Maudsley NHS Foundation Trust Research Articles

Pharmacologic Interventions for Kawasaki Disease in Children: A Network Meta-Analysis of 56 Randomized Controlled Trials

Background: Although the current consensus recommends a standard treatment of high-dose intravenous immunoglobulin with high-dose aspirin to manage Kawasaki disease (KD), the use of different adjunctive therapies remains controversial. The aim of current network meta-analysis (NMA) was to compare the efficacy and tolerability of different existing interventions for the initial stage and the refractory stage of KD. Methods: The current NMA of randomized controlled trials (RCTs) was conducted under the frequentist model. Findings: Total fifty-six RCTs with 6,486 participants were included. The NMA demonstrated that the medium intravenous immunoglobulin (IVIG) + aspirin + infliximab [mean difference=−1.76 days (95% confidence intervals (95%CIs): −3.65 to 0.13 days) compared to high IVIG + aspirin] had the shortest fever duration; likewise, the medium IVIG + aspirin + infliximab [odds ratio (OR)=0.50, 95%CIs: 0.18 to 1.37 compared to high IVIG + aspirin] had the least CAL incidence in the initial-stage KD. The high IVIG + pulse steroid therapy (OR=0.04, 95%CIs: 0.00 to 0.43 compared to the high IVIG only) had the best fever subsided rate; likewise, the high IVIG + ciclosporin [OR=0.05 (95%CIs: 0.00 to 1.21) compared to the high IVIG only] had the least CAL incidence in the refractory-stage KD. Interpretation: The current NMA demonstrates that the addition of infliximab plus current standard therapy might be the best treatment for acute KD. Conversely, ciclosporin plus IVIG serves as the best choice for lower the CAL incidence in refractory KD. Further controlled trials are warranted to confirm these findings. Funding Statement: The authors of this work did not receive any grant supports. Brendon Stubbs is supported by a Clinical Lectureship (ICA-CL-2017-03-001) jointly funded by Health Education England (HEE) and the National Institute for Health Research (NIHR). Brendon Stubbs is part funded by the NIHR Biomedical Research Centre at South London and Maudsley NHS Foundation Trust. Brendon Stubbs is also supported by the Maudsley Charity, King’s College London and the NIHR South London Collaboration for Leadership in Applied Health Research and Care (CLAHRC) funding. This paper presents independent research. The views expressed in this publication are those of the authors and not necessarily those of the acknowledged institutions. Declaration of Interests: The authors report no financial interests or potential conflicts of interest.

The anticholinergic effect on cognition (AEC) scale: Associations with mortality, hospitalisation and cognitive decline following dementia diagnosis

AbstractObjectivesTo investigate associations between central anticholinergic burden (using the AEC scale), and mortality, hospitalisation and cognitive decline in patients with dementia.MethodsThe South London and Maudsley NHS Foundation Trust (SLaM) Clinical Records Interactive Search (CRIS) application was used to identify patients 65 years or older at their first recorded diagnosis of dementia. Data were linked to national mortality and hospitalisation sources, and serially recorded Mini‐Mental State Examination (MMSE) scores were used to investigate cognitive decline over the 36 months after diagnosis in mixed models.ResultsPatients for whom a review of their medication was indicated (AEC score ≥ 2 for any individual drug or total AEC score ≥ 3) had an increased risk of mortality (hazard ratio 1.07; 95% CI 1.01‐1.15) and emergency hospitalisation (1.10; 95% CI 1.04‐1.17), but there were no associations with duration of hospitalisation. Cognitive trajectory analyses showed that this exposure group had lower MMSE scores at diagnosis and a sharper increase in MMSE scores over the subsequent 6 months, but similar slopes for the 6‐36 months period to the remainder of the sample.ConclusionsPatients with dementia receiving medication with high central anticholinergic activity (as measured on the AEC scale), appear to have worse prognosis in terms of mortality and hospitalisation risk, but have primarily acutely impaired cognitive function, rather than longer term differences in cognitive decline.

Clinical factors associated with progression to dementia in people with late‐life depression: A cohort study of patients in secondary care

AbstractBackgroundDepression in later life is increasingly being recognised as a prodrome for the development of dementia. We aimed to investigate which clinical factors are associated with more rapid conversion from depression to dementia.MethodThe South London and Maudsley NHS Foundation Trust (SLaM) Clinical Record Interactive Search (CRIS) was used to retrieve anonymised data on patients who were aged 65 years or older and received a diagnosis of depression in mental health services, followed by a diagnosis of dementia >3 months later. Predictors of accelerated dementia development were investigated including demographic factors, health status rated on the Health of the National Outcome scale for older people (HoNOS65+), depression recurrence, and treatments including psychotropic drugs and cognitive behavioural therapy (CBT).ResultIn 806 patients with late‐life depression who later received a diagnosis of dementia, significant predictors of shorter time to dementia diagnosis in fully adjusted models were older age, male gender, higher deprivation, and HoNOS65+ subscales measuring depressed mood and cognitive problems. A diagnosis of recurrent depressive disorder was independently associated with a longer time to dementia diagnosis. Antipsychotic drugs and CBT were significantly associated with longer times to dementia diagnosis when adjusted for demographic factors and severity of mood and cognitive difficulties, but not in fully adjusted models.ConclusionIn older adults with depression and subsequent dementia diagnosed by mental health services, faster progression to a diagnosis of dementia was predicted by age and gender, new onset depression, and severity of depressive and cognitive symptoms.

Reviewing a Decade of Research Into Suicide and Related Behaviour Using the South London and Maudsley NHS Foundation Trust Clinical Record Interactive Search (CRIS) System.

Suicide is a serious public health issue worldwide, yet current clinical methods for assessing a person's risk of taking their own life remain unreliable and new methods for assessing suicide risk are being explored. The widespread adoption of electronic health records (EHRs) has opened up new possibilities for epidemiological studies of suicide and related behaviour amongst those receiving healthcare. These types of records capture valuable information entered by healthcare practitioners at the point of care. However, much recent work has relied heavily on the structured data of EHRs, whilst much of the important information about a patient's care pathway is recorded in the unstructured text of clinical notes. Accessing and structuring text data for use in clinical research, and particularly for suicide and self-harm research, is a significant challenge that is increasingly being addressed using methods from the fields of natural language processing (NLP) and machine learning (ML). In this review, we provide an overview of the range of suicide-related studies that have been carried out using the Clinical Records Interactive Search (CRIS): a database for epidemiological and clinical research that contains de-identified EHRs from the South London and Maudsley NHS Foundation Trust. We highlight the variety of clinical research questions, cohorts and techniques that have been explored for suicide and related behaviour research using CRIS, including the development of NLP and ML approaches. We demonstrate how EHR data provides comprehensive material to study prevalence of suicide and self-harm in clinical populations. Structured data alone is insufficient and NLP methods are needed to more accurately identify relevant information from EHR data. We also show how the text in clinical notes provide signals for ML approaches to suicide risk assessment. We envision increased progress in the decades to come, particularly in externally validating findings across multiple sites and countries, both in terms of clinical evidence and in terms of NLP and machine learning method transferability.

Cognitive Trajectories in Comorbid Dementia With Schizophrenia or Bipolar Disorder: The South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register

ObjectivesWe aimed to compare trajectories of cognitive performance in individuals diagnosed with dementia with and without severe mental illness (SMI). DesignRetrospective cohort study. SettingWe used data from a large longitudinal mental healthcare case register, the Clinical Record Interactive Search (CRIS), at the South London and Maudsley NHS Foundation Trust (SLaM) which provides mental health services to four south London boroughs. ParticipantsOur sample (N = 4718) consisted of any individual who had a primary or secondary diagnosis of dementia from 2007 to 2018, was 50 years old or over at first diagnosis of dementia and had at least 3 recorded Mini-Mental State Examination (MMSE) scores. MeasurementsCognitive performance was measured using MMSE. Linear mixed models were fitted to explore whether MMSE trajectories differed between individuals with or without prior/current SMI diagnoses. Models were adjusted by socio-demographics, cardiovascular risk, smoking, and medication. Results and conclusionsOur results showed differences in the rate of change, where individuals with comorbid SMI had a faster decline when compared with those that have dementia without comorbid SMI. However, this association was partially attenuated when adjusted by socio-demographics, smoking and cardiovascular risk factors; and more substantially attenuated when medication was included in models. Additional analyses showed that this accelerated decline might be more evident in individuals with bipolar disorders. Future research to detangle the potential biological underlying mechanisms of these associations is needed.

Biological Responses to COVID-19 Insights from Physiological and Blood Biomarker Profiles

Background: Understanding the spectrum and course of biological responses to coronavirus disease 2019 (COVID-19) may have important therapeutic implications. We sought to characterise biological responses among patients hospitalised with severe COVID-19 based on their serial physiological and blood biomarker values.Methods and Findings: We performed a retrospective cohort study of 1335 patients hospitalised with laboratory-confirmed COVID-19 (median age 70 years, 56% male), between 1st March and 30th April, 2020. Latent profile analysis was performed on serial physiological and blood biomarkers. Patient characteristics, comorbidities and rates of death and admission to intensive care, were compared between the latent classes. A five class solution provided the best fit. Class 1 “Typical response” exhibited a moderately elevated and rising C-reactive protein (CRP), stable lymphopaenia, and the lowest rates of 14-day adverse outcomes. Class 2 “Rapid hyperinflammatory response” comprised older patients, with higher admission white cell and neutrophil counts, which declined over time, and were accompanied by a very high and rising CRP and platelet count, and the greatest risk of mortality. Class 3 “Progressive inflammatory response” was similar to the typical response except for a higher and rising CRP, though similar mortality rate. Class 4 “Inflammatory response with kidney injury” had prominent lymphopaenia, moderately elevated (and rising) CRP, and severe renal failure. Class 5 “Hyperinflammatory response with kidney injury” comprised older patients, with a very high and rising CRP, and severe renal failure that attenuated over time. Physiological measures did not substantially vary between classes at baseline or early admission.Conclusions and Relevance: Our identification of five distinct classes of biomarker profiles provides empirical evidence for heterogeneous biological responses to COVID-19. Early hyperinflammatory responses and kidney injury may signify unique pathophysiology that requires targeted therapy.Funding Statement: This paper represents independent research part-funded by the National Institute for Health Research (NIHR) Biomedical Research Centres at South London and Maudsley NHS Foundation Trust, London AI Medical Imaging Centre for Value-Based Healthcare, and Guy’s & St Thomas’ NHS Foundation Trust, both with King’s College London.Declaration of Interests: JTHT received research support and funding from InnovateUK, Bristol-Myers-Squibb, iRhythm Technologies, and holds shares Ethics Approval Statement: This project was conducted under London South East Research Ethics Committee (reference 18/LO/2048) approval granted to the King’s Electronic Records Research Interface (KERRI); specific work on COVID-19 research was reviewed with expert patient input on a virtual committee with Caldicott Guardian oversight.

Pandemic-Related Emergency Psychiatric Presentations for Self-Harm of Children and Adolescents in 10 Countries (PREP-Kids): A Retrospective International Cohort Study

Background: Suicide is the second leading cause on death in young people and self-harm is one of the strongest predictors of death by suicide. Little is known about the impact of covid-19 lockdown on hospital presentations with self-harm.Method: We used electronic patient records from 23 hospital emergency departments in 10 countries to examine differences in hospital emergency psychiatric presentations for self-harm of youths through age 18 in March and April 2020 compared with the same period in 2019. To compare the number of hospital presentations a negative binomial model was used. For other variables, individual participant data (IPD) meta-analyses were carried out.Findings: The total number of emergency psychiatric hospital presentations decreased from 1,239 in 2019 to 834 in 2020, IRR 0·67, 95% CI 0·62-0·73. The proportion of youths presenting with self-harm increased from 50% in 2019 to 57% in 2020, OR 1·33, 95% CI 1·07-1·64, but there was no difference in the proportion presenting with severe self-harm. Within self-harm presentations, the proportion of youths with emotional disorders increased from 58% to 66%, OR 1·58, 95% CI 1·06-2·36. The proportion of youths admitted to an observation ward also decreased from 13% to 9% in 2020, OR 0·52, 95% CI 0·28 to 0·96. There were no differences in other outcomes and no evidence that youths from deprived areas or from ethnic minorities were disproportionally affected.Interpretation: During lockdowns, there are likely to be fewer hospital emergency psychiatric presentations. Many children and adolescents with psychiatric emergencies might not receive any service. Developing intensive community care services with outreach capabilities should be prioritised.Funding Statement: None.Declaration of Interests: In the last three years Dr. Carucci had collaborations within projects from the European Union (7th Framework Program) and as sub-investigator in sponsored clinical trials by Shire Pharmaceutical Company, Lundbeck, Otsuka, Janssen Cilag and Angelini. Travel support from Fidia Farmaceutici. PLP has received research funding from the German Federal Ministry of Education and Research (BMBF), the German Federal Institute for Drugs and Medical devices (BfARM), the Baden Wuerttemberg state foundation, eh Volkswagen foundation, Lundbeck and Servier. He received a speaker´s honorarium from Shire. All remaining authors have no competing interests to declare.Ethics Approval Statement: This study is based on the data from the NCDR obtained under licence from the UK Medicines and Healthcare products Regulatory Agency. The study was approved by the King’s College London/South London and Maudsley NHS Foundation Trust service evaluation and clinical audit committee Ref no: AP1312/05/2020.

Genetic Risk of Clozapine Induced Leukopenia and Neutropenia: A Genome-Wide Association Study

Background: Antipsychotics can improve psychotic symptoms, but treatment responses vary widely. Clozapine is considered to be the most effective antipsychotic medication for schizophrenia. However, it is also associated with several adverse effects such as metabolic syndrome and leukopenia. The mechanism of clozapine induced leukopenia (CIL) has not yet been fully elucidated. Genetic factors are likely to play an important role in the molecular basis, but most investigations have focused on individuals of European ancestry. In this manuscript, we report the first genome-wide association study (GWAS) of CIL and clozapine induced neutropenia (CIN) in a Chinese population. Methods: We performed a GWAS in up to 1,879 patients (225 CIL cases with WBC < 4,000 mm−3, including 43 CIN cases with ANC < 1500 mm−3, and 1654 controls) of Chinese descent. Data from common and rare single nucleotide polymorphisms (SNPs) were tested for association. We also performed a trans-ancestry meta-analysis with GWAS results of European individuals from the Clozapine Induced Agranulocytosis Consortium (CIAC). Findings: We identified several novel loci reaching the threshold of genome-wide significance level (P < 5 × 10−8). Three novel loci were associated with CIL while six were associated with CIN. We identified two T cell related genes in this study (TRAC and TRAT1). We also observed that one locus with evidence close to genome-wide significance (P = 5·08 × 10−8) was near the HLA-B gene in the major histocompatibility complex region in the trans-ancestry meta-analysis. Interpretation: Our results provide novel understanding of potential genetic and immune mechanisms for CIL and CIN. Funding Statement: This work was supported by the National Key RD Shanghai Youth Top-notch Talent Support Program to J.C., Shanghai Mental Health Center (2016-fx-02), Shanghai Municipal Commission of Science and Technology (17JC1402900, 17490712200, 18DZ2260200), Shanghai Municipal Health Commission (ZK2015B01, 201540114), Scientific Research and Development Fund of Shanghai Jiao Tong University (19X150010012), Shanghai Municipal Science and Technology Major Project (2018SHZDZX05), Innovative Research Team of High-Level Local Universities in Shanghai and Shanghai Clinical Research Center for Mental Health (19MC1911100). R.S. is part-funded by: i) the National Institute for Health Research (NIHR) Biomedical Research Centre at the South London and Maudsley NHS Foundation Trust and King’s College London; ii) a Medical Research Council (MRC) Mental Health Data Pathfinder Award to King’s College London; iii) an NIHR Senior Investigator Award; iv) the National Institute for Health Research (NIHR) Applied Research Collaboration South London (NIHR ARC South London) at King’s College Hospital NHS Foundation Trust. Declaration of Interests: We declare that we have no conflicts of interest. Ethics Approval Statement: In accordance with the principles in Declaration of Helsinki, the study was approved by the Ethics Committee at the Bio-X Institutes of Shanghai Jiao Tong University and the written informed consent was obtained from each participant. It is confirmed that the research complied with the Guidance of the Ministry of Science and Technology (MOST) for the Review and Approval of Human Genetic Resources.

Educational attainment trajectories among children and adolescents with depression, and the role of sociodemographic characteristics: longitudinal data-linkage study.

Depression is associated with lower educational attainment, but there has been little investigation of long-term educational trajectories in large cohorts with diagnosed depression. To describe the educational attainment trajectories of children with a depression diagnosis in secondary care, and to investigate whether these trajectories vary by sociodemographic characteristics. We identified new referrals to South London and Maudsley's NHS Foundation Trust between 2007 and 2013 who received a depression diagnosis at under 18 years old. Linking their health records to the National Pupil Database, we standardised their performance on three assessments (typically undertaken at ages 6-7 years (school Year 2), 10-11 (Year 6) and 15-16 (Year 11)) relative to the local reference population in each academic year. We used mixed models for repeated measures to estimate attainment trajectories. In our sample of 1492 children, the median age at depression diagnosis was 15 years (interquartile range = 14-16). Their attainment showed a decline between school Years 6 and 11. Attainment was consistently lower among males and those eligible for free school meals. Black ethnic groups also showed lower attainment than White ethnic groups between Years 2 and 6, but showed a less pronounced drop in attainment at Year 11. Those who receive a depression diagnosis during their school career show a drop in attainment in Year 11. Although this pattern was seen among multiple sociodemographic groups, gender, ethnicity and socioeconomic status predict more vulnerable subgroups within this clinical population who might benefit from additional educational support or more intensive treatment.

Using Natural Language Processing on Electronic Health Records to Enhance Detection and Prediction of Psychosis Risk.

Using novel data mining methods such as natural language processing (NLP) on electronic health records (EHRs) for screening and detecting individuals at risk for psychosis. The study included all patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within the South London and Maudsley (SLaM) NHS Foundation Trust between January 1, 2008, and July 28, 2018. Least Absolute Shrinkage and Selection Operator (LASSO)-regularized Cox regression was used to refine and externally validate a refined version of a five-item individualized, transdiagnostic, clinically based risk calculator previously developed (Harrell's C = 0.79) and piloted for implementation. The refined version included 14 additional NLP-predictors: tearfulness, poor appetite, weight loss, insomnia, cannabis, cocaine, guilt, irritability, delusions, hopelessness, disturbed sleep, poor insight, agitation, and paranoia. A total of 92 151 patients with a first index diagnosis of nonorganic and nonpsychotic mental disorder within the SLaM Trust were included in the derivation (n = 28 297) or external validation (n = 63 854) data sets. Mean age was 33.6 years, 50.7% were women, and 67.0% were of white race/ethnicity. Mean follow-up was 1590 days. The overall 6-year risk of psychosis in secondary mental health care was 3.4 (95% CI, 3.3-3.6). External validation indicated strong performance on unseen data (Harrell's C 0.85, 95% CI 0.84-0.86), an increase of 0.06 from the original model. Using NLP on EHRs can considerably enhance the prognostic accuracy of psychosis risk calculators. This can help identify patients at risk of psychosis who require assessment and specialized care, facilitating earlier detection and potentially improving patient outcomes.

Factors associated with slow progression of cognitive impairment following first dementia diagnosis.

To investigate the extent to which slow progression of dementia after diagnosis might be predicted from routine longitudinal healthcare data, in order to clarify characteristics of people who experience this outcome. A retrospective observational study was conducted using data from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre Case Register. This study included all patients receiving a first dementia diagnosis between 2006 and 2017, restricted to those with a baseline Mini-Mental State Examination (MMSE) score within 6 months of initial diagnosis of dementia and at least one MMSE score after 3 years post-diagnosis. Slow progression was defined as a change in MMSE score of -1, 0 or an increase at the follow-up point. This group was compared to the remainder with an MMSE decline of -2 or more. Overall, 682 patients with slow progression were compared to 1045 with faster progression. In the confounder-adjusted multivariate logistic regression model, slow progression was more likely in younger patients (age 65-74 years; odds ratio: 1.18; 95% confidence intervals: 1.04-1.37), males (1.24; 1.01-1.53), those with moderate or severe dementia according to MMSE, patients with mixed-type dementia (2.06; 1.11-3.82) compared to Alzheimer's disease and less likely in those receiving acetylcholinesterase inhibitor (AChEI) treatment (0.57; 0.46-0.71). Slow dementia progression after diagnosis was common in patients with mixed Alzheimer's and vascular dementia, younger age, males and non-receipt of AChEIs, possibly suggesting non-Alzheimer pathologies and clarifying such predictors is important, as there is currently very limited information on which to base prognosis estimates in post-diagnosis counselling.

Anticipating Issues with Capacitous Pregnant Women: United Lincolnshire NHS Hospitals Trust v CD [2019] EWCOP 24 and Guys and St Thomas' NHS Foundation Trust (GSTT) and South London and Maudsley NHS Foundation Trust (SLAM) v R [2020] EWCOP 4.

In United Lincolnshire NHS Hospitals Trust v CD and Guys and St Thomas' NHS Foundation Trust (GSTT) and South London and Maudsley NHS Foundation Trust (SLAM) v R, the Court of Protection was asked to make anticipatory and contingent declarations relating to the obstetric care and mode of delivery for currently capacitous women who were near to their due date but not yet in labour. In this case note I explore the judges' reasoning on the legal basis for these declarations. In so doing, I consider the wider implications of employing this seemingly new addition to the Court of Protection's armoury.

Clozapine treatment and risk of COVID-19 infection: retrospective cohort study.

Clozapine, an antipsychotic with unique efficacy in treatment-resistant psychosis, is associated with increased susceptibility to infection, including pneumonia. To 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. Using 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. Of 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). These 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.

Clozapine Treatment and Risk of COVID-19

Background: COVID-19 is a novel infection that leads to pneumonia in severe cases. Clozapine, an antipsychotic with unique efficacy in treatment resistant psychosis, is known to be associated with increasing risk of pneumonia. Aims: To investigate possible 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. Method: We identified 6304 individuals who had an ICD-10 diagnosis of schizophrenia-spectrum disorders and were taking antipsychotic during the 3 months prior the follow-up period. People who were on clozapine treatment were designated as the exposed group. Those on any type or combination of antipsychotic treatment that did not include clozapine were designated unexposed. We tested associations between clozapine treatment and COVID-19, adjusting for potential confounders. Results: 70 patients developed COVID-19. Individuals who were on clozapine had a nearly threefold increased risk of COVID-19 compared with those who were on other antipsychotic medication (hazard ratio HR=2.70, 95% CI 1.62 - 4.51). This association was attenuated but remained after adjustment for potential confounders. Conclusion: These findings provide support for the hypothesis that clozapine treatment is associated with increased risk of COVID-19. Further research will be needed in other samples to confirm this association. Potential clinical implications are discussed. Funding Statement: This work was supported by the Clinical Records Interactive Search (CRIS) system funded and developed by the National Institute for Health Research (NIHR) Mental Health Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King’s College London and a joint infrastructure grant from Guy’s and St Thomas’ Charity and the Maudsley Charity (grant number BRC-2011-10035). RDH DF and JHM receive salary support from the National Institute for Health Research (NIHR) Maudsley Biomedical Research Centre at South London and Maudsley NHS Foundation Trust and King's College London. Declaration of Interests: RDH, received research funding from Roche, Pfizer, Janssen and Lundbeck, DF has received research funding from Janssen and Lundbeck. JHM has received research funding from Lundbeck. All other authors have no conflict of interest. Ethics Approval Statement: The research was conducted under ethical approval reference 18/SC/0372 from Oxfordshire Research Ethics Committee C.

Impact of matching error on linked mortality outcome in a data linkage of secondary mental health data with Hospital Episode Statistics (HES) and mortality records in South East London: a cross-sectional study

ObjectivesLinkage of electronic health records (EHRs) to Hospital Episode Statistics (HES)-Office for National Statistics (ONS) mortality data has provided compelling evidence for lower life expectancy in people with severe mental...

The anticholinergic effect on cognition (AEC) scale-Associations with mortality, hospitalisation and cognitive decline following dementia diagnosis.

To investigate associations between central anticholinergic burden (determined through the anticholinergic effect on cognition [AEC] scale) and mortality, hospitalisation and cognitive decline in patients with dementia. The South London and Maudsley NHS Foundation Trust (SLaM) Clinical Records Interactive Search (CRIS) application was used to identify patients with a first diagnosis of dementia. Medication exposure was extracted through a natural language processing algorithm, allowing for calculations and comparisons of AEC scores. Data were linked to national mortality and hospitalisation data sources, and serially recorded Mini-Mental State Examination (MMSE) scores were used to investigate cognitive decline. We identified 14 093 patients with dementia, 60.7% were female and the mean age at diagnosis was 79.8 years. Patients for whom a review of their medication was indicated (AEC score ≥ 2 for any individual drug or total AEC score ≥ 3) had an increased risk of mortality (hazard ratio 1.07; 95% confidence interval [CI]: 1.01-1.15) and emergency hospitalisation (1.10; 95% CI: 1.04-1.17), but there were no associations with duration of hospitalisation. Cognitive trajectory analyses showed that this exposure group had lower MMSE scores at diagnosis and a sharper increase in MMSE scores over the subsequent 6 months, but similar slopes for the 6 to 36 months period compared to the remainder of the sample. Patients with dementia receiving medication with high central anticholinergic activity appear to have worse prognosis in terms of mortality and hospitalisation risk, but have, primarily, acutely impaired cognitive function, rather than longer-term differences in cognitive decline. J Am Geriatr Soc 68:-, 2020.

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.

Seclusion: A Patient Perspective

The appropriate treatment of mentally unwell, aggressive patients has challenged psychiatry for centuries. Seclusion is practiced worldwide, but concerns remain regarding its appropriateness and lack of alternatives. Patients generally report seclusion as a negative experience, though there is a paucity of literature exploring this in detail. This investigation was a service evaluation appraising inpatients’ perspective of processes occurring before (information, communication), during (review, care), and after (debrief, reflection) seclusion in a psychiatric intensive care unit (PICU). In this phenomenological study, qualitative data were gathered using a questionnaire in a structured interview. All patients had been nursed in seclusion during admission to a male PICU at South London and the Maudsley NHS Foundation Trust. Ten patients were interviewed over 4 months. The central theme was perceived lack of communication in the patient-professional relationship, which manifested itself as (i) violence against patients, (ii) lack of psychological support, and (iii) the need for alternatives. Such feedback from patients queries whether national guidelines are appropriate and/or being adhered to. Healthcare practitioners have a responsibility to challenge accepted practice to continually improve the standard of patient-centred care. Utilising patient perspectives can be a powerful driver of change towards more humane treatment of vulnerable patients.

Clinical factors associated with progression to dementia in people with late-life depression: a cohort study of patients in secondary care

ObjectivesDepression can be a prodromal feature or a risk factor for dementia. We aimed to investigate which clinical factors in patients with late-life depression are associated with a higher risk...

Effectiveness of small group cognitive behavioural therapy for anxiety and depression in Ebola treatment centre staff in Sierra Leone

Following the 2014 Ebola outbreak, South London and Maudsley NHS Foundation Trust (SLAM) were commissioned to provide a ‘culturally appropriate, effective and sustainable’ intervention to address the psychological needs of the Sierra Leonean Ebola Treatment Centre (ETC) staff. The study evaluated the effectiveness of group Cognitive Behavioural Therapy (CBT) developed to treat anxiety, depression and functional impairment amongst a sample of former ETC staff in Sierra Leone. Group comparisons explored whether the effect of the intervention differed dependent on the facilitators that delivered it, as well as whether it differed between former staff of high- and low-risk ETC roles. A sample of 253 former ETC staff attended the group CBT intervention comprised of eight sessions over six weeks. Outcome measures were administered upon entry and within two weeks after the intervention. At post-intervention, anxiety, depression and functional impairment significantly reduced. Reading ability (RA) was introduced as a covariate having impacted the outcomes. The intervention effect differed by facilitators delivering the sessions but not by ETC role risk. The implications of these results are discussed. Group CBT is a promising psychological intervention for treating the anxiety, depression and functional impairment of former ETC staff in Sierra Leone. Furthermore, as part of a stepped-care approach, it may provide a model for psychological support for staff that have worked on the frontline during future epidemics.