 26.80–30.09%), 33.96% at 3-year (95% CI 32.25–35.75%), 36.85% at 4-year (95%CI 35.07–38.69%), 40.99% at 5-year (95% CI 39.12–42.92%), 42.58% at 6-year (95%CI 40.67–44.55%), 44.65% at 7-year (95% CI 42.66–46.69%), and 46.25% at 8-year (95% CI 44.17–48.37%). The cumulative risk of schizophrenia-spectrum disorder at 8-year was 36.14% (95% CI 34.09–38.27%). ConclusionsIndividuals with ATPD have a very high risk of developing persistent psychotic disorders and may benefit from early detection and preventive treatments to improve their outcomes.

O4.5. INVESTIGATING GENETIC PROFILES ASSOCIATED WITH ‘REAL WORLD’ CLINICAL OUTCOMES IN PSYCHOSIS: A RETROSPECTIVE COHORT STUDY

BackgroundThe Clinical Record Interactive Search (CRIS) database provides anonymised data from the full electronic health records of all patients at the South London and Maudsley NHS Foundation Trust, a large provider of secondary mental health care. We have previously shown how the large volumes of available CRIS data pertaining to outcomes can be mined and integrated with patient data collected by historical research interview.The applications of this futuristic translational research model are yet to be fully explored. The aim of this study is to determine whether transcriptomic profiles at the onset of psychosis can discern the likely trajectory symptoms over the subsequent 5 years of illness.MethodsThe study sample consists of 200 first-episode psychosis cases (ICD-10 codes: F20-F29 or F30-F33) aged 18–65 years who presented to SLAM (South London and Maudsley NHS Trust) mental health services between the 1st of January 2010 and the 1st of January 2015. Patients were subsequently recruited to the GAP study. Patients were followed-up electronically for 5 years post recruitment using the CRIS research platform.RNA samples were collected at the baseline timepoint via PAXgene blood tubes and interrogates, using the Illumina HumanHT-12.v4 beadchip array. Samples were run at the National Institute for Health Research’s (NIHR) Biomedical Research Centre for Mental Health (BRC-MH) at the Institute of Psychiatry, Psychology and Neuroscience. A total of 4756 probes passed a stringent quality control across the 200 samples.ResultsCRIS data pertaining to the GAP cohort was interrogated for information on clinical symptoms over a 5-year period using text-mining and natural language processing apps that represent over 70 different dictionary definitions of psychotic and affective symptoms. Confirmatory factor analysis was used to reduce this to a much smaller set of orthogonal symptom dimensions which were then the subject of a genetic interrogation using gene expression data. The analysis was conducted using a statistical learning framework which combines Elastic net penalised regression methodology with K-fold cross-validation (via the GLMnet package in R). This identified gene transcripts that were predictive of longer term symptom trajectories in half of the available sample. The veracity of the model was further validated using the second withheld portion of the sample.DiscussionThe results of this discovery phase may provide a rationale for subsequent multi-modal investigations whose aims will be to further enrich the biomarker signature and to also understand the molecular mechanisms that sustain them.

T122. UNMET NEEDS IN PATIENTS WITH ACUTE TRANSIENT PSYCHOTIC DISORDERS (ATPD): ANALYSIS OF PATHWAYS TO CARE: AN 8 YEARS FOLLOW-UP STUDY

BackgroundAcute and transient psychotic disorders (ATPDs) constitute a highly heterogeneous category of brief psychotic disorders. The long-term course and outcomes of ATPDs is not completely clear, with more than half of patients initially diagnosed with ATPDs shifting towards other psychotic spectrum diagnoses. Uncertainties in the real-world clinical care of these patients is further complicated by the diagnostic overlap with the Brief Limited Intermittent Psychotic Symptoms (BLIPS). Thus, patients with similar diagnostic features may either be recommended conventional antipsychotic treatment (if diagnosed with ATPD and according to the current guidelines for first episode psychosis - FEP) or be contraindicated antipsychotic treatment and receive psychological therapies (recommended for BLIPS cases).Given the complexity of the clinical presentation, admission to highly specialized services for early intervention in psychotic disorders (EIP) should represent the best therapeutic pathway for these patients. However, it is not known how many individuals with ATPDs are effectively detected and treated by EIP services.This study aims at overcoming such a gap in knowledge by describing the pathways to care of patients with ATPDs and the treatments received across eight follow-up time-points (3, 6, 12, 18, 24, 48, 72, and 96 months).MethodsElectronic health record-based retrospective cohort study including all patients who received a first index diagnosis of ATPD (F23, ICD-10) within the South London and Maudsley (SLaM) National Health Service Trust, between 1st April 2006 and 15th June 2017. Sociodemographic and clinical characteristics were analyzed using one-way ANOVA and Tukey post-hoc tests for continuous variables and chi square test for categorical variables. Logistic regression analyses were used to investigate the association between sociodemographic characteristics and detection/treatment by EIP.ResultsA total of 3074 patients receiving a first index diagnosis of ATPD (F23, ICD-10) within SLaM were included. The mean follow-up was 1495 days. After 8-year, 1883 cases (61.26%) retained the index diagnosis of ATPD; the remaining developed schizophrenia (23.8%), affective-spectrum psychoses (4.8%), and other psychotic disorders.Only 7.5 % of ATPDs was detected and treated by Early intervention in Psychosis services (EIP). The remaining quote of patients were treated with general mental health services (91.5%).Active treatment by EIS was more common among males, caucasian, and younger individuals (odds ratio (OR) = 1.35, 95% CI 1.01–1.7, P<0.001; OR = 0.6, 95% CI 0.46–0.78, P<0.001; and OR = 0.91, 95% CI 0.90–0.92, P<0.001, respectively).Almost half of the total sample (48.5%) was in treatment with antipsychotic medications after 1 year of follow-up. This proportion dropped to 25% after 3 years of active treatment.Less than 1% of ATPDs were offered psychotherapy interventions at any of the 8 time points of interest.DiscussionThe present study shows that the largest majority of individuals with ATPD (91.5%) is never detected and treated by the EIP services, which should be the best clinical option for these patients.This suggests that they are receiving neither the best first-episode care nor the best preventative care. Efforts should be done to promote outreach campaigns in general mental health services to persuade clinicians referring these patients to local EIP services, with the aim of providing the best possible care.

S24. IS IT FEASIBLE TO PREDICT LONG-TERM METABOLIC OUTCOMES IN PSYCHOSIS USING BIOLOGICAL PROFILING AT BASELINE?

BackgroundAntipsychotic medications are widely prescribed for the treatment of psychotic disorders but carry a variable propensity to increase weight. Thus metabolic dysfunction is the primary cause of premature death in psychosis patients. A system-based approach to understanding the molecular mechanisms behind metabolic dysfunction can potentially provide scope for tailored interventions and alternative treatment pathways that avert such risks on an individual basis. The aim of this study is to identify transcriptomic predictors of high Body Mass Index (BMI) and blood glucose in first episode and chronic psychosis patients.Methods100 first-episode and 100 chronic cases of psychosis meeting ICD-10 criteria (F20-29 and F30-33) were recruited as part of 2 independent studies from 3 NHS Trusts: South London and Maudsley (SLAM), Oxleas and Sussex. Cases were ethnically mixed and aged between 18–65. All participants gave informed consent for biological sampling and a range of physical health assessments. Blood glucose was measure using HbA1c while height and weight data were also taken and used to calculate BMI. For FEP subjects biological measures were taken at baseline, 3 months and 12 months post recruitment. RNA samples were collected at the baseline timepoint via PAXgene blood tubes and interrogates, using the Illumina HumanHT-12.v4 beadchip array. Samples were run at the National Institute for Health Research’s (NIHR) Biomedical Research Centre for Mental Health (BRC-MH) at the Institute of Psychiatry, Psychology and Neuroscience. A total of 4756 probes passed a stringent quality control across the 200 samples.ResultsQuantitative data on BMI and hba1c levels were used to assess the predictive efficacy of variables grouped by source (ie. clinical, demographic, technical and transcriptomic features) in first episode psychosis patients. All the predictor categories were included in the initial model, although individual categories were then dropped one at a time. This leave-one-out strategy allowed the direction, impact and relative contribution of the different feature classes to be assessed. Gene-expression and clinical features were consistently associated with the lowest Mean Squared Error after 100 iterations of K-fold cross-validation and after 11 different values of the alpha parameter across 500 imputed datasets. Hba1c or BMI was used as the clinical predictor, depending on whether Hba1c or BMI was used as the target variable. Unattributed surrogate variables derived from surrogate variable analysis (n=6) were analysed within the technical feature set. Having established that gene expression has inherent value as a predictor of metabolic status the same analytical steps were repeated for the discretised versions of these traits (ie. diabetes and obesity). Top-ranking gene transcripts were compared between the quantitative and discretised models. Rank lists of transcripts were subsetted to allow the power distribution across ordered transcripts to be profiled.DiscussionThe top performing transcripts identified are undergoing validation analysis in the chronic sample. Results will be conveyed in terms of sensitivity and false positive rates (ie. the area under the Receiver Operating Characteristic curve). We will undertake further validation through trajectory analysis of gene-expression profiles in followed-up patients.

Is lithium monitoring NICE? Lithium monitoring in a UK secondary care setting.

Lithium is widely used for the treatment of bipolar disorder. Owing to its narrow therapeutic index and side-effect profile, regular monitoring of serum levels, renal and thyroid function has been recommended by all major guidelines on lithium use. We investigated whether lithium monitoring during maintenance phase treatment in clinical practice meets the latest recommendation by the National Institute for Health and Clinical excellence (i.e. lithium levels between 0.6 and 1.0 mmol/L and lithium level, thyroid and renal function tests every 6 months) in one of the largest mental health organizations in Europe, the South London and Maudsley (SLaM) NHS Foundation Trust. Retrospective data were extracted from SLaM's Clinical Record Interactive Search (CRIS) system. Adult patients with a psychiatric disorder who were on lithium at any point during the period January 2012-January 2016 and had at least one lithium level test result in the system were included in the analyses. A total of 2639 lithium level tests results were retrieved for 412 patients. Overall, the serum level was within the recommended range in 50.7% of all tests, below the range in 42.4% and above in 6.9%. Lithium level, renal and thyroid function tests were performed at the recommended frequency of 6 months (or less) in 76.2%, 72.7% and 60.2% of patients, respectively. These data demonstrate that there is a gap between the NICE 2014 recommendation and lithium monitoring practice in secondary care, with a high number of lithium level results below the therapeutic minimum. Reminder strategies for secondary care practitioners, shared care agreements or a central registry for lithium users could improve monitoring performance.

Antipsychotic polypharmacy prescribing and risk of hospital readmission

ObjectivesThe 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.MethodsUsing 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.ResultsWe 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 < 0.001). This association was maintained in the fully adjusted model and following several sensitivity analyses. We further established that patients receiving clozapine APP (n = 200) were at a significantly increased risk for readmission in comparison to patients on clozapine monotherapy (HR = 1.8, 1.2–2.6, p = 0.008).ConclusionsOur results suggest that patients discharged on APP are more likely to be readmitted into hospital within 6 months in comparison to those discharged on monotherapy. This needs to be considered in treatment decisions and the reasons for the association clarified.

Predictors of long-term (≥ 6 months) antipsychotic polypharmacy prescribing in secondary mental healthcare

IntroductionThe predictors of long-term antipsychotic polypharmacy (APP) initiation are poorly understood. Existing research has been hampered by residual confounding, failure to exclude cross-titration, and difficulties in separating the timing of predictors and APP administration. Materials and methodsUsing data from the South London and Maudsley (SLaM) case register, we identified all adult patients with serious mental illness (SMI) who were receiving care between 1st July 2011 and 30th June 2012. Exposures measured between 1st July and 31st December 2011 included socio-demographic, socioeconomic, clinical and service use characteristics. We then determined if long-term APP (six or more months) had been initiated between 1st January and 30th June 2012. Multivariable logistic regression models, adjusted for socio-demographic and socioeconomic factors, were built to investigate the associations between the above factors and the initiation of long-term APP. ResultsWe identified 6857 adults with SMI receiving SLaM care, of whom 115 (1.7%) were newly prescribed long-term APP. In the adjusted models, predictors of long-term APP initiation included: symptoms (severity of hallucinations and/or delusions), previous treatments (clozapine and long-acting injectable antipsychotic agents), service use (more contact with outpatient services, community treatment order receipt), social factors (higher area-level deprivation, homelessness) and socio-demographic status (younger age, not in a relationship). ConclusionOur findings highlight that certain patient groups are at an increased risk for long-term APP initiation. Identifying these groups earlier in their treatment could encourage clinicians to employ a broader range of interventions in addition to pharmacotherapy to reduce the risk of APP prescribing.

Ethnic inequalities in the use of secondary and tertiary mental health services among patients with obsessive-compulsive disorder.

Obsessive-compulsive disorder (OCD) has similar prevalence rates across ethnic groups. However, ethnic minorities are underrepresented in clinical trials of OCD. It is unclear whether this is also the case in clinical services. To explore whether ethnic minorities with OCD are underrepresented in secondary and tertiary mental health services in the South London and Maudsley (SLaM) NHS Foundation Trust. The ethnic distribution of patients with OCD seen between 1999 and 2013 in SLaM (n = 1528) was compared with that of the general population in the catchment area using census data. A cohort of patients with depression (n = 22 716) was used for comparative purposes. Ethnic minorities with OCD were severely underrepresented across services (-57%, 95% CI -62% to -52%). The magnitude of the observed inequalities was significantly more pronounced than in depression (-29%, 95% CI -31% to -27%). There is a clear need to understand the reasons behind such ethnic inequalities and implement measures to reduce them.

Recommendations for a “Recovery” orientated apprenticeships scheme in mental health: a literature review

Purpose – Recovery principles have been central to debates in both the government and the mental health field, when thinking about the best way to support people who have experienced mental health distress into employment and education. The purpose of this paper is to review how this principle has been employed within the most effective approaches. This information will contribute to the development of the South London and Maudsley (SLaM) NHS Foundation Trust apprenticeship/return-to-work scheme for people who have experienced mental health distress. Design/methodology/approach – NHS evidence was used to undertake searches journals on CINAHL, EMBASE, PsycINFO, MEDLINE, HMIC, AMED, BNI, HEALTH BUSINESS ELITE and the Cochrane Library. Common search terms used were as follows: apprentice*; mental illness*; mental disorder*; psychiatric; psychosis; chronic mental disorder*; patient*; service user*; client*; return to work schemes; work; employment; unemployment; peer worker*; supported employment; vocational rehabilitation; peer training*; outcome measure*; recovery. Findings – Although the available literature writing about these employment schemes were not explicit in using Recovery as its guiding principle (i.e. Hope, Control and Opportunity), many of the participants in studies about a particular type of supported employment called Individual Placement Support (IPS) referred to recovery concepts in their narrative accounts, i.e. doing work that is meaningful, building self-esteem. This particular type of employment scheme was shown to have better outcomes for people who have experienced mental health difficulties then others schemes. The importance of employers having systems in place to support people’s control/self-management of their mental health condition was a key factor in helping them retain jobs once they have got them. Originality/value – The SLaM education and training service plans to develop a return to work programme for people who have had lived experience of mental health distress, through a workforce skills apprenticeships scheme. This is first apprenticeship scheme of this type in London. Therefore, this paper will review the literature on previous and current employment programmes for people who have experienced mental health distress, specifically highlighting what has worked well and what could be improved. This paper will also draw on the literature presented in this review and conclude on key points, which will contribute to the development of SLaM’s apprenticeships scheme. This literature review will form the basis of further research about the outcome/evaluation of the actual apprenticeship scheme after the first year.

Opportunities and challenges in Improving Access to Psychological Therapies for people with Severe Mental Illness (IAPT-SMI): Evaluating the first operational year of the South London and Maudsley (SLaM) demonstration site for psychosis

Despite its demonstrated clinical and economic effectiveness, access to Cognitive Behavioural Therapy for psychosis (CBTp) in routine practice remains low. The UK National Health Service (NHS England) Improving Access to Psychological Therapies for people with Severe Mental Illness (IAPT-SMI) initiative aims to address this problem. We report 14-month outcomes for our psychosis demonstration site.Primary and secondary care and self-referrals were screened to check the suitability of the service for the person. Psychotic symptoms, distress, service use, functioning and satisfaction were measured before and after therapy, by trained assessors. User-defined wellbeing and goal-attainment were rated sessionally.Access to CBTp increased almost threefold (2011/12 accepted referrals/year n = 106; 2012/13, n = 300). The IAPT-SMI assessment protocol proved feasible and acceptable to service users, with paired primary outcomes for 97% of closed cases. Therapy completion (≥5 sessions) was high (83%) irrespective of ethnicity, age and gender. Preliminary pre–post outcomes showed clinical improvement and reduced service use, with medium/high effect sizes. User-rated satisfaction was high.We conclude that individual psychological interventions for people with psychosis can be successfully delivered in routine services using an IAPT approach. High completion rates for paired outcomes demonstrate good user experience, clinical improvement, and potential future cost savings.

HORMONES OF THE ANTERIOR LOBE OF THE PITUITARY GLAND

<h3>Abstract</h3> <h3>Objectives</h3> The recent COVID-19 pandemic has disrupted mental healthcare delivery, with many services shifting from in- person to remote patient contact. We investigated the impact of the pandemic on the use of remote consultation and on the prescribing of psychiatric medications. <h3>Design and setting</h3> The Clinical Record Interactive Search tool (CRIS) was used to examine de-identified electronic health records (EHRs) of people receiving mental healthcare from the South London and Maudsley (SLaM) NHS Foundation Trust. Data from the period before and after the onset of the pandemic were analysed using linear regression, and visualised using locally estimated scatterplot smoothing (LOESS). <h3>Participants</h3> All patients receiving care from SLaM between 7^th January 2019 and 20^th September 2020 (around 37,500 patients per week). <h3>Outcome measures</h3> The number of clinical contacts (in-person, remote or non-attended) with mental healthcare professionals per week Prescribing of antipsychotic and mood stabiliser medications per week <h3>Results</h3> Following the onset of the pandemic, the frequency of in-person contacts was significantly reduced compared to that in the previous year (β coefficient: −5829.6 contacts, 95% CI −6919.5 to −4739.6, p&lt;0.001), while the frequency of remote contacts significantly increased (β coefficient: 3338.5 contacts, 95% CI 3074.4 to 3602.7, p&lt;0.001). Rates of remote consultation were lower in older adults than in working age adults, children and adolescents. Despite this change in the type of patient contact, antipsychotic and mood stabiliser prescribing remained at similar levels. <h3>Conclusions</h3> The COVID-19 pandemic has been associated with a marked increase in remote consultation, particularly among younger patients. However, there was no evidence that this has led to changes in psychiatric prescribing. Nevertheless, further work is needed to ensure that older patients are able to access mental healthcare remotely.