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Current criteria for depression are imprecise and do not accurately characterize its distinct clinical presentations. As a result, its diagnosis lacks clinical utility in both treatment and research settings. Data-driven efforts to refine criteria have typically focused on a limited set of symptoms that do not reflect the disorder’s heterogeneity. By contrast, clinicians often write about patients in depth, creating descriptions that may better characterize depression. However, clinical text is not commonly used to this end. Here we show that clinically relevant depressive subtypes can be derived from unstructured electronic health records. Five subtypes were identified amongst 18,314 patients with depression treated at a large mental healthcare provider by using unsupervised machine learning: severe-typical, psychotic, mild-typical, agitated, and anergic-apathetic. Subtypes were used to place patients in groups for validation; groups were found to be associated with future outcomes and characteristics that were consistent with the subtypes. These associations suggest that these categorizations are actionable due to their validity with respect to disease prognosis. Moreover, they were derived with automated techniques that might theoretically be widely implemented, allowing for future analyses in more varied populations and settings. Additional research, especially with respect to treatment response, may prove useful in further evaluation.

Antipsychotic treatments are associated with safety concerns in people with dementia. The authors aimed to investigate whether risk of adverse outcomes related to antipsychotic prescribing differed according to major neuropsychiatric syndromes—specifically psychosis, agitation, or a combination. A cohort of 10,106 patients with a diagnosis of dementia was assembled from a large dementia care database in South East London. Neuropsychiatric symptoms closest to first dementia diagnosis were determined according to the Health of the Nation Outcome Scales’ mental and behavioural problem scores and the sample was divided into four groups: ‘agitation and psychosis’, ‘agitation, but no psychosis’, ‘psychosis, but no agitation’, and ‘neither psychosis nor agitation’. Antipsychotic prescription in a one-year window around first dementia diagnosis was ascertained as exposure variable through natural language processing from free text. Cox regression models were used to analyse associations of antipsychotic prescription with all-cause and stroke-specific mortality, emergency hospitalisation and hospitalised stroke adjusting for sixteen potential confounders including demographics, cognition, functioning, as well as physical and mental health. Only in the group ‘psychosis, but no agitation’ (n = 579), 30% of whom were prescribed an antipsychotic, a significant antipsychotic-associated increased risk of hospitalised stroke was present after adjustment (adjusted hazard ratio (HR) 2.16; 95% confidence interval (CI) 1.09–4.25). An increased antipsychotic-related all-cause (adjusted HR 1.14; 95% CI 1.04–1.24) and stroke-specific mortality risk (adjusted HR 1.28; 95% CI 1.01–1.63) was detected in the whole sample, but no interaction between the strata and antipsychotic-related mortality. In conclusion, the adverse effects of antipsychotics in dementia are complex. Stroke risk may be highest when used in patients presenting with psychosis without agitation, indicating the need for novel interventions for this group.

ObjectivesTo describe the distribution of contacts with mental health service-employed social workers over time and by patient characteristics using routine mental health service data resources.DesignA descriptive study.Setting and participantsIn a large secondary mental healthcare provider in London serving a geographic catchment of around 1.3 million residents, mental health social worker contacts were ascertained from the case note entries for all patients aged 16 years or above at the time of contact who received treatment in any services from 2008 to 2023.Main outcome measuresPatient demographic and clinical characteristics at or closest to the social worker contact event.ResultsA total 1 541 078 social worker contacts were extracted. Contacts were most likely in the 20–39 years age group (38.1%), in men (51.9%), in patients from white (45.3%) and black (38.8%) ethnic groups, in those who were non-cohabiting (89.9%) and in those living in more deprived neighbourhoods. The most likely diagnosis in those receiving social work contacts was schizophrenia (39.2%). Males had the highest number of face-to-face social worker contacts, and females were more represented in phone and video contacts. Over the past 16 years, social worker contacts were highest between 2014 and 2015.ConclusionsTo the best of our knowledge, this study is the first quantification of social work deployment within mental healthcare. Research into the role of social workers within mental health services has been of small scale and predominantly qualitative to date. However, growing data resources, building on distributions of service provision, present important opportunities for wider evaluation of the role of this professional group and the interventions they support within multidisciplinary teams.

Acetylcholinesterase inhibitors (AChEIs) are widely used to delay cognitive decline in Alzheimer's disease. Observational studies in routine clinical practice have shown cognitive improvement in some groups of patients receiving these agents but longitudinal trajectories before and after AChEI initiation have not previously been considered. To compare trajectories of cognitive function before and after AChEI initiation and investigate predictors of these differences. A retrospective longitudinal study was constructed using data from 2460 patients who received AChEIs and who had routine data on cognitive function (Mini-Mental State Examination; MMSE) before and after AChEI initiation. Longitudinal MMSE change was modelled using three-piece linear mixed models with the following segments: 0-12 months prior to AChEI initiation, 0-6 months and 6-36 months after initiation. MMSE decline was reversed (in that the slope was improved by an average 4.2 units per year, 95% CI 3.5-4.8) during the 6-month period following AChEI initiation compared with the slope in the one year period before AChEI initiation. The slope in the period from 6-36 months following AChEI initiation returned to the pre-initiation downward trajectory. The differences in slopes in the 1 year period prior to AChEI initiation and in the 6 months after initiation were smaller among those with higher MMSE scores at the time of AChEI initiation, among those who received a vascular dementia diagnosis at any point, and among those receiving antipsychotic agents. In this naturalistic observational study, changes in cognitive trajectories around AChEI initiation were similar to those reported in randomised controlled trials. The magnitude of the difference in slopes between the 1 year period prior to AChEI initiation and the 6 month period after AChEI initiation was related to level of cognitive function at treatment initiation, vascular comorbidity and antipsychotic use.

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.

PurposeIt is well known that loneliness can worsen physical and mental health outcomes, but there is a dearth of research on the impact of loneliness in populations receiving mental healthcare. This study aimed to investigate cross-sectional correlates of loneliness among such patients and longitudinal risk for acute general hospitalisations.MethodA retrospective observational study was conducted on the data from patients aged 18 + receiving assessment/care at a large mental healthcare provider in South London. Recorded loneliness status was ascertained among active patients on the index date, 30th Jun 2012. Acute general hospitalisation (emergency/elective) outcomes were obtained until 31st Mar 2018. Length of stay was modelled using Poisson regression models and time-to hospitalisation and time-to mortality were modelled using Cox proportional hazards regression models.ResultsThe data from 26,745 patients were analysed. The prevalence of patients with recorded loneliness was 16.4% at the index date. In the fully adjusted model, patients with recorded loneliness had higher hazards of emergency (HR 1.15, 95% CI 1.09–1.22) and elective (1.05, 1.01–1.12) hospitalisation than patients who were not recorded as lonely, and a longer duration of both emergency (IRR 1.06, 95% CI 1.05–1.07) and elective (1.02, 1.01–1.03) general hospitalisations. There was no association between loneliness and mortality. Correlates of loneliness included having an eating disorder (OR 1.67, 95% CI 1.29–2.25) and serious mental illnesses (OR 1.44, 1.29–1.62).ConclusionLoneliness in patients receiving mental healthcare is associated with higher use of general hospital services. Increased attention to the physical healthcare of this patient group is therefore warranted.

Patients diagnosed with mental health problems are more predisposed to cardiovascular disease, including cardiac surgery. Nevertheless, health outcomes after cardiac surgery for patients with mental health problems as a discrete group are unknown. This study examined the association between secondary care mental health service use and postoperative health outcomes following cardiac surgery. We conducted a retrospective observational research, utilizing data from a large South London mental healthcare supplier linked to national hospitalization data. OPCS-4 codes were applied to classify cardiac surgery. Health results were compared between those individuals with a mental health disorder diagnosis from secondary care and other local residents, including the length of hospital stay (LOS), inpatient mortality, and 30-day emergency hospital readmission. Twelve thousand three hundred and eighty-four patients received cardiac surgery, including 1,481 with a mental disorder diagnosis. Patients with mental health diagnosis were at greater risk of emergency admissions for cardiac surgery (odds ratio [OR] 1.60; 1.43, 1.79), longer index LOS (incidence rate ratio 1.28; 1.26, 1.30), and at higher risk of 30-day emergency readmission (OR 1.53; 1.31, 1.78). Those who underwent pacemaker insertion and major open surgery had worse postoperative outcomes during index surgery hospital admission while those who had major endovascular surgery had worse health outcomes subsequent 30-day emergency hospital readmission. People with a mental health disorder diagnosis undertaking cardiac surgery have significantly worse health outcomes. Personalized guidelines and policies to manage preoperative risk factors require consideration and evaluation.

Background Case registers have been used extensively in mental health research. Recent developments in electronic medical records, and in computer software to search and analyse these in anonymised format, have the potential to revolutionise this research tool. Methods We describe the development of the South London and Maudsley NHS Foundation Trust (SLAM) Biomedical Research Centre (BRC) Case Register Interactive Search tool (CRIS) which allows research-accessible datasets to be derived from SLAM, the largest provider of secondary mental healthcare in Europe. All clinical data, including free text, are available for analysis in the form of anonymised datasets. Development involved both the building of the system and setting in place the necessary security (with both functional and procedural elements). Results Descriptive data are presented for the Register database as of October 2008. The database at that point included 122,440 cases, 35,396 of whom were receiving active case management under the Care Programme Approach. In terms of gender and ethnicity, the database was reasonably representative of the source population. The most common assigned primary diagnoses were within the ICD mood disorders (n = 12,756) category followed by schizophrenia and related disorders (8158), substance misuse (7749), neuroses (7105) and organic disorders (6414). Conclusion The SLAM BRC Case Register represents a 'new generation' of this research design, built on a long-running system of fully electronic clinical records and allowing in-depth secondary analysis of both numerical, string and free text data, whilst preserving anonymity through technical and procedural safeguards.

Background Currently, the main pharmaceutical intervention for COVID-19 is vaccination. While antidepressant (AD) drugs have shown some efficacy in treatment of symptomatic COVID-19, their preventative potential remains largely unexplored. Analysis of association between prescription of ADs and COVID-19 incidence in the population would be beneficial for assessing the utility of ADs in COVID-19 prevention. Methods Retrospective study of association between AD prescription and COVID-19 diagnosis was performed in a cohort of community-dwelling adult mental health outpatients during the 1st wave of COVID-19 pandemic in the UK. Clinical record interactive search (CRIS) was performed for mentions of ADs within 3 months preceding admission to inpatient care of the South London and Maudsley (SLaM) NHS Foundation Trust. Incidence of positive COVID-19 tests upon admission and during inpatient treatment was the primary outcome measure. Results AD mention was associated with approximately 40% lower incidence of positive COVID-19 test results when adjusted for socioeconomic parameters and physical health. This association was also observed for prescription of ADs of the selective serotonin reuptake inhibitor (SSRI) class. Conclusions This preliminary study suggests that ADs, and SSRIs in particular, may be of benefit for preventing COVID-19 infection spread in the community. The key limitations of the study are its retrospective nature and the focus on a mental health patient cohort. A more definitive assessment of AD and SSRI preventative potential warrants prospective studies in the wider demographic.

Patients with depression are more susceptible to cardiovascular illness including vascular surgeries. However, health outcomes after vascular surgery among patients with depression is unknown. This study aimed to investigate associations of depression with post-operative health outcomes for vascular surgical patients. A retrospective observational study was conducted using data from a large mental healthcare provider and linked national hospitalization data for the same south London geographic catchment. OPCS-4 codes were used to identify vascular procedures. Health outcomes were compared between those with/without depression including length of hospital stay (LOS), inpatient mortality, and 30 day emergency hospital readmissions. Predictors of these health outcomes were also assessed. Vascular surgery was received by 9,267 patients, including 446 diagnosed with depression. Patients with depression had a higher risk of emergency admission for vascular surgery (odds ratio [OR] 1.28; 1.03, 1.59), longer index LOS (IRR 1.38; 1.33-1.42), and a higher risk of 30-day emergency readmission (OR 1.82; 1.35-2.47). Patients with depression had higher inpatient mortality after adjustment for sociodemographic status (1.51; 1.03, 2.23) but not on full adjustment, and had longer emergency readmission LOS (1.13; 1.04, 1.22) after adjustment for sociodemographic factors and cardiovascular disease. Correlates of vascular surgery hospitalization among patients with depression included admission through emergency route for longer LOS, inpatient mortality, and 30-day hospital readmission. Patients with depression undergoing vascular surgery have substantially poorer health outcomes. Screening for depression prior to surgery might be indicated to target preventative measures.