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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.

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.

Objectives To develop a prognostic tool of treatment resistant schizophrenia (TRS) in a large and diverse clinical cohort, with comprehensive coverage of patients using mental health services in four London boroughs. Methods We used the Least Absolute Shrinkage and Selection Operator (LASSO) for time-to-event data, to develop a risk prediction model from the first antipsychotic prescription to the development of TRS, using data from electronic health records. Results We reviewed the clinical records of 1,515 patients with a schizophrenia spectrum disorder and observed that 253 (17%) developed TRS. The Cox LASSO survival model produced an internally validated Harrel’s C index of 0.60. A Kaplan-Meier curve indicated that the hazard of developing TRS remained constant over the observation period. Predictors of TRS were: having more inpatient days in the three months before and after the first antipsychotic, more community face-to-face clinical contact in the three months before the first antipsychotic, minor cognitive problems, and younger age at the time of the first antipsychotic. Conclusions Routinely collected information, readily available at the start of treatment, gives some indication of TRS but is unlikely to be adequate alone. These results provide further evidence that earlier onset is a risk factor for TRS.

Funder: Psychiatry Research Trust Peggy Pollak Research Fellowship in Developmental Psychiatry, Funder: MQ: Transforming Mental Health; doi: http://dx.doi.org/10.13039/100011705, Funder: Psychiatry Research Trust, Funder: NIHR Senior Investigator Award, Funder: NIHR Applied Research Collaboration South London (NIHR ARC South London) at King’s College Hospital NHS Foundation Trust, Funder: NIHR, BACKGROUND: Individuals with autism spectrum disorder (ASD) are at particularly high risk of suicide and suicide attempts. Presentation to a hospital with self-harm is one of the strongest risk factors for later suicide. We describe the use of a novel data linkage between routinely collected education data and child and adolescent mental health data to examine whether adolescents with ASD are at higher risk than the general population of presenting to emergency care with self-harm. METHODS: A retrospective cohort study was conducted on the population aged 11-17 resident in four South London boroughs between January 2009 and March 2013, attending state secondary schools, identified in the National Pupil Database (NPD). Exposure data on ASD status were derived from the NPD. We used Cox regression to model time to first self-harm presentation to the Emergency Department (ED). RESULTS: One thousand twenty adolescents presented to the ED with self-harm, and 763 matched to the NPD. The sample for analysis included 113,286 adolescents (2.2% with ASD). For boys only, there was an increased risk of self-harm associated with ASD (adjusted hazard ratio 2·79, 95% CI 1·40-5·57, P

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.

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.

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.

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

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.

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.

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 illness. However, linkage error may underestimate these estimates. Using a clinical sample (n=265 300) of individuals accessing mental health services, we examined potential biases introduced through missed matching and examined the impact on the association between clinical disorders and mortality.SettingThe South London and Maudsley NHS Foundation Trust (SLaM) is a secondary mental healthcare provider in London. A deidentified version of SLaM’s EHR was available via the Clinical Record Interactive Search system linked to HES-ONS mortality records.ParticipantsRecords from SLaM for patients active between January 2006 and December 2016.Outcome measuresTwo sources of death data were available for SLaM participants: accurate and contemporaneous date of death via local batch tracing (gold standard) and date of death via linked HES-ONS mortality data. The effect of linkage error on mortality estimates was evaluated by comparing sociodemographic and clinical risk factor analyses using gold standard death data against HES-ONS mortality records.ResultsOf the total sample, 93.74% were successfully matched to HES-ONS records. We found a number of statistically significant administrative, sociodemographic and clinical differences between matched and unmatched records. Of note, schizophrenia diagnosis showed a significant association with higher mortality using gold standard data (OR 1.08; 95% CI 1.01 to 1.15; p=0.02) but not in HES-ONS data (OR 1.05; 95% CI 0.98 to 1.13; p=0.16). Otherwise, little change was found in the strength of associated risk factors and mortality after accounting for missed matching bias.ConclusionsDespite significant clinical and sociodemographic differences between matched and unmatched records, changes in mortality estimates were minimal. However, researchers and policy analysts using HES-ONS linked resources should be aware that administrative linkage processes can introduce error.

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 1,970 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.

Bulimia nervosa (BN) is associated with increased mortality. Frequent comorbidities of BN include substance use disorders, affective disorders and personality disorders (PD). These comorbidities may add an additional risk for mortality. We investigated the influence of these psychiatric comorbidities on all-cause mortality with demographic and socioeconomic factors considered as confounders over an observation period from January 2007 to March 2016 for 1501 people with BN using anonymised health records data from the South London and Maudsley NHS Foundation Trust (SLaM), retrieved through its Clinical Records Interactive Search (CRIS) data resource. Mortality was ascertained through monthly linkages to the nationwide tracing system administered by the Office for National Statistics (ONS). We used Cox proportional hazards regression to calculate hazard ratios (HRs) with 95% confidence intervals (CIs). Multivariable analyses were also performed to estimate effects when controlling for confounding of age, sex, ethnicity, borough, marital status and deprivation score. A total of 18 patients with BN died during the observation period. The standardised mortality ratio (SMR) for our study cohort (against the population of England and Wales in 2012 as a standard) was 2.52 (95% CI 1.49–3.97). Cox regressions revealed significant associations of mortality with older age and male gender. Comorbid PD (HR: 3.36; 95% CI 1.05–10.73) was significantly associated with all-cause mortality, even after controlling for demographic and socioeconomic covariates. These results highlight increased mortality in patients with BN and the importance of recognising and treating PDs in patients with BN.

BACKGROUND: Opioid misusers have recognized high mortality but the influence of psychiatric comorbidity in excess cause-specific mortality is unclear.METHODS: Opioid use disorder (OUD) patients were identified in the South London and Maudsley Case Register. Deaths were identified through database linkage to the national mortality dataset. Standard mortality ratios were calculated to compare mortality risk with the general population. Cox and competing risk regression models were used to investigate the effect of psychiatric comorbidity and psychological health on all-cause and cause-specific mortality (respectively) in OUD patients.RESULTS: Of 4837 OUD patients, 176 had died. Mortality rates were substantially higher than the general population (SMR 4.23; 95%CI 3.63-4.90). Among those with OUD, comorbid personality disorder (PD) and comorbid alcohol use disorder (AUD) was associated with increased all-cause mortality in all models, including the fully adjusted model, controlling for socio-demographic factors, severity of drug use, risk behaviours and physical health (HR2.15, 95%CI 1.17-3.95; HR2.28, 95%CI 1.54-3.36). AUD was associated with increased risk of fatal overdose (HR2.57, 95%CI 1.26-5.26) and hepatic-related deaths (HR7.26, 95%CI 2.79-18.86). Individuals with OUD and comorbid PD had almost four times greater risk of liver related deaths compared to those without PD (HR3.76, 95%CI 1.21-11.74). Comorbid severe mental illness and poor psychological health were not associated with increased mortality.CONCLUSIONS: This study highlights the importance of assessment for PD and AUD in OUD patients in order to identify individuals at substantially elevated mortality risk to enable a more personalized approach to their medical care.

Linkage of routinely collected data from public services has the potential to improve how local health, education and social care are delivered to children. All mental health services, hospital-based child health services, schools and child protection services which serve the same local area could be more efficient if the design, monitoring, targeting and integration of services were based on data. Health services need evidence from the populations that they serve to plan care and know whether they are meeting children's needs, duplicating effort or allowing some children to fall through the net. In this paper, we describe how the Clinical Record Interactive Search (CRIS) programme has joined up data from health, education and social services for children living in four local authorities in South London to create two datasets: one linking hospital to children's mental health services and the second linking mental health data to education data. We describe these resources, give examples of how they are being used to improve services and discuss what is needed to implement this approach more widely across the UK. Across England, all National Health Service (NHS) and state education services for children routinely generate administrative data, but few areas have managed to join these data systematically to evaluate how services could better serve their populations. Details of every NHS hospital inpatient admission, emergency department and outpatient contact are centrally collated by NHS Digital.1 Demographic and socioeconomic data on every child in state education are submitted by all state-maintained schools to the Department of Education, along with the information on school attendance, attainment, exclusion, child protection involvement and special educational needs.2 Centrally collected child mental health data have yet to become available, but nearly all local services collect these data within their electronic health record systems.3 A big challenge is meeting …

In a sample of children and adolescents with first-episode psychosis, we investigated whether multiple treatment failure (MTF, defined as the initiation of a third trial of novel antipsychotic due to nonadherence, adverse effects, or insufficient response) was associated with comorbid autism spectrum disorders.Data were from the electronic health records of 638 children (51% male) aged from 10 to 17 years with first-episode psychosis (per ICD-10 criteria) from January 1, 2008, to November 1, 2014, referred to mental health services in South London, United Kingdom; data were extracted using the Clinical Record Interactive Search (CRIS) system. The effect of autism spectrum disorder comorbidity on the development of MTF during a 5-year period was modeled using Cox regression.There were 124 cases of MTF prior to the age of 18 (19.4% of the sample). Comorbid autism spectrum disorders were significantly associated with MTF (adjusted hazard ratio = 1.99; 95% CI, 1.19-3.31; P = .008) after controlling for a range of potential confounders. Other factors significantly associated with MTF included higher age at first presentation (P = .001), black ethnicity (P = .03), and frequency of clinical contact (P.001). No significant association between other comorbid neurodevelopmental disorders (hyperkinetic disorder or intellectual disability) and MTF was found.Children with first-episode psychosis and comorbid autism spectrum disorders at first presentation are less likely to have a beneficial response to antipsychotics.

Purpose This study compares polydrug use in national and inner city samples to (1) examine patterns of use underlying different prevalence rates and (2) identify how inner city polydrug use needs targeting in ways not suggested by national research. Methods Latent class analyses on indicators of illicit drug use in the last year, hazardous alcohol use, and cigarette smoking were compared between the inner city 2008-2010 South East London Community Health study (n = 1698) and the nationally representative 2007 Adult Psychiatric Morbidity Survey in England (n = 7403). Multinomial logistic regressions then examined latent class solutions with demographic and socioeconomic factors. Results Both samples revealed three notably similar classes of polydrug users: a "high-drug" group using multiple substances; a "moderate-drug" group using cannabis, alcohol, and cigarettes; and a "low-drug" group reporting minimal alcohol and cigarette use. However, South East London Community Health reported lower risks of polydrug use for ethnic minorities but not for more educated participants. Conclusions Despite higher polydrug use prevalence in the inner city, latent classes of polydrug users were similar between samples. Some demographic and socioeconomic factors differed between the samples, suggesting the need for inner city services to use both local and national data for policy planning.

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.Mortality data were identified within a sample of 5335 patients with opioid use disorder who had received OST treatment between 1 April 2008 and 31 December 2013 from a large mental health-care provider in the 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, dropout and transfer between services.Crude mortality rates for overdose mortality 14 days, 28 days and more than 1 month after the end of treatment/transfer for overdose mortality.Of 47 individuals who died from overdose after having been transferred between services, nine died during the first 2 weeks [crude mortality rate (CMR) = 136.4, 95% confidence interval (CI) = 64.3-243.1] and a further five died during the first month post-transfer (CMR= 79.5, 95% CI = 44.2-129.7). Of the 32 individuals who died from overdose after planned OST cessation, five died during the first 2 weeks (CMR = 151.5, 95% CI = 51.1-319.0) and a further four died during the first month post-discharge (CMR = 82.6, 95% CI = 38.4-151.0).In the United Kingdom, 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 during the first month (especially during the first 14 days) following transfer.

The life expectancy gap between people with severe mental illness (SMI) and the general population persists and may even be widening. This study aimed to estimate contributions of specific causes of death to the gap. Age of death and primary cause of death were used to estimate life expectancy at birth for people with SMI from a large mental healthcare case register during 2007–2012. Using data for England and Wales in 2010, death rates in the SMI cohort for each primary cause of death category were replaced with gender- and age-specific norms for that cause. Life expectancy in SMI was then re-calculated and, thus, the contribution of that specific cause of death estimated. Natural causes accounted for 79.2% of lost life-years in women with SMI and 78.6% in men. Deaths from circulatory disorders accounted for more life-years lost in women than men (22.0% versus 17.4%, respectively), as did deaths from cancer (8.1% versus 0%), but the contribution from respiratory disorders was lower in women than men (13.7% versus 16.5%). For women, cancer contributed more in those with non-affective than affective disorders, while suicide, respiratory and digestive disorders contributed more in those with affective disorders. In men, respiratory disorders contributed more in non-affective disorders. Other contributions were similar between gender and affective/non-affective groups. Loss of life expectancy in people with SMI is accounted for by a broad range of causes of death, varying by gender and diagnosis. Interventions focused on multiple rather than individual causes of death should be prioritised accordingly.

Objectives To examine links between clinical and other characteristics of people with Alzheimer9s disease living in the community, likelihood of care home or hospital admission, and associated costs. Design Observational data extracted from clinical records using natural language processing and Hospital Episode Statistics. Statistical analyses examined effects of cognition, physical health, mental health, sociodemographic factors and living circumstances on risk of admission to care home or hospital over 6 months and associated costs, adjusting for repeated observations. Setting Catchment area for South London and Maudsley National Health Service Foundation Trust, provider for 1.2 million people in Southeast London. Participants Every individual with diagnosis of Alzheimer9s disease seen and treated by mental health services in the catchment area, with at least one rating of cognition, not resident in care home at time of assessment (n=3075). Interventions Usual treatment. Main outcome measures Risk of admission to, and days spent in three settings during 6-month period following routine clinical assessment: care home, mental health inpatient care and general hospital inpatient care. Results Predictors of probability of care home or hospital admission and/or associated costs over 6 months include cognition, functional problems, agitation, depression, physical illness, previous hospitalisations, age, gender, ethnicity, living alone and having a partner. Patterns of association differed considerably by destination. Conclusions Most people with dementia prefer to remain in their own homes, and funding bodies see this as cheaper than institutionalisation. Better treatment in the community that reduces health and social care needs of Alzheimer9s patients would reduce admission rates. Living alone, poor living circumstances and functional problems all raise admission rates, and so major cuts in social care budgets increase the risk of high-cost admissions which older people do not want. Routinely collected data can be used to reveal local patterns of admission and costs.

BACKGROUND:dementia is increasingly recognised as life-limiting condition. Although the benefits of acetylcholinesterase inhibitors (AChEIs) on cognition and function are well established, their effect on survival is less clear.OBJECTIVE:to investigate associations between AChEI prescription and mortality in patients with Alzheimer's dementia (AD) in a naturalistic setting, using detailed baseline data on cognition, functioning, and mental and physical wellbeing.METHODS:we used a large mental healthcare database in South London, linked to Hospital Episode Statistics and Office for National Statistics mortality data, to assemble a retrospective cohort. We conducted a survival analysis adjusting for a wide range of potential confounders using propensity scores to reduce the impact of confounding by indication.RESULTS:of 2,464 patients with AD, 1,261 were prescribed AChEIs. We detected a strong association between AChEI receipt and lower mortality (hazard ratio = 0.57; 95% CI 0.51-0.64). This remained significant after controlling for a broad range of potential confounders including psychotropic co-prescription, symptom severity, functional status and hospital admissions (hazard ratio = 0.77; 95% CI 0.67-0.87).CONCLUSIONS:in a large cohort of patients with AD, AChEI prescription was associated with reduced risk of death by more than 20% in adjusted models. This has implications for individual care planning and service development.

Purpose: The South London and Maudsley National Health Service (NHS) Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register and itsClinical Record Interactive Search (CRIS) application were developed in 2008, generating a research repository of real-time, anonymised, structured andopen-text data derived from the electronic health record system used by SLaM, a large mental healthcare provider in southeast London. In this paper, we updatethis register’s descriptive data, and describe the substantial expansion and extension of the data resource since its original development.Participants: Descriptive data were generated from the SLaM BRC Case Register on 31 December 2014. Currently, there are over 250 000 patient records accessed through CRIS.Findings to date: Since 2008, the most significant developments in the SLaM BRC Case Register have been the introduction of natural language processing toextract structured data from open-text fields, linkages to external sources of data, and the addition of a parallel relational database (Structured QueryLanguage) output. Natural language processing applications to date have brought in new and hitherto inaccessible data on cognitive function, education,social care receipt, smoking, diagnostic statements and pharmacotherapy. In addition, through external data linkages, large volumes of supplementary information have been accessed on mortality, hospital attendancesand cancer registrations.Future plans: Coupled with robust data security and governance structures, electronic health records provide potentially transformative information onmental disorders and outcomes in routine clinical care. The SLaM BRC Case Register continues to grow as a database, with approximately 20 000 new cases added each year, in addition to extension of follow-up for existing cases. Data linkages and natural language processing present important opportunities toenhance this type of research resource further, achieving both volume and depth of data. However, research projects still need to be carefully tailored, so that they take into account the nature and quality of the source information.

Introduction The 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 methods Using 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. Results We 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). Conclusion Our 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.

PURPOSE: There is a paucity of known correlates of common mental disorders (CMDs) among the youth age group in India. This analysis aims to determine risk factors associated with a probable diagnosis of CMD in a youth sample in India. METHODS: This is a secondary analysis of data collected via a door-to-door (community) survey of 3,662 youth (aged 16-24 years) in selected urban and rural areas in Goa. The urban and rural areas were selected based on their engagement with a Goan-based mental health charity organisation, Sangath. Point prevalence of CMD was estimated using the general health questionnaire-12 (GHQ-12). Multivariate logistic regression analyses determined factors associated with CMD and associations were stratified by gender. RESULTS: In total, 3,649 (1,796 urban; 1,853 rural) youth were assessed for probable diagnosis of CMD. There was an almost equal ratio of males (49 %) to females (51 %) in the sample. During the time of the survey, 91 % of the sample was residing with parents, with 83 % being between the ages of 22 and 24 years living with parents. A small proportion of the sample never attended school (1.1 %) with the rest either educated, employed or unemployed. The point prevalence of probable CMD in the sample was 7.87 %; 95 % CI 7.01-8.80 %. Those living in urban areas had a higher prevalence of CMD (9.12 %; 95 % CI 7.90-10.52 %) compared to those living in rural areas (6.60 %; 95 % CI 5.50-7.82 %). After adjusting for a range of potential confounders, independent risk factors for CMD were being older, i.e., between 22- and 24-years old, (OR 1.60; 95 % CI 1.10-2.24; p = 0.015), residing in urban areas (OR 1.51; 95 % CI 1.12-2.04; p = 0.007), physical abuse (beaten in the last 3 months) by parents, teachers or others (OR 3.10; 95 % CI 2.11-4.51; p < 0.001), sexual harassment (OR 2.01; 95 % CI 1.30-3.20; p = 0.003) and sexual abuse (OR 2.54; 95 % CI 1.94-3.33; p < 0.001). Being able to talk about personal problems (OR 0.52; 95 % CI 0.34-0.80; p = 0.003) was a protective factor. After stratifying by gender, sexual harassment, physical and sexual abuse were associated with a likely CMD diagnosis in females and males. CONCLUSIONS: Sexual and recent physical abuses were independent risk factors for CMD in both genders. In addition, being older and being able to discuss problems were associated with CMD diagnosis in females but not in males.

Objective To determine if aggression, hallucinations or delusions, and depression contribute to excess mortality risk observed in individuals with serious mental illness (SMI). Methods We identified SMI cases (schizophrenia, schizoaffective and bipolar disorder) aged ≥ 15 years in a large secondary mental healthcare case register linked to national mortality tracing. We modelled the effect of specific symptoms (HoNOS subscales) on all-cause mortality using Cox regression. Results We identified 6880 SMI cases (242 deaths) occurring 2007–2010. Bipolar disorder was associated with reduced mortality risk compared to schizophrenia (HR 0.7; 95% CI 0.4–0.96; p = 0.028). Mortality was not significantly associated with hallucinations and delusions or overactive–aggressive behaviour, but was associated with physical illness/disability. There was a positive association between mortality and subclinical depression among individuals with schizophrenia (HR 1.5; 1.1–2.2; p = 0.019) but a negative association with subclinical and more severe depression among those with schizoaffective disorder (HR 0.1; 0.02–0.4; p = 0.001 and 0.3; 0.1–0.8; p = 0.021, respectively). Conclusions The recognised increased risk of mortality in SMI did not appear to be influenced by severity of hallucinations, delusions, or overactive–aggressive behaviour. Physical illness and lifestyle may need to be addressed and the relationship between depression and mortality requires further investigation.

The human pathogen Trichomonas vaginalis lacks conventional mitochondria and instead contains divergent mitochondrial-related organelles. These double-membrane bound organelles, called hydrogenosomes, produce molecular hydrogen. Phylogenetic and biochemical analyses of hydrogenosomes indicate a common origin with mitochondria; however identification of hydrogenosomal proteins and studies on its metabolism have been limited. Here we provide a detailed proteomic analysis of the T. vaginalis hydrogenosome. The proteome of purified hydrogenosomes consists of 569 proteins, a number substantially lower than the 1,000 - 1,500 proteins reported for fungal and animal mitochondrial proteomes, yet considerably higher than proteins assigned to mitosomes. Pathways common to and distinct from both mitochondria and mitosomes were revealed by the hydrogenosome proteome. Proteins known to function in amino acid and energy metabolism, Fe-S cluster assembly, flavin-mediated catalysis, oxygen stress response, membrane translocation, chaperonin functions, proteolytic processing and ATP hydrolysis account for ∼30% of the hydrogenosome proteome. Of the 569 proteins in the hydrogenosome proteome, many appear to be associated with the external surface of hydrogenosomes, including large numbers of GTPases and ribosomal proteins. Glycolytic proteins were also found to be associated with the hydrogenosome proteome, similar to that previously observed for mitochondrial proteomes. Approximately 18% of the hydrogenosomal proteome is composed of hypothetical proteins of unknown function, predictive of multiple activities and properties yet to be uncovered for these highly adapted organelles.

Background People with substance use disorders (SUDs) have increased risk of mortality but risk in sub-groups is poorly understood. Methods SUD cases, aged 15 years or older, were identified in the South London and Maudsley Case Register which contains over 150,000 specialist mental healthcare and addictions service users linked to regular national mortality tracing. Standardized mortality ratios (SMRs) for the period 2007–2009 were calculated based on expected numbers of deaths for England and Wales in 2008 then stratified by gender, age, ethnicity, and type of substance use disorder. Life expectancies at birth were estimated. Results We detected 10,927 cases with a primary substance use disorder diagnosis prior to 2010, who were active to South London and Maudsley NHS Foundation Trust services between 2007 and 2009. Alcohol and opioid use disorders were the most common disorders (45.4% and 44.2% of the SUD cohort respectively) and were associated with increased mortality (SMRs 4.04 and 4.85 respectively). Subgroups at particularly high risk were women with opioid use disorder (SMR 7.32) and those under the age of 45 years with alcohol use disorder (SMR 9.25). SMRs associated with alcohol and opioid use disorders diminished with age. Life expectancies of individuals with alcohol and opioid use disorders were reduced by 9–17 years compared to national norms. Conclusions Those under 45 years with alcohol use disorder and women with opioid use disorder are at particularly high risk of mortality. More targeted health care is required to address the specific needs of these vulnerable subgroups.

Background: in community studies the prevalence of depression is higher in women than men; however, in palliative care settings this relationship is usually less strong, absent or reversed. Aim: to identify reasons for excess depression among men receiving palliative care. Design: cross-sectional study. Setting/participants: we interviewed 300 patients recruited from a large hospice in South East London. Depression was measured using the Primary Care Evaluation of Mental Disorder. Results: the higher prevalence of depression among men was not explained by a higher prevalence of particular types of cancer nor confounding by other covariates. Possible effect modifiers were examined. Depending on others for help with basic tasks (eating, dressing, washing or using the toilet) was a risk factor for depression in men only, with 37.8% of dependent men being depressed compared to 2.4% of similarly affected women (OR = 24.3, 3.1–193.2, p = 0.003). We observed a dose-response effect between the level of dependency and depression in men ( p for trend = 0.01). Conclusion: depending on others for help with basic tasks appears to contribute to the burden of depression among men with terminal illness. This gender-specific association may explain why the usual gender differences in depression prevalence are not observed in palliative care.

Introduction Previous, population‐based studies investigating the risk factors for sexual distress have not drawn on longitudinal data. Aims Determine the prevalence of sexual distress and dysfunction, explore factors associated with/predictive of sexual distress, and describe changes in sexual function over a decade in a population‐based sample of mid‐aged women. Methods Eleven‐year prospective study of Australian‐born women, aged 45–55 years, and menstruating at baseline. Short Personal Experiences Questionnaire (SPEQ) was completed in years 1 to 8 and 11 of follow‐up. Female Sexual Distress Scale (FSDS) was completed in the 11th year of follow‐up. Main Outcome Measures Validated outcome measures were the SPEQ (total sex score ≤7 indicates low sexual function) and FSDS (score ≥15 indicates sexual distress). Results Two hundred fifty‐seven women were interviewed in the 11th year of follow‐up. All domains of sexual function declined significantly in the decade studied. Women using hormone therapy in year 11 had significantly greater responsivity and higher frequency of sexual activities than nonusers. Two hundred four women completed both the FSDS and SPEQ questionnaires. One hundred sixty‐six (81%) women had an SPEQ score ≤7 of whom 34 (17% of the total sample) had an FSDS score ≥15, and were classified as having female sexual dysfunction. The multiple logistic regression analysis found that female sexual distress was concurrently associated with higher depression scores (odds ratio [OR] 1.31, 95% confidence interval [CI] 1.10, 1.56) and more negative feelings for partner (OR 0.49, 95% CI 0.32, 0.76) and predicted by prior negative feelings for partner (OR 0.31, 95% CI 0.14, 0.70), and a greater decline in total sex score (OR 0.77, 95% CI 0.59, 0.99). Conclusion By the end of the sixth decade, women have low levels of sexual function. Hormone therapy may help these women maintain sexual function. A minority of these mostly postmenopausal women are significantly distressed about low sexual function. Sexual distress is associated with depression and relationship factors. Dennerstein L, Guthrie JR, Hayes RD, DeRogatis LR, and Lehert P. Sexual function, dysfunction, and sexual distress in a prospective, population‐based sample of mid‐aged, Australian‐born women. J Sex Med 2008;5:2291–2299.

Objective To investigate associations between the prevalence of sexual difficulties reported in published studies and design features of those studies to determine if differences in design contribute to variation in prevalence estimates. Design Systematic review, multivariate analysis. Setting Studies published internationally in English. Patient(s) Not applicable. Intervention(s) None. Main Outcome Measure(s) Prevalence estimates of difficulty with desire, arousal, orgasm, and sexual pain reported in published studies. Result(s) Our systematic literature search identified 1,380 publications. Fifty-five studies met our inclusion criteria (reporting prevalence, sample size and response rate, sample size greater than 100, not clinic based). Reported prevalence of sexual difficulty varied across studies (up to tenfold). Eleven aspects of research conduct in these studies were included in our multivariate analysis as explanatory variables. Five aspects of study design and conduct (data collection procedures, inclusion criteria, duration of sexual difficulty recorded, sample size, and response rate) were associated with the reported prevalence of at least one type of sexual difficulty independently of likely predictors of true variation in prevalence: study location, study year, and age range of participants. Conclusion(s) This review provides evidence that study design may influence reported prevalence estimates of female sexual difficulties and contribute to the wide variation in published estimates.

Introduction No previous population-based studies have used validated instruments to measure female sexual dysfunction (FSD) in Australian women across a broad age range. Aim To estimate prevalence and explore factors associated with the components of FSD. Main Outcome Measures Sexual Function Questionnaire measured low sexual function. Female Sexual Distress Scale measured sexual distress. Methods Multivariate analysis of postal survey data from a random sample of 356 women aged 20–70 years. Results Low desire was more likely to occur in women in relationships for 20–29 years (odds ratio 3.7, 95% confidence intervals 1.1–12.8) and less likely in women reporting greater satisfaction with their partner as a lover (0.3, 0.1–0.9) or who placed greater importance on sex (0.1, 0.03–0.3). Low genital arousal was more likely among women who were perimenopausal (4.4, 1.2–15.7), postmenopausal (5.3, 1.6–17.7), or depressed (2.5, 1.1–5.3), and was less likely in women taking hormone therapy (0.2, 0.04–0.7), more educated (0.5, 0.3–0.96), in their 30s (0.2, 0.1–0.7) or 40s (0.2, 0.1–0.7), or placed greater importance on sex (0.2, 0.05–0.5). Low orgasmic function was less likely in women who were in their 30s (0.3, 0.1–0.8) or who placed greater importance on sex (0.3, 0.1–0.7). Sexual distress was positively associated with depression (3.1, 1.2–7.8) and was inversely associated with better communication of sexual needs (0.2, 0.05–0.5). Results were adjusted for other covariates including age, psychological, socioeconomic, physiological, and relationship factors. Conclusions Relationship factors were more important to low desire than age or menopause, whereas physiological and psychological factors were more important to low genital arousal and low orgasmic function than relationship factors. Sexual distress was associated with both psychological and relationship factors. Hayes RD, Dennerstein L, Bennett CM, Sidat M, Gurrin LC, and Fairley CK. Risk factors for female sexual dysfunction in the general population: Exploring factors associated with low sexual function and sexual distress.

Introduction A range of methodological inconsistencies has the potential to affect reported prevalence rates of sexual intercourse. Aims We reviewed published studies of sexual intercourse frequency reported by women and associated factors. Methods Literature search of electronic databases. Inclusion criteria for selected cross-sectional studies were population and community-based studies of frequency of intercourse in women published in English or German languages with sample size greater than 300. Longitudinal studies were selected if duration was at least 1 year and samples were not clinically based. Main Outcome Measures Frequency of sexual intercourse/activities and any associated factors. Results There was a great deal of variation in the mean frequency of intercourse across all age groups with higher rates reported by European and American women. There was a reduction in frequency of sexual intercourse from age 50 among women from Europe and the United States. Asian women reported increasing rates through the age group 20–30 followed by a decline. Change with age was not as evident among African and South American studies. Factors most often associated with the frequency of sexual intercourse were age, parity, duration of relationship, pregnancy, time, relationship status, fertility intentions, and contraception. Conclusions There is variation in reported frequency of sexual intercourse between studies, age groups, and continents. Some of the variation may be due to variation in definitions, study designs, and methods suggesting a need for greater consistency in research practice. Schneidewind-Skibbe A, Hayes RD, Koochaki PE, Meyer J, and Dennerstein L. The frequency of sexual intercourse reported by women: A review of community-based studies and factors limiting their conclusions.

Introduction Studies that address sensitive topics, such as female sexual difficulty and dysfunction, often achieve poor response rates that can bias results. Factors that affect response rates to studies in this area are not well characterized. Aim To model the response rate in studies investigating the prevalence of female sexual difficulty and dysfunction. Methods Databases were searched for English-language, prevalence studies using the search terms: sexual difficulties/dysfunction, woman/women/female, prevalence, and cross-sectional. Studies that did not report response rates or were clinic-based were excluded. A multiple linear regression model was constructed. Main Outcome Measures Published response rates. Results A total of 1,380 publications were identified, and 54 of these met our inclusion criteria. Our model explained 58% of the variance in response rates of studies investigating the prevalence of difficulty with desire, arousal, orgasm, or sexual pain ( R 2 = 0.581, P = 0.027). This model was based on study design variables, study year, location, and the reported prevalence of each type of sexual difficulty. More recent studies (β = −1.05, P = 0.037) and studies that only included women over 50 years of age (β = −31.11, P = 0.007) had lower response rates. The use of face-to-face interviews was associated with a higher response rate (β = 20.51, P = 0.036). Studies that did not include questions regarding desire difficulties achieved higher response rates than those that did include questions on desire difficulty (β = 23.70, P = 0.034). Conclusion Response rates in prevalence studies addressing female sexual difficulty and dysfunction are frequently low and have decreased by an average of just over 1% per anum since the late 60s. Participation may improve by conducting interviews in person. Studies that investigate a broad range of ages may be less representative of older women, due to a poorer response in older age groups. Lower response rates in studies that investigate desire difficulty suggest that sexual desire is a particularly sensitive topic. Hayes RD, Bennett C, Dennerstein L, Gurrin L, and Fairley C. Modeling response rates in surveys of female sexual difficulty and dysfunction.

Objective Explore the association between Hypoactive Sexual Desire Disorder (HSDD) and aging. The American Foundation of Urologic Disease and the American Psychiatric Association stipulate that HSDD is only diagnosed when both low sexual desire and sexually related personal distress are present. Design Community-based, cross-sectional study. Setting Europe (UK, Germany, France, Italy) and the USA. Patient(s) Women aged 20-70 in sexual relationships participating in the Women's International Study of Health and Sexuality (n=1998 Europe, n=1591 USA). Intervention(s) No interventions were administered. Main Outcome Measures Self-administered questionnaire that included two validated instruments: Profile of Female Sexual Function© measured sexual desire; Personal Distress Scale© measured sexual distress. Women with low desire and distress were considered to have HSDD. Results The proportion of European women with low desire increased from 11% amongst women aged 20-29 years to 53% amongst women aged 60-70 years. The proportion of American women with low desire displayed a trend towards an increase with age. In the 20-29 year age group 65% of European women and 67% of American women with low sexual desire were distressed by it. This decreased to 22% and 37%, respectively, in the 60-70 year age group. In Europe and the USA the prevalence of HSDD in the population did not change significantly with age (6-13% in Europe, 12-19% in the USA). Conclusions The proportion of women with low desire increased with age while the proportion of women distressed about their low desire decreased with age. Consequently, the prevalence of HSDD remained essentially constant with age. This may explain why no association between HSDD and age is often reported in the literature.

Clozapine can cause severe adverse effects yet it is associated with reduced mortality risk. We test the hypothesis this association is due to increased clinical monitoring and investigate risk of premature mortality from natural causes. We identified 14 754 individuals (879 deaths) with serious mental illness (SMI) including schizophrenia, schizoaffective and bipolar disorders aged ≥ 15 years in a large specialist mental healthcare case register linked to national mortality tracing. In this cohort study we modeled the effect of clozapine on mortality over a 5-year period (2007–2011) using Cox regression. Individuals prescribed clozapine had more severe psychopathology and poorer functional status. Many of the exposures associated with clozapine use were themselves risk factors for increased mortality. However, we identified a strong association between being prescribed clozapine and lower mortality which persisted after controlling for a broad range of potential confounders including clinical monitoring and markers of disease severity (adjusted hazard ratio 0.4; 95% CI 0.2–0.7; p = .001). This association remained after restricting the sample to those with a diagnosis of schizophrenia or those taking antipsychotics and after using propensity scores to reduce the impact of confounding by indication. Among individuals with SMI, those prescribed clozapine had a reduced risk of mortality due to both natural and unnatural causes. We found no evidence to indicate that lower mortality associated with clozapine in SMI was due to increased clinical monitoring or confounding factors. This is the first study to report an association between clozapine and reduced risk of mortality from natural causes.

Observational research using data from electronic health records (EHR) is a rapidly growing area, which promises both increased sample size and data richness - therefore unprecedented study power. However, in many medical domains, large amounts of potentially valuable data are contained within the free text clinical narrative. Manually reviewing free text to obtain desired information is an inefficient use of researcher time and skill. Previous work has demonstrated the feasibility of applying Natural Language Processing (NLP) to extract information. However, in real world research environments, the demand for NLP skills outweighs supply, creating a bottleneck in the secondary exploitation of the EHR. To address this, we present TextHunter, a tool for the creation of training data, construction of concept extraction machine learning models and their application to documents. Using confidence thresholds to ensure high precision (>90%), we achieved recall measurements as high as 99% in real world use cases.

Background Antipsychotic prescription information is commonly derived from structured fields in clinical health records. However, utilising diverse and comprehensive sources of information is especially important when investigating less frequent patterns of medication prescribing such as antipsychotic polypharmacy (APP). This study describes and evaluates a novel method of extracting APP data from both structured and free-text fields in electronic health records (EHRs), and its use for research purposes. Methods Using anonymised EHRs, we identified a cohort of patients with serious mental illness (SMI) who were treated in South London and Maudsley NHS Foundation Trust mental health care services between 1 January and 30 June 2012. Information about antipsychotic co-prescribing was extracted using a combination of natural language processing and a bespoke algorithm. The validity of the data derived through this process was assessed against a manually coded gold standard to establish precision and recall. Lastly, we estimated the prevalence and patterns of antipsychotic polypharmacy. Results Individual instances of antipsychotic prescribing were detected with high precision (0.94 to 0.97) and moderate recall (0.57-0.77). We detected baseline APP (two or more antipsychotics prescribed in any 6-week window) with 0.92 precision and 0.74 recall and long-term APP (antipsychotic co-prescribing for 6 months) with 0.94 precision and 0.60 recall. Of the 7,201 SMI patients receiving active care during the observation period, 338 (4.7 %; 95 % CI 4.2-5.2) were identified as receiving long-term APP. Two second generation antipsychotics (64.8 %); and first -second generation antipsychotics were most commonly co-prescribed (32.5 %). Conclusions These results suggest that this is a potentially practical tool for identifying polypharmacy from mental health EHRs on a large scale. Furthermore, extracted data can be used to allow researchers to characterize patterns of polypharmacy over time including different drug combinations, trends in polypharmacy prescribing, predictors of polypharmacy prescribing and the impact of polypharmacy on patient outcomes.

International audience; The BioMart Community Portal (www.biomart.org) is a community-driven effort to provide a unified interface to biomedical databases that are distributed worldwide. The portal provides access to numerous database projects supported by 30 scientific organizations. It includes over 800 different biological datasets spanning genomics, proteomics, model organisms, cancer data, ontology information and more. All resources available through the portal are independently administered and funded by their host organizations. The BioMart data federation technology provides a unified interface to all the available data. The latest version of the portal comes with many new databases that have been created by our ever-growing community. It also comes with better support and extensibility for data analysis and visualization tools. A new addition to our toolbox, the enrichment analysis tool is now accessible through graphical and web service interface. The BioMart community portal averages over one million requests per day. Building on this level of service and the wealth of information that has become available, the BioMart Community Portal has introduced a new, more scalable and cheaper alternative to the large data stores maintained by specialized organizations.

Introduction Despite rapid current and anticipated growth in the number of women who will spend a substantial portion of their life span in the postmenopausal period, the nature, incidence, and prevalence of changes in sexual function during and after the menopausal transition remain poorly characterized. Aim Challenges inherent in studying the menopausal transition and proposed additions and changes that have emerged from recent consensus conferences on female sexual dysfunction are reviewed. Methods Specific topics related to female sexual dysfunction were presented in a Postmenopausal FSD Roundtable in which multidisciplinary international experts participated. Main Outcome Measure Expert opinion was based on a review of evidence‐based medical literature, presentation, and internal discussion. Results Knowledge concerning sexual function in the menopause is limited, in part, due to the difficulty in designing and conducting studies that adequately address these changes over time, and which also permit the effects of menopause to be distinguished from more general changes associated with aging. Moreover, the study of female sexual function and dysfunction is in the midst of significant transition: a tentative definition of the stages of reproductive aging and menopause has recently been advanced, and a set of comprehensive changes to the diagnostic framework that defines female sexual dysfunction is under review. Conclusions In spite of fast‐moving changes in this field of study, it is possible to reach some tentative conclusions about how women's sexual function changes after menopause: postmenopausal women report a relatively high rate of sexual dysfunction (higher than men). There is a marked decline in sexual interest and frequency of sexual activity. This decline can be ameliorated by a number of psychosocial factors, although vaginal dryness and dyspareunia seem to be driven primarily by declining estradiol. The effects of menopause appear to be incremental and additional to those characteristic of aging. Dennerstein L, and Hayes RD. Confronting the challenges: epidemiological study of female sexual dysfunction and the menopause. J Sex Med 2005;2(suppl 3):118–132.

Introduction Scientific interest in the impact of aging on women's sexual function and dysfunction has increased in the half century since Kinsey described age‐related changes in women's sexual activities. However, a range of methodological issues limit the conclusions that can be drawn from many published studies in this area. Aim To review community‐based studies investigating changes in women's sexual function and sexual dysfunction with age, taking into account confounders to aging and methodological limitations. Methods Electronic databases were searched for published studies investigating changes in sexual function and dysfunction with age. A critical review was carried out. Main Outcome Measures Age‐related changes in sexual function and dysfunction. Results There are inconsistencies in the way sexual function and sexual dysfunction are measured. Validated scales are infrequently used. Low response rates, limited age ranges, and restrictive inclusion criteria limit the generalizability of many studies. Confounders are often either not measured or not analyzed. Longitudinal studies are rare, making it difficult to separate the effects of birth cohort and aging. The evidence indicates that a woman's sexual function declines with age. This decline begins in a woman's late 20s to late 30s. Specifically, desire, frequency of orgasm, and frequency of sexual intercourse decrease with age. However, it is not clear whether arousal decreases or remains relatively constant. In longitudinal studies, decline in women's sexual function has also been detected, but patterns of stability and improved sexual function have also been observed for short periods of time. The prevalence of most sexual difficulties or dysfunctions changes little with age, with the exception of sexual pain, which may decrease. Conclusions Age‐related changes in sexually related personal distress may help explain why the prevalence of sexual dysfunctions remains constant with age while sexual function declines. More research is needed to demonstrate this.