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1.  Mini-Mental State Examination as a Predictor of Mortality among Older People Referred to Secondary Mental Healthcare 
PLoS ONE  2014;9(9):e105312.
Lower levels of cognitive function have been found to be associated with higher mortality in older people, particularly in dementia, but the association in people with other mental disorders is still inconclusive.
Methods and Findings
Data were analysed from a large mental health case register serving a geographic catchment of 1.23 million residents, and associations were investigated between cognitive function measured by the Mini-Mental State Examination (MMSE) and survival in patients aged 65 years old and over. Cox regressions were carried out, adjusting for age, gender, psychiatric diagnosis, ethnicity, marital status, and area-level socioeconomic index. A total of 6,704 subjects were involved, including 3,368 of them having a dementia diagnosis and 3,336 of them with depression or other diagnoses. Descriptive outcomes by Kaplan-Meier curves showed significant differences between those with normal and impaired cognitive function (MMSE score<25), regardless of a dementia diagnosis. As a whole, the group with lower cognitive function had an adjusted hazard ratio (HR) of 1.42 (95% CI: 1.28, 1.58) regardless of diagnosis. An HR of 1.23 (95% CI: 1.18, 1.28) per quintile increment of MMSE was also estimated after confounding control. A linear trend of MMSE in quintiles was observed for the subgroups of dementia and other non-dementia diagnoses (both p-values<0.001). However, a threshold effect of MMSE score under 20 was found for the specific diagnosis subgroups of depression.
Current study identified an association between cognitive impairment and increased mortality in older people using secondary mental health services regardless of a dementia diagnosis. Causal pathways between this exposure and outcome (for example, suboptimal healthcare) need further investigation.
PMCID: PMC4153564  PMID: 25184819
2.  Suicide completion in secondary mental healthcare: a comparison study between schizophrenia spectrum disorders and all other diagnoses 
BMC Psychiatry  2014;14(1):213.
Suicide completion is a tragic outcome in secondary mental healthcare. However, the extent to which demographic and clinical characteristics, suicide method and service use-related factors vary across psychiatric diagnoses remains poorly understood, particularly regarding differences between ‘schizophrenia spectrum disorders (SSD)’ and ‘all other diagnoses’, which may have implications for suicide prevention in high risk groups.
308 patients who died by suicide over 2007–2011 were identified from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre Case Register. Demographic, clinical, services use-related factors, ‘full risk assessment’ ratings and the Health of the Nation Outcome Scale (HONOS) scores were compared across psychiatric diagnoses. Specifically, differences between patients with and without SSD were investigated.
Patients with SSD ended their lives at a younger age, were more frequently of Black ethnicity and had higher levels of social deprivation than other diagnoses. Also, these patients were more likely to have HONOS and ‘risk assessment’ completed. However, patients who had no SSD scored significantly higher on ‘self-injury’ and ‘depression’ HONOS items and they were more likely to have the following ‘risk assessment’ items: ‘suicidal ideation’, ‘hopelessness’, ‘feeling no control of life’, ‘impulsivity’ and ‘significant loss’. Of note, ‘disengagement’ was more common in patients with SSD, although they had been seen by the staff closer to the time of suicide than in all-other diagnoses. Whilst ‘hanging’ was the most common suicide method amongst patients with non-SSD, most service users with a SSD diagnosis used ‘jumping’ (from heights or in front of a vehicle).
Suicide completion characteristics varied between SSD and other diagnoses in patients receiving secondary mental healthcare. In particular, although clinicians tend to more frequently recognize suicide risk as a focus of concern in patients who have SSD, who are therefore more likely to have a detailed risk assessment documented; ‘known’ suicide risk factors appear to be more relevant in patients with non-SSD. Hence, the classic suicide prevention model might be of little use for SSD.
PMCID: PMC4149212  PMID: 25085220
Suicide completion; Secondary mental healthcare; Schizophrenia spectrum disorders
3.  Predictors of Natural and Unnatural Mortality among Patients with Personality Disorder: Evidence from a Large UK Case Register 
PLoS ONE  2014;9(7):e100979.
People with personality disorder have reduced life expectancy, yet, within this population, little is known about the clinical predictors of natural and unnatural deaths. We set out to investigate this, using a large cohort of secondary mental health patients with personality disorder.
We identified patients with an ICD-10 diagnosis of personality disorder, aged ≥15 years in a large secondary mental healthcare case register. The case register was linked to national mortality tracing. Using Cox regression, we modelled the effect of a number of pre-specified clinical variables on all-cause, natural cause and unnatural cause mortality.
2,440 patients were identified. Eighty-five deaths (3.5% of cohort) occurred over a 5-year observation period, of which over 50% were from natural causes. All-cause mortality was associated with alcohol or drug use (adjusted Hazard Ratio [aHR] 2.3; 95% CI 1.3–4.1), physical illness (aHR 1.9; 95% CI 1.0–3.6), and functional impairment (aHR 1.9; 95% CI 1.0–3.6). Natural cause mortality was associated with mild problems of alcohol or drug use (aHR 3.4; 95% CI 1.5–7.4), and physical illness (aHR 2.4; 95% CI 1.0–5.6). Unnatural cause mortality was associated only with severe alcohol or drug use (aHR 3.1; 95% CI 1.3–7.3).
Alcohol and drug use, physical illness, and functional impairment are predictors of mortality in individuals with personality disorder. Clinicians should be aware of the existence of problems in these domains, even at mild levels, when assessing the needs of patients with personality disorder.
PMCID: PMC4085063  PMID: 25000503
4.  A cohort study on mental disorders, stage of cancer at diagnosis and subsequent survival 
BMJ Open  2014;4(1):e004295.
To assess the stage at cancer diagnosis and survival after cancer diagnosis among people served by secondary mental health services, compared with other local people.
Using the anonymised linkage between a regional monopoly secondary mental health service provider in southeast London of four London boroughs, Croydon, Lambeth, Lewisham and Southwark, and a population-based cancer register, a historical cohort study was constructed.
A total of 28 477 cancer cases aged 15+ years with stage of cancer recorded at diagnosis were identified. Among these, 2206 participants had been previously assessed or treated in secondary mental healthcare before their cancer diagnosis and 125 for severe mental illness (schizophrenia, schizoaffective or bipolar disorders).
Primary and secondary outcome measures
Stage when cancer was diagnosed and all-cause mortality after cancer diagnosis among cancer cases registered in the geographical area of southeast London.
Comparisons between people with and without specific psychiatric diagnosis in the same residence area for risks of advanced stage of cancer at diagnosis and general survival after cancer diagnosed were analysed using logistic and Cox models. No associations were found between specific mental disorder diagnoses and beyond local spread of cancer at presentation. However, people with severe mental disorders, depression, dementia and substance use disorders had significantly worse survival after cancer diagnosis, independent of cancer stage at diagnosis and other potential confounders.
Previous findings of associations between mental disorders and cancer mortality are more likely to be accounted for by differences in survival after cancer diagnosis rather than by delayed diagnosis.
PMCID: PMC3913023  PMID: 24477317
Cancer Stage at Diagnosis; Case Register Linkage; Severe Mental Illness; Survival
5.  Evaluation of Smoking Status Identification Using Electronic Health Records and Open-Text Information in a Large Mental Health Case Register 
PLoS ONE  2013;8(9):e74262.
High smoking prevalence is a major public health concern for people with mental disorders. Improved monitoring could be facilitated through electronic health record (EHR) databases. We evaluated whether EHR information held in structured fields might be usefully supplemented by open-text information. The prevalence and correlates of EHR-derived current smoking in people with severe mental illness were also investigated.
All cases had been referred to a secondary mental health service between 2008-2011 and received a diagnosis of schizophreniform or bipolar disorder. The study focused on those aged over 15 years who had received active care from the mental health service for at least a year (N=1,555). The ‘CRIS-IE-Smoking’ application used General Architecture for Text Engineering (GATE) natural language processing software to extract smoking status information from open-text fields. A combination of CRIS-IE-Smoking with data from structured fields was evaluated for coverage and the prevalence and demographic correlates of current smoking were analysed.
Proportions of patients with recorded smoking status increased from 11.6% to 64.0% through supplementing structured fields with CRIS-IE-Smoking data. The prevalence of current smoking was 59.6% in these 995 cases for whom this information was available. After adjustment, younger age (below 65 years), male sex, and non-cohabiting status were associated with current smoking status.
A natural language processing application substantially improved routine EHR data on smoking status above structured fields alone and could thus be helpful in improving monitoring of this lifestyle behaviour. However, limited information on smoking status remained a challenge.
PMCID: PMC3772070  PMID: 24069288
6.  Development and evaluation of a de-identification procedure for a case register sourced from mental health electronic records 
Electronic health records (EHRs) provide enormous potential for health research but also present data governance challenges. Ensuring de-identification is a pre-requisite for use of EHR data without prior consent. The South London and Maudsley NHS Trust (SLaM), one of the largest secondary mental healthcare providers in Europe, has developed, from its EHRs, a de-identified psychiatric case register, the Clinical Record Interactive Search (CRIS), for secondary research.
We describe development, implementation and evaluation of a bespoke de-identification algorithm used to create the register. It is designed to create dictionaries using patient identifiers (PIs) entered into dedicated source fields and then identify, match and mask them (with ZZZZZ) when they appear in medical texts. We deemed this approach would be effective, given high coverage of PI in the dedicated fields and the effectiveness of the masking combined with elements of a security model. We conducted two separate performance tests i) to test performance of the algorithm in masking individual true PIs entered in dedicated fields and then found in text (using 500 patient notes) and ii) to compare the performance of the CRIS pattern matching algorithm with a machine learning algorithm, called the MITRE Identification Scrubber Toolkit – MIST (using 70 patient notes – 50 notes to train, 20 notes to test on). We also report any incidences of potential breaches, defined by occurrences of 3 or more true or apparent PIs in the same patient’s notes (and in an additional set of longitudinal notes for 50 patients); and we consider the possibility of inferring information despite de-identification.
True PIs were masked with 98.8% precision and 97.6% recall. As anticipated, potential PIs did appear, owing to misspellings entered within the EHRs. We found one potential breach. In a separate performance test, with a different set of notes, CRIS yielded 100% precision and 88.5% recall, while MIST yielded a 95.1% and 78.1%, respectively. We discuss how we overcome the realistic possibility – albeit of low probability – of potential breaches through implementation of the security model.
CRIS is a de-identified psychiatric database sourced from EHRs, which protects patient anonymity and maximises data available for research. CRIS demonstrates the advantage of combining an effective de-identification algorithm with a carefully designed security model. The paper advances much needed discussion of EHR de-identification – particularly in relation to criteria to assess de-identification, and considering the contexts of de-identified research databases when assessing the risk of breaches of confidential patient information.
PMCID: PMC3751474  PMID: 23842533
De-identification; Anonymisation; Electronic health records; Psychiatric case register; Medical health records security; Medical information database security
7.  Abuse and other correlates of common mental disorders in youth: a cross-sectional study in Goa, India 
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.
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.
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.
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.
PMCID: PMC3597274  PMID: 23111769
Youth; 16–24 years; Common mental disorders; India; Community survey
8.  Functional Status and All-Cause Mortality in Serious Mental Illness 
PLoS ONE  2012;7(9):e44613.
Serious mental illness can affect many aspects of an individual’s ability to function in daily life. The aim of this investigation was to determine if the environmental and functional status of people with serious mental illness contribute to the high mortality risk observed in this patient group.
We identified cases of 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 activities of daily living (ADLs), living conditions, occupational and recreational activities and relationship factors (Health of the Nation Outcome Scale [HoNOS] subscales) on all-cause mortality over a 4-year observation period (2007–10) using Cox regression.
We identified 6,880 SMI cases (242 deaths) in the observation period. ADL impairment was associated with an increased risk of all-cause mortality (adjusted HR 1.9; 95% CI 1.3–2.8; p = 0.001, p for trend across ADL categories = 0.001) after controlling for a broad range of covariates (including demographic factors, physical health, mental health symptoms and behaviours, socio-economic status and mental health service contact). No associations were found for the other three exposures. Stratification by age indicated that ADLs were most strongly associated with mortality in the youngest (15 to <35 years) and oldest (≥55 years) groups.
Functional impairment in people with serious mental illness diagnoses is a marker of increased mortality risk, possibly in younger age groups as a marker of negative symptomatology.
PMCID: PMC3435298  PMID: 22970266
9.  Phytozome: a comparative platform for green plant genomics 
Nucleic Acids Research  2011;40(Database issue):D1178-D1186.
The number of sequenced plant genomes and associated genomic resources is growing rapidly with the advent of both an increased focus on plant genomics from funding agencies, and the application of inexpensive next generation sequencing. To interact with this increasing body of data, we have developed Phytozome (, a comparative hub for plant genome and gene family data and analysis. Phytozome provides a view of the evolutionary history of every plant gene at the level of sequence, gene structure, gene family and genome organization, while at the same time providing access to the sequences and functional annotations of a growing number (currently 25) of complete plant genomes, including all the land plants and selected algae sequenced at the Joint Genome Institute, as well as selected species sequenced elsewhere. Through a comprehensive plant genome database and web portal, these data and analyses are available to the broader plant science research community, providing powerful comparative genomics tools that help to link model systems with other plants of economic and ecological importance.
PMCID: PMC3245001  PMID: 22110026
10.  Life Expectancy at Birth for People with Serious Mental Illness and Other Major Disorders from a Secondary Mental Health Care Case Register in London 
PLoS ONE  2011;6(5):e19590.
Despite improving healthcare, the gap in mortality between people with serious mental illness (SMI) and general population persists, especially for younger age groups. The electronic database from a large and comprehensive secondary mental healthcare provider in London was utilized to assess the impact of SMI diagnoses on life expectancy at birth.
People who were diagnosed with SMI (schizophrenia, schizoaffective disorder, bipolar disorder), substance use disorder, and depressive episode/disorder before the end of 2009 and under active review by the South London and Maudsley NHS Foundation Trust (SLAM) in southeast London during 2007–09 comprised the sample, retrieved by the SLAM Case Register Interactive Search (CRIS) system. We estimated life expectancy at birth for people with SMI and each diagnosis, from national mortality returns between 2007–09, using a life table method.
A total of 31,719 eligible people, aged 15 years or older, with SMI were analyzed. Among them, 1,370 died during 2007–09. Compared to national figures, all disorders were associated with substantially lower life expectancy: 8.0 to 14.6 life years lost for men and 9.8 to 17.5 life years lost for women. Highest reductions were found for men with schizophrenia (14.6 years lost) and women with schizoaffective disorders (17.5 years lost).
The impact of serious mental illness on life expectancy is marked and generally higher than similarly calculated impacts of well-recognised adverse exposures such as smoking, diabetes and obesity. Strategies to identify and prevent causes of premature death are urgently required.
PMCID: PMC3097201  PMID: 21611123
11.  Psychiatric disorder in early adulthood and risk of premature mortality in the 1946 British Birth Cohort 
BMC Psychiatry  2011;11:37.
Few studies of the association between psychiatric disorder and premature death have adjusted for key confounders and used structured psychiatric interviews. We aimed to investigate if psychiatric disorder was associated with a higher risk of mortality and whether any excess mortality was due to suicide, or explained by other health or socioeconomic risk factors.
We used data from the MRC National Survey of Health and Development, a nationally representative UK birth cohort. 3283 men and women completed the Present State Examination at age 36. The main outcome measure was all-cause mortality before age 60.
Those with psychiatric disorder at age 36 had a higher risk of death even after adjusting for potential confounders (Hazard ratio = 1.84, 95% C.I. 1.22-2.78). Censoring violent deaths and suicides led to similar results.
Psychiatric disorder was associated with excess premature mortality not explained by suicide or other health or socioeconomic risk factors.
PMCID: PMC3062592  PMID: 21385445
12.  All-cause mortality among people with serious mental illness (SMI), substance use disorders, and depressive disorders in southeast London: a cohort study 
BMC Psychiatry  2010;10:77.
Higher mortality has been found for people with serious mental illness (SMI, including schizophrenia, schizoaffective disorders, and bipolar affective disorder) at all age groups. Our aim was to characterize vulnerable groups for excess mortality among people with SMI, substance use disorders, depressive episode, and recurrent depressive disorder.
A case register was developed at the South London and Maudsley National Health Services Foundation Trust (NHS SLAM), accessing full electronic clinical records on over 150,000 mental health service users as a well-defined cohort since 2006. The Case Register Interactive Search (CRIS) system enabled searching and retrieval of anonymised information since 2008. Deaths were identified by regular national tracing returns after 2006. Standardized mortality ratios (SMRs) were calculated for the period 2007 to 2009 using SLAM records for this period and the expected number of deaths from age-specific mortality statistics for the England and Wales population in 2008. Data were stratified by gender, ethnicity, and specific mental disorders.
A total of 31,719 cases, aged 15 years old or more, active between 2007-2009 and with mental disorders of interest prior to 2009 were detected in the SLAM case register. SMRs were 2.15 (95% CI: 1.95-2.36) for all SMI with genders combined, 1.89 (1.64-2.17) for women and 2.47 (2.17-2.80) for men. In addition, highest mortality risk was found for substance use disorders (SMR = 4.17; 95% CI: 3.75-4.64). Age- and gender-standardised mortality ratios by ethnic group revealed huge fluctuations, and SMRs for all disorders diminished in strength with age. The main limitation was the setting of secondary mental health care provider in SLAM.
Substantially higher mortality persists in people with serious mental illness, substance use disorders and depressive disorders. Furthermore, mortality risk differs substantially with age, diagnosis, gender and ethnicity. Further research into specific risk groups is required.
PMCID: PMC2958993  PMID: 20920287
13.  Draft Genome Sequence of the Sexually Transmitted Pathogen Trichomonas vaginalis 
Science (New York, N.Y.)  2007;315(5809):207-212.
We describe the genome sequence of the protist Trichomonas vaginalis, a sexually transmitted human pathogen. Repeats and transposable elements comprise about two-thirds of the ~160-megabase genome, reflecting a recent massive expansion of genetic material. This expansion, in conjunction with the shaping of metabolic pathways that likely transpired through lateral gene transfer from bacteria, and amplification of specific gene families implicated in pathogenesis and phagocytosis of host proteins may exemplify adaptations of the parasite during its transition to a urogenital environment. The genome sequence predicts previously unknown functions for the hydrogenosome, which support a common evolutionary origin of this unusual organelle with mitochondria.
PMCID: PMC2080659  PMID: 17218520

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