A transdiagnostic prodrome for severe mental disorders: an electronic health record study.

Effective prevention of severe mental disorders (SMD), including non-psychotic unipolar mood disorders (UMD), non-psychotic bipolar mood disorders (BMD), and psychotic disorders (PSY), rely on accurate knowledge of the duration, first presentation, time course and transdiagnosticity of their prodromal stages. Here we present a retrospective, real-world, cohort study using electronic health records, adhering to RECORD guidelines. Natural language processing algorithms were used to extract monthly occurrences of 65 prodromal features (symptoms and substance use), grouped into eight prodromal clusters. The duration, first presentation, and transdiagnosticity of the prodrome were compared between SMD groups with one-way ANOVA, Cohen's f and d. The time course (mean occurrences) of prodromal clusters was compared between SMD groups with linear mixed-effects models. 26,975 individuals diagnosed with ICD-10 SMD were followed up for up to 12 years (UMD = 13,422; BMD = 2506; PSY = 11,047; median[IQR] age 39.8[23.7] years; 55% female; 52% white). The duration of the UMD prodrome (18[36] months) was shorter than BMD (26[35], d = 0.21) and PSY (24[38], d = 0.18). Most individuals presented with multiple first prodromal clusters, with the most common being non-specific ('other'; 88% UMD, 85% BMD, 78% PSY). The only first prodromal cluster that showed a medium-sized difference between the three SMD groups was positive symptoms (f = 0.30). Time course analysis showed an increase in prodromal cluster occurrences approaching SMD onset. Feature occurrence across the prodromal period showed small/negligible differences between SMD groups, suggesting that most features are transdiagnostic, except for positive symptoms (e.g. paranoia, f = 0.40). Taken together, our findings show minimal differences in the duration and first presentation of the SMD prodromes as recorded in secondary mental health care. All the prodromal clusters intensified as individuals approached SMD onset, and all the prodromal features other than positive symptoms are transdiagnostic. These results support proposals to develop transdiagnostic preventive services for affective and psychotic disorders detected in secondary mental healthcare.

Life expectancy, mortality risks and cause of death in patients with serious mental illness in South East London: a comparison between 2008-2012 and 2013-2017.

BACKGROUND: People with serious mental illness (SMI) have a significantly shorter life expectancy than the general population. This study investigates whether the mortality rate in this group has changed over the last decade. METHODS: Using Clinical Record Interactive Search software, we extracted data from a large electronic database of patients in South East London. All patients with schizophrenia, schizoaffective disorder or bipolar disorder from 2008 to 2012 and/or 2013 to 2017 were included. Estimates of life expectancy at birth, standardised mortality ratios and causes of death were obtained for each cohort according to diagnosis and gender. Comparisons were made between cohorts and with the general population using data obtained from the UK Office of National Statistics. RESULTS: In total, 26 005 patients were included. In men, life expectancy was greater in 2013-2017 (64.9 years; 95% CI 63.6-66.3) than in 2008-2012 (63.2 years; 95% CI 61.5-64.9). Similarly, in women, life expectancy was greater in 2013-2017 (69.1 years; 95% CI 67.5-70.7) than in 2008-2012 (68.1 years; 95% CI 66.2-69.9). The difference with general population life expectancy fell by 0.9 years between cohorts in men, and 0.5 years in women. In the 2013-2017 cohorts, cancer accounted for a similar proportion of deaths as cardiovascular disease. CONCLUSIONS: Relative to the general population, life expectancy for people with SMI is still much worse, though it appears to be improving. The increased cancer-related mortality suggests that physical health monitoring should consider including cancer as well.

The association between early childhood onset epilepsy and attention-deficit hyperactivity disorder (ADHD) in 3237 children and adolescents with Autism Spectrum Disorder (ASD): a historical longitudinal cohort data linkage study.

Children and young people with Autism Spectrum Disorder (ASD) have an increased risk of comorbidities, such as epilepsy and Attention-Deficit/Hyperactivity Disorder (ADHD). However, little is known about the relationship between early childhood epilepsy (below age 7) and later ADHD diagnosis (at age 7 or above) in ASD. In this historical cohort study, we examined this relationship using an innovative data source, which included linked data from routinely collected acute hospital paediatric records and childhood community and inpatient psychiatric records. In a large sample of children and young people with ASD (N = 3237), we conducted a longitudinal analysis to examine early childhood epilepsy as a risk factor for ADHD diagnosis while adjusting for potential confounders, including socio-demographic characteristics, intellectual disability, family history of epilepsy and associated physical conditions. We found that ASD children and young people diagnosed with early childhood epilepsy had nearly a twofold increase in risk of developing ADHD later in life, an association which persisted after adjusting for potential confounders (adjusted OR = 1.72, CI95% = 1.13-2.62). This study suggests that sensitive monitoring of ADHD symptoms in children with ASD who have a history of childhood epilepsy may be important to promote early detection and treatment. It also highlights how linked electronic health records can be used to examine potential risk factors over time for multimorbidity in neurodevelopmental conditions.

Antidepressant and antipsychotic treatment of Psychotic Major Depression in a British mental healthcare setting.

BACKGROUND: Evidence from treatment trials shows that the most effective pharmacological treatment for Psychotic Major Depression (PMD) is combined antidepressant and antipsychotic pharmacotherapy. AIM: This study investigates the use of antidepressant and antipsychotic treatment for PMD in clinical practice and examines how treatment profiles correlate with demographic and clinical symptoms. METHOD: Anonymised electronic health records of 2,837 individuals with PMD were followed up for 12-months post-diagnosis in a historic open cohort design. The use of antidepressants and antipsychotics, alone or in combination, were described using frequency statistics. Demographic and clinical characteristics associated with each treatment were assessed using logistic regression analyses. RESULTS: Antidepressant and antipsychotic combination pharmacotherapy was the most used treatment for PMD with 69.9% users, compared to antidepressant monotherapy (10.9%) and antipsychotic monotherapy (10.3%). The remaining 8.9% of individuals did not receive antidepressant or antipsychotic treatment. The presence of delusions was strongly associated with the use of antipsychotics, both alone (odds ratio =3.99, 95% confidence intervals = 2.72-5.83, p<.001) and in combination with antidepressants (OR = 2.7, 95% CI = 2.09-3.67, p<.001), rather than antidepressant treatment alone. CONCLUSIONS: Combined antidepressant and antipsychotic pharmacotherapy is the most common treatment of PMD in clinical practice, showing that clinical practice is in line with evidence from treatment research.

Ethnic inequalities in clozapine use among people with treatment-resistant schizophrenia: a retrospective cohort study using data from electronic clinical records.

PURPOSE: Clozapine is the most effective intervention for treatment-resistant schizophrenia (TRS). Several studies report ethnic disparities in clozapine treatment. However, few studies restrict analyses to TRS cohorts alone or address confounding by benign ethnic neutropenia. This study investigates ethnic equity in access to clozapine treatment for people with treatment-resistant schizophrenia spectrum disorder. METHODS: A retrospective cohort study, using information from 11 years of clinical records (2007-2017) from the South London and Maudsley NHS Trust. We identified a cohort of service-users with TRS using a validated algorithm. We investigated associations between ethnicity and clozapine treatment, adjusting for sociodemographic factors, psychiatric multi-morbidity, substance misuse, neutropenia, and service-use. RESULTS: Among 2239 cases of TRS, Black service-users were less likely to be receive clozapine compared with White British service-users after adjusting for confounders (Black African aOR = 0.49, 95% CI [0.33, 0.74], p = 0.001; Black Caribbean aOR = 0.64, 95% CI [0.43, 0.93], p = 0.019; Black British aOR = 0.61, 95% CI [0.41, 0.91], p = 0.016). It was additionally observed that neutropenia was not related to treatment with clozapine. Also, a detention under the Mental Health Act was negatively associated clozapine receipt, suggesting people with TRS who were detained are less likely to be treated with clozapine. CONCLUSION: Black service-users with TRS were less likely to receive clozapine than White British service-users. Considering the protective effect of treatment with clozapine, these inequities may place Black service-users at higher risk for hospital admissions and mortality.

Augmentation of clozapine with ECT: a retrospective case analysis.

OBJECTIVE: We sought to assess the effectiveness of clozapine augmentation with Electroconvulsive therapy (ECT) (C+ECT) in patients with clozapine-resistant schizophrenia. METHODS: We conducted a retrospective review of electronic health records to identify patients treated with C+ECT. We determined the response to C+ECT and the rate of rehospitalisation over the year following treatment with C+ECT. RESULTS: Forty-two patients were treated with C+ECT over a 10-year period. The mean age of the patients at initiation of ECT was 46.3 (SD = 8.2) years (range 27-62 years). The mean number of ECTs given was 10.6 (SD = 5.3) (range 3-25) with the majority receiving twice weekly ECT. Seventy-six per cent of patients (n = 32) showed a Clinical Global Impression-Improvement (CGI-I) score of ≤3 (at least minimally improved) following C+ECT. The mean number of ECT treatments was 10.6 (SD = 5.3) (range 3-25) with the majority receiving twice weekly ECT. Sixty-four per cent of patients experienced no adverse events. Response to C+ECT was not associated with gender, age, duration of illness or duration of clozapine treatment. Seventy-five per cent of responders remained out of hospital over the course of 1-year follow-up, while 70% of those with no response to C+ECT were not admitted to hospital. Three patients received maintenance ECT, one of whom was rehospitalised. CONCLUSION: This study lends support to emerging evidence for the effectiveness of C+ECT in clozapine-resistant schizophrenia. These results are consistent with the results of a meta-analysis and the only randomised controlled trial (RCT) of this intervention. Further RCTs are required before this treatment can be confidently recommended.

Severe mental illness diagnosis in English general hospitals 2006-2017: A registry linkage study.

BACKGROUND: The higher mortality rates in people with severe mental illness (SMI) may be partly due to inadequate integration of physical and mental healthcare. Accurate recording of SMI during hospital admissions has the potential to facilitate integrated care including tailoring of treatment to account for comorbidities. We therefore aimed to investigate the sensitivity of SMI recording within general hospitals, changes in diagnostic accuracy over time, and factors associated with accurate recording. METHODS AND FINDINGS: We undertook a cohort study of 13,786 adults with SMI diagnosed during 2006-2017, using data from a large secondary mental healthcare database as reference standard, linked to English national records for 45,706 emergency hospital admissions. We examined general hospital record sensitivity across patients' subsequent hospital records, for each subsequent emergency admission, and at different levels of diagnostic precision. We analyzed time trends during the study period and used logistic regression to examine sociodemographic and clinical factors associated with psychiatric recording accuracy, with multiple imputation for missing data. Sensitivity for recording of SMI as any mental health diagnosis was 76.7% (95% CI 76.0-77.4). Category-level sensitivity (e.g., proportion of individuals with schizophrenia spectrum disorders (F20-29) who received any F20-29 diagnosis in hospital records) was 56.4% (95% CI 55.4-57.4) for schizophrenia spectrum disorder and 49.7% (95% CI 48.1-51.3) for bipolar affective disorder. Sensitivity for SMI recording in emergency admissions increased from 47.8% (95% CI 43.1-52.5) in 2006 to 75.4% (95% CI 68.3-81.4) in 2017 (ptrend < 0.001). Minority ethnicity, being married, and having better mental and physical health were associated with less accurate diagnostic recording. The main limitation of our study is the potential for misclassification of diagnosis in the reference-standard mental healthcare data. CONCLUSIONS: Our findings suggest that there have been improvements in recording of SMI diagnoses, but concerning under-recording, especially in minority ethnic groups, persists. Training in culturally sensitive diagnosis, expansion of liaison psychiatry input in general hospitals, and improved data sharing between physical and mental health services may be required to reduce inequalities in diagnostic practice.

Suicide attempts requiring hospitalization in patients with eating disorders: A retrospective cohort study.

OBJECTIVE: Suicide attempts requiring hospitalization are known to be common in patients who are diagnosed with eating disorders. Attempting suicide is a major indicator for those at risk of completed suicide. Both the specific eating disorder diagnosis and the influence of psychiatric comorbidities on suicide attempts requiring hospitalization were investigated, with demographic and socioeconomic variables as confounders, over a 10-year observation period from January 2007 to March 2017. METHODS: Anonymized health-record data from the South London and Maudsley NHS Foundation Trust (SLaM) were retrieved through the Clinical Record Interactive Search (CRIS) data resource; this is linked to national Hospital Episode Statistics (HES) data. These data include all diagnoses for inpatient admissions. Hazard ratios, with 95% confidence intervals (CIs), were calculated from cox regression analyses and the effects of a number of confounders were estimated by performing multivariable analyses. RESULTS: In total, 4,895 patients were diagnosed with anorexia nervosa (AN), bulimia nervosa (BN), or eating disorder otherwise not specified (EDNOS). Of these, 331 (6.7%) had attempted suicide requiring hospitalization and 21 (0.04%) completed suicide. The eating disorder category associated with the highest risk of a suicide attempt was AN (HR: 1.43, 95%CI: 1.08-1.89, p = .01). The risk was significantly increased further if the patient had a comorbid diagnosis of personality disorder, depression, bipolar affective disorder, and substance misuse. DISCUSSION: Suicide attempts requiring hospitalization have a high incidence rate among patients with eating disorders, and the risk is significantly increased in AN. Comorbid psychiatric illness and suicidal ideation should be carefully assessed in all eating disorder patients.

Diagnostic trajectories in child and adolescent mental health services: exploring the prevalence and patterns of diagnostic adjustments in an electronic mental health case register.

Community-based epidemiological studies show transitions between psychiatric disorders are common during child development. However, little research has explored the prevalence or patterns of the diagnostic adjustments that occur in child and adolescent mental health services (CAMHS). Understanding diagnostic trajectories is necessary to inform theory development in developmental psychopathology and clinical judgements regarding risk and prognosis. In this study, data from CAMHS clinical records were extracted from a British mental health case register (N = 12,543). Analysis calculated the proportion of children whose clinical records showed a longitudinal diagnostic adjustment (i.e. addition of a subsequent diagnosis of a different diagnostic class, at > 30 days' distance from their first diagnosis). Regression analyses investigated typical diagnostic sequences and their relationships with socio-demographic variables, service use and standardised measures of mental health. Analysis found that 19.3% of CAMHS attendees had undergone a longitudinal diagnostic adjustment. Ethnicity, diagnostic class and symptom profiles significantly influenced the likelihood of a diagnostic adjustment. Affective and anxiety/stress-related disorders longitudinally predicted each other, as did hyperkinetic and conduct disorders, and hyperkinetic and pervasive developmental disorders. Results suggest that approximately one in five young service users have their original psychiatric diagnosis revised or supplemented during their time in CAMHS. By revealing the most common diagnostic sequences, this study enables policy makers to anticipate future service needs and clinicians to make informed projections about their patients' likely trajectories. Further research is required to understand how young people experience diagnostic adjustments and their psychological and pragmatic implications.

Psychiatric comorbidity as a risk factor for mortality in people with anorexia nervosa.

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 1970 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.

Psychiatric comorbidity as a risk factor for the mortality of people with bulimia nervosa.

BACKGROUND: 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. METHODS: 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. RESULTS: 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. CONCLUSIONS: These results highlight increased mortality in patients with BN and the importance of recognising and treating PDs in patients with BN.

Associations of acetylcholinesterase inhibitor treatment with reduced mortality in Alzheimer's disease: a retrospective survival analysis.

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.

Can risk assessment predict suicide in secondary mental healthcare? Findings from the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register.

PURPOSE: The predictive value of suicide risk assessment in secondary mental healthcare remains unclear. This study aimed to investigate the extent to which clinical risk assessment ratings can predict suicide among people receiving secondary mental healthcare. METHODS: Retrospective inception cohort study (n = 13,758) from the South London and Maudsley NHS Foundation Trust (SLaM) (London, UK) linked with national mortality data (n = 81 suicides). Cox regression models assessed survival from the last suicide risk assessment and ROC curves evaluated the performance of risk assessment total scores. RESULTS: Hopelessness (RR = 2.24, 95% CI 1.05-4.80, p = 0.037) and having a significant loss (RR = 1.91, 95% CI 1.03-3.55, p = 0.041) were significantly associated with suicide in the multivariable Cox regression models. However, screening statistics for the best cut-off point (4-5) of the risk assessment total score were: sensitivity 0.65 (95% CI 0.54-0.76), specificity 0.62 (95% CI 0.62-0.63), positive predictive value 0.01 (95% CI 0.01-0.01) and negative predictive value 0.99 (95% CI 0.99-1.00). CONCLUSIONS: Although suicide was linked with hopelessness and having a significant loss, risk assessment performed poorly to predict such an uncommon outcome in a large case register of patients receiving secondary mental healthcare.

Inpatient use and area-level socio-environmental factors in people with psychosis.

PURPOSE: There is consistent evidence that socio-environmental factors measured at an area-level, such as ethnic density, urban environment and deprivation are associated with psychosis risk. However, whether area-level socio-environmental factors are associated with outcomes following psychosis onset is less clear. This study aimed to examine whether the number of inpatient days used by people presenting to mental health services for psychosis was associated with five key area-level socio-environmental factors: deprivation, ethnic density, social capital, population density and social fragmentation. METHODS: Using a historical cohort design based on electronic health records from the South London and Maudsley NHS Trust Foundation electronic Patient Journey System, people who presented for the first time to SLAM between 2007 and 2010 with psychosis were included. Structured data were extracted on age at presentation, gender, ethnicity, residential area at first presentation and number of inpatient days over 5 years of follow-up. Data on area-level socio-environmental factors taken from published sources were linked to participants' residential addresses. The relationship between the number of inpatient days and each socio-environmental factor was investigated in univariate negative binomial regression models with time in contact with services treated as an offset variable. RESULTS: A total of 2147 people had full data on area level outcomes and baseline demographics, thus, could be included in the full analysis. No area-level socio-environmental factors were associated with inpatient days. CONCLUSION: Although a robust association exists between socio-environmental factors and psychosis risk, in this study we found no evidence that neighbourhood deprivation was linked to future inpatient admissions following the onset of psychosis. Future work on the influence of area-level socio-environmental factors on outcome should examine more nuanced outcomes, e.g. recovery, symptom trajectory, and should account for key methodological challenges, e.g. accounting for changes in address.

Cannabis use and treatment resistance in first episode psychosis: a natural language processing study.

BACKGROUND: Cannabis is frequently used among individuals with first episode psychosis and is associated with poor clinical outcomes. However, little is known about the effect of cannabis use on the response to antipsychotic medications and how use could affect outcomes. Using natural language processing on clinical data from a large electronic case register, we sought to investigate whether resistance to antipsychotic treatment mediated poor clinical outcomes associated with cannabis use. METHODS: Data were obtained from 2026 people with first episode psychosis in south London, UK. Cannabis use documented in free text clinical records was identified with natural language processing. Data for age, sex, ethnicity, marital status, psychotic disorder diagnosis, subsequent hospital admission, and number of unique antipsychotic medications prescribed were obtained using the Clinical Record Interactive Search instrument. The association of these variables with cannabis use was analysed with multivariable regression and mediation analysis. FINDINGS: 939 people (46·3%) with first episode psychosis were using cannabis at first presentation. Cannabis use was most strongly associated with being 16-25 years old, male, and single, and was also associated with an increase in number of hospital admissions (incidence rate ratio 1·50, 95% CI 1·25-1·80), compulsory hospital admission (odds ratio 1·55, 1·16-2·08), and number of days spent in hospital (ß coefficient 35·1 days, 12·1-58·1) over 5 years' follow-up. An increase in number of unique antipsychotic medications mediated an increase in number of hospital admissions (natural indirect effect 1·11, 1·04-1·17; total effect 1·41, 1·22-1·64), compulsory hospital admission (1·27, 1·10-1·45; 1·71, 1·05-2·78), and number of days spent in hospital (16·1, 6·7-25·5; 19·9, 2·5-37·3). INTERPRETATION: We showed that a substantial number of people with first episode psychosis used cannabis and that its use was associated with increased likelihood of hospital admission and number of days spent in hospital. These associations were partly mediated by an increase in number of unique antipsychotic medications prescribed. These findings suggest that cannabis might reduce response to conventional antipsychotic treatment and highlight the importance of strategies to reduce its use. FUNDING: National Institute for Health Research, UK Medical Research Council.

Clinical predictors of antipsychotic use in children and adolescents with autism spectrum disorders: a historical open cohort study using electronic health records.

Children with autism spectrum disorders (ASD) are more likely to receive antipsychotics than any other psychopharmacological medication, yet the psychiatric disorders and symptoms associated with treatment are unclear. We aimed to determine the predictors of antipsychotic use in children with ASD receiving psychiatric care. The sample consisted of 3482 children aged 3-17 with an ICD-10 diagnosis of ASD referred to mental health services between 2008 and 2013. Antipsychotic use outcome, comorbid diagnoses, and other clinical covariates, including challenging behaviours were extracted from anonymised patient records. Of the 3482 children (79 % male) with ASD, 348 (10 %) received antipsychotic medication. The fully adjusted model indicated that comorbid diagnoses including hyperkinetic (OR 1.44, 95 %CI 1.01-2.06), psychotic (5.71, 3.3-10.6), depressive (2.36, 1.37-4.09), obsessive-compulsive (2.31, 1.16-4.61) and tic disorders (2.76, 1.09-6.95) were associated with antipsychotic use. In addition, clinician-rated levels of aggression, self-injurious behaviours, reduced adaptive function, and overall parental concern for their child's presenting symptoms were significant risk factors for later antipsychotic use. In ASD, a number of comorbid psychiatric disorders are independent predictors for antipsychotic treatment, even after adjustment for familial, socio-demographic and individual factors. As current trial evidence excludes children with comorbidity, more pragmatic randomised controlled trials with long-term drug monitoring are needed.

Extracting antipsychotic polypharmacy data from electronic health records: developing and evaluating a novel process.

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

Defining severity of personality disorder using electronic health records: short report.

Severity of personality disorder is an important determinant of future health. However, this key prognostic variable is not captured in routine clinical practice. Using a large clinical data-set, we explored the predictive validity of items from the Health of Nation Outcome Scales (HoNOS) as potential indicators of personality disorder severity. For 6912 patients with a personality disorder diagnosis, we examined associations between HoNOS items relating to core personality disorder symptoms (self-harm, difficulty in interpersonal relationships, performance of occupational and social roles, and agitation and aggression) and future health service use. Compared with those with no self-harm problem, the total healthcare cost was 2.74 times higher (95% CI 1.66-4.52; P < 0.001) for individuals with severe to very severe self-harm problems. Other HoNOS items did not demonstrate clear patterns of association with service costs. Self-harm may be a robust indicator of the severity of personality disorder, but further replication work is required.

Birth without intervention in women with severe mental illness: cohort study.

SUMMARY: The rate of normal birth outcomes (i.e. full-term births without intervention) for women with severe mental illness (SMI - psychotic and bipolar disorders) is not known. We examined rates of birth without intervention (spontaneous labour onset, spontaneous vaginal delivery without instruments, no episiotomy and no indication of pre- or post-delivery anaesthesia) in women with SMI (584 pregnancies) compared with a control population (70 942 pregnancies). Outcome ratios were calculated standardising for age. Women with SMI were less likely to have a birth without intervention (29.5%) relative to the control population (36.8%) (standardised outcome ratio 0.74, 95% CI 0.63-0.87).

Body mass index and mortality in patients with schizophrenia spectrum disorders: a cohort study in a South London catchment area.

Background: People with schizophrenia have a high premature mortality risk. Obesity is a key potential underlying risk factor that is relatively unevaluated to date. Aims: In this study, we investigated the associations of routinely recorded body size with all-cause mortality and deaths from common causes in a large cohort of people with schizophrenia spectrum disorders. Methods: We assembled a retrospective observational cohort using data from a large mental health service in South London. We followed all patients over the age of 18 years with a clinical diagnosis of schizophrenia spectrum disorders from the date of their first recorded body mass index (BMI) between 1 January 2007 and 31 March 2018. Results: Of 11 900 patients with a BMI recording, 1566 died. The Cox proportional hazards regression models, after adjusting for sociodemographic, socioeconomic variables and comorbidities, indicated that all-cause mortality was only associated with underweight status compared with healthy weight status (hazard ratio (HR): 1.33, 95% confidence interval (CI): 1.01 to 1.76). Obesity (HR: 1.24, 95% CI: 1.01 to 1.52) and morbid obesity (HR: 1.54, 95% CI: 1.03 to 2.42) were associated with all-cause mortality in the 18-45 years age range, and obesity was associated with lower risk (HR: 0.66, 95% CI: 0.50 to 0.87) in those aged 65+ years. Cancer mortality was raised in underweight individuals (HR: 1.93, 95% CI: 1.03 to 4.10) and respiratory disease mortality raised in those with morbid obesity (HR: 2.17, 95% CI: 1.02 to 5.22). Conclusions: Overall, being underweight was associated with higher mortality in this disorder group; however, this was potentially accounted for by frailty in older age groups, and obesity was a risk factor for premature mortality in younger ages. The impact of obesity on life expectancy for people with schizophrenia spectrum disorders is clear from our findings. A deeper biological understanding of the relationship between these diseases and schizophrenia will help improve clinical practice.