Search

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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

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.

© 2018, Filiault et al. The columbine genus Aquilegia is a classic example of an adaptive radiation, involving a wide variety of pollinators and habitats. Here we present the genome assembly of A. coerulea 'Goldsmith', complemented by high-coverage sequencing data from 10 wild species covering the world-wide distribution. Our analyses reveal extensive allele sharing among species and demonstrate that introgression and selection played a role in the Aquilegia radiation. We also present the remarkable discovery that the evolutionary history of an entire chromosome differs from that of the rest of the genome - a phenomenon that we do not fully understand, but which highlights the need to consider chromosomes in an evolutionary context.

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 Personality disorder (PD) is associated with important health outcomes in the general population. However, the length of diagnostic interviews poses a significant barrier to obtaining large scale, population-based data on PD. A brief screen for the identification of people at high risk of PD in the general population could be extremely valuable for both clinicians and researchers. Aim We set out to validate the Standardised Assessment of Personality – Abbreviated Scale (SAPAS), in a general population sample, using the Structured Clinical Interviews for DSM-IV Personality Disorders (SCID-II) as a gold standard. Method One hundred and ten randomly selected, community-dwelling adults were administered the SAPAS screening interview. The SCID-II was subsequently administered by a clinical interviewer blind to the initial SAPAS score. Receiver operating characteristic analysis was used to assess the discriminatory performance of the SAPAS, relative to the SCID-II. Results Area under the curve for the SAPAS was 0.70 (95% CI = 0.60 to 0.80; p

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.

ObjectivesTo compare sample biases when linking education data to external datasets using opt in and opt out consent models for the Millennium Cohort Study (MCS) – opt in, and the Case Register Interactive Search Child and Adolescent Mental Health sample (CRIS CAMHS) –opt out. ApproachWe compared demographic factors in the linked and unlinked populations when two cohorts, the MCS, and CRIS CAMHS data were linked to the National Pupil Database. The MCS is a birth cohort collecting prospective data on the social, economic and health-related circumstances of children surveyed at roughly two-yearly intervals from the age of 9 months. At age 7, parents were asked to consent for information from their child’s education records (via the UK Department for Education’s National Pupil Database, NPD) to linked to the MCS. Of the 9000 adults with parental responsibility, 8448 (93.9%) consented. The CRIS CAMHS sample is the UK's largest, anonymised clinical database for children and adolescents referred to South London child and adolescent mental health services, which is collected using opt out consent. All 35, 426 children were eligible for linkage to their educational data. ResultsFor MCS, 7446 (82.7% of the population) eligible children were successfully linked to NPD following opt in consent. After stratification into distinct geographical regions, London children in the most deprived quartile of neighbourhood deprivation were over twice as likely (O.R 2.5, C.I 1.18-5.3) not to have their educational records linked. For the opt out CRIS CAMHS cohort, 30,178 (85.1%) were linked, with no significant differences in linkage rates between children in the highest and lowest quartiles of deprivation (O.R 1.05, C.I 0.93-1.18). Relative to children of White ethnicity, Asian, Black African and Mixed ethnic groups were significantly less likely to be matched in both studies. Black Caribbean ethnicity was significantly associated with non-linkage in the MCS cohort (O.R 3.0, C.I 1.49-6.01), but not in CRIS CAMHS (0.96, C.I 0.83-1.12). ConclusionRecord linkages are a valuable enhancement to child-based longitudinal studies and clinical registries, allowing evaluation of questions relevant to public health and social care policy. Opt out consent approaches improve representation of more socially disadvantaged populations. Nevertheless, whether using opt in and opt out consent process, possible biases due to linkage error can be important and need to be addressed when analysing and interpreting results.

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.

Objectives People with vascular dementia (VaD) are frequently prescribed atypical antipsychotics to treat behavioural and psychological symptoms, but there is an alarming lack of evidence regarding their safety or efficacy in VaD. This study sought to identify the mortality risk associated with the most commonly prescribed atypical antipsychotics in people with VaD compared with people not exposed to these drugs. Methods A clinical cohort study of 1531 people with VaD performed using anonymised versions of full electronic health records from the Clinical Record Interactive Search application at the South London and Maudsley NHS Foundation Trust. Patients were identified from 2007 to 2010, of whom 337 were exposed to quetiapine, risperidone or olanzapine. The main outcome measure was mortality. Results Patients exposed to atypical antipsychotics were not at increased risk of mortality [hazard ratio (HR) 1.05, 95% confidence interval (CI): 0.87–1.26]. Exposure to risperidone did not result in an increased risk of mortality (HR = 0.85; 95% CI: 0.59–1.24), and patients exposed to quetiapine had a non-significant numerical increase in mortality risk (HR = 1.14; 95% CI: 0.93–1.39; p-value = 0.20) compared with untreated patients. Too few patients were exposed to olanzapine alone to provide reliable results. Conclusions The absence of a significant increase in mortality risk associated with atypical antipsychotics in people with VaD indicates that a clinical trial of antipsychotics focussing on the treatment of aggression and agitation in this patient group will be justified and feasible following further consideration of possible confounders, which will be critical to determine the role of antipsychotics in treatment of VaD. Copyright © 2014 John Wiley & Sons, Ltd.

Background Polypharmacy is common in real clinical practice and in pharma-sponsored clinical trials. Chlorpromazine equivalents do not take into account pharmacodynamic interactions of drug combinations. If there is a sufficiently deep calibration set available, bio-informatics approaches can build classifiers for clinical phenotypes. However, this is not always the case which severely limits the generalizability of the predictions. Methods We applied a mechanism-based computer model of a cortico-striatal-thalamocortical loop of the dorsal motor circuit that has been calibrated with clinical data on the prevalence of extrapyramidal symptoms after antipsychotic treatment in schizophrenia patients and therapeutic interventions in Parkinson’s patients[1]. The Quantitative Systems Pharmacology (QSP) model is based on the appropriate connections between basal ganglia regions and consists of 220 neurons (8 different cell types), 3500 synapses and implementations of 32 CNS active targets, based on their unique locations and coupling with intracellular pathways. Modulation of the various CNS targets were calculated on simulating the competition between the endogenous neurotransmitter and the two drugs at their appropriate concentrations and affinity. The model was challenged to blindly predict the extrapyramidal symptoms liability of 1,124 patients prescribed two antipsychotics for six or more months (772 unique combinations). Anonymized data were derived from South London and Maudsley NHS Foundation Trust (SLAM) electronic health records (EHR). Extrapyramidal side effects were captured and identified using a combination of Natural Language Processing and a bespoke algorithm [2]. Only names and doses of the two drugs were made available without any calibration set. Results Blind prediction of the outcomes using a Receiver Operating Characteristic curve with the QSP model resulted in an Area-Under-the Curve of 0.64 (p

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.

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.

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.

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.