Purpose The South London and Maudsley National Health Service (NHS) Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive Search (CRIS) application were developed in 2008, generating a research repository of real-time, anonymised, structured and open-text data derived from the electronic health record system used by SLaM, a large mental healthcare provider in southeast London. In this paper, we update this 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 to extract structured data from open-text fields, linkages to external sources of data, and the addition of a parallel relational database (Structured Query Language) 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 attendances and cancer registrations. Future plans Coupled with robust data security and governance structures, electronic health records provide potentially transformative information on mental 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 to enhance 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.

We sought to develop (11)C-labeled ligands for sensitive imaging of brain peripheral benzodiazepine receptors (PBR) in vivo. Two aryloxyanilides with high affinity for PBR were identified and synthesized, namely, N-acetyl- N-(2-methoxycarbonylbenzyl)-2-phenoxyaniline ( 3, PBR01) and N-(2-methoxybenzyl)- N-(4-phenoxypyridin-3-yl)acetamide ( 10, PBR28). 3 was hydrolyzed to 4, which was esterified with [ (11)C]iodomethane to provide [ (11)C] 3. The O-desmethyl analogue of 10 was converted into [ (11)C] 10 with [ (11)C]iodomethane. [ (11)C] 3 and [ (11)C] 10 were each injected into monkey to assess their brain kinetics with positron emission tomography (PET). After administration of either radioligand there was moderately high brain uptake of radioactivity. Receptor blocking and displacement experiments showed that a high proportion of this radioactivity was bound specifically to PBR. In monkey and rat, 3 and 10 were rapidly metabolized by ester hydrolysis and N-debenzylation, respectively, each to a single polar radiometabolite. [ (11)C] 3 and [ (11)C] 10 are effective for imaging PBR in monkey brain. [ (11)C] 10 especially warrants further evaluation in human subjects.

The measurements with (1)H-MRS of absolute metabolite concentrations in the neocortex showed abnormal concentrations of brain metabolites in AD; these metabolite concentrations do not necessarily correlate with disease severity. Although changes in myo-inositol and creatine occur in the early stages of AD, abnormalities of N-acetyl aspartate do not occur in mild AD but progressively change with dementia severity. Further, subjects with mild AD can be differentiated from controls with (1)H-MRS.

Significant risk enrichment occurs before individuals are assessed for a suspected CHR state. Race/ethnicity and source of referral are associated with pretest risk enrichment in individuals undergoing CHR assessment. A stratification model can identify individuals at differential pretest risk of psychosis. Identification of these subgroups may inform outreach campaigns and subsequent testing and eventually optimize psychosis prediction.

ObjectivesMood instability is a clinically important phenomenon but has received relatively little research attention. The objective of this study was to assess the impact of mood instability on clinical outcomes in a large sample of people receiving secondary mental healthcare.DesignObservational study using an anonymised electronic health record case register.SettingSouth London and Maudsley NHS Trust (SLaM), a large provider of inpatient and community mental healthcare in the UK.Participants27 704 adults presenting to SLaM between April 2006 and March 2013 with a psychotic, affective or personality disorder.ExposureThe presence of mood instability within 1 month of presentation, identified using natural language processing (NLP).Main outcome measuresThe number of days spent in hospital, frequency of hospital admission, compulsory hospital admission and prescription of antipsychotics or non-antipsychotic mood stabilisers over a 5-year follow-up period.ResultsMood instability was documented in 12.1% of people presenting to mental healthcare services. It was most frequently documented in people with bipolar disorder (22.6%), but was common in people with personality disorder (17.8%) and schizophrenia (15.5%). It was associated with a greater number of days spent in hospital (β coefficient 18.5, 95% CI 12.1 to 24.8), greater frequency of hospitalisation (incidence rate ratio 1.95, 1.75 to 2.17), greater likelihood of compulsory admission (OR 2.73, 2.34 to 3.19) and an increased likelihood of prescription of antipsychotics (2.03, 1.75 to 2.35) or non-antipsychotic mood stabilisers (2.07, 1.77 to 2.41).ConclusionsMood instability occurs in a wide range of mental disorders and is not limited to affective disorders. It is generally associated with relatively poor clinical outcomes. These findings suggest that clinicians should screen for mood instability across all common mental health disorders. The data also suggest that targeted interventions for mood instability may be useful in patients who do not have a formal affective disorder.

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.

BackgroundBipolar disorder is a significant cause of morbidity and mortality. Although existing treatments are effective, there is often a substantial delay before diagnosis and treatment initiation. We sought to investigate factors associated with the delay before diagnosis of bipolar disorder and the onset of treatment in secondary mental healthcare.MethodRetrospective cohort study using anonymised electronic mental health record data from the South London and Maudsley NHS Foundation Trust (SLaM) Biomedical Research Centre (BRC) Case Register on 1364 adults diagnosed with bipolar disorder between 2007 and 2012. The following predictor variables were analysed in a multivariable Cox regression analysis: age, gender, ethnicity, compulsory admission to hospital under the UK Mental Health Act, marital status and other diagnoses prior to bipolar disorder. The outcomes were time to recorded diagnosis from first presentation to specialist mental health services (the diagnostic delay), and time to the start of appropriate therapy (treatment delay).ResultsThe median diagnostic delay was 62 days (interquartile range: 17–243) and median treatment delay was 31 days (4–122). Compulsory hospital admission was associated with a significant reduction in both diagnostic delay (hazard ratio 2.58, 95% CI 2.18–3.06) and treatment delay (4.40, 3.63–5.62). Prior diagnoses of other psychiatric disorders were associated with increased diagnostic delay, particularly alcohol (0.48, 0.33–0.41) and substance misuse disorders (0.44, 0.31–0.61). Prior diagnosis of schizophrenia and psychotic depression were associated with reduced treatment delay.ConclusionsSome individuals experience a significant delay in diagnosis and treatment of bipolar disorder after initiation of specialist mental healthcare, particularly those who have prior diagnoses of alcohol and substance misuse disorders. These findings highlight a need for further study on strategies to better identify underlying symptoms and offer appropriate treatment sooner in order to facilitate improved clinical outcomes, such as developing specialist early intervention services to identify and treat people with bipolar disorder.

Objective To investigate whether cannabis use is associated with increased risk of relapse, as indexed by number of hospital admissions, and whether antipsychotic treatment failure, as indexed by number of unique antipsychotics prescribed, may mediate this effect in a large data set of patients with first episode psychosis (FEP). Design Observational study with exploratory mediation analysis. Setting Anonymised electronic mental health record data from the South London and Maudsley NHS Foundation Trust. Participants 2026 people presenting to early intervention services with FEP. Exposure Cannabis use at presentation, identified using natural language processing. Main outcome measures admission to psychiatric hospital and clozapine prescription up to 5 years following presentation. Mediator Number of unique antipsychotics prescribed. Results Cannabis use was present in 46.3% of the sample at first presentation and was particularly common in patients who were 16–25, male and single. It was associated with increased frequency of hospital admission (incidence rate ratio 1.50, 95% CI 1.25 to 1.80), increased likelihood of compulsory admission (OR 1.55, 1.16 to 2.08) and greater number of days spent in hospital (β coefficient 35.1 days, 12.1 to 58.1). The number of unique antipsychotics prescribed, mediated increased frequency of hospital admission (natural indirect effect 1.09, 95% CI 1.01 to 1.18; total effect 1.50, 1.21 to 1.87), increased likelihood of compulsory admission (natural indirect effect (NIE) 1.27, 1.03 to 1.58; total effect (TE) 1.76, 0.81 to 3.84) and greater number of days spent in hospital (NIE 17.9, 2.4 to 33.4; TE 34.8, 11.6 to 58.1). Conclusions Cannabis use in patients with FEP was associated with an increased likelihood of hospital admission. This was linked to the prescription of several different antipsychotic drugs, indicating clinical judgement of antipsychotic treatment failure. Together, this suggests that cannabis use might be associated with worse clinical outcomes in psychosis by contributing towards failure of antipsychotic treatment.