Maudsley National Health Service Foundation Research Articles

Development of a Corpus Annotated With Mentions of Pain in Mental Health Records: Natural Language Processing Approach.

Pain is a widespread issue, with 20% of adults (1 in 5) experiencing it globally. A strong association has been demonstrated between pain and mental health conditions, and this association is known to exacerbate disability and impairment. Pain is also known to be strongly related to emotions, which can lead to damaging consequences. As pain is a common reason for people to access health care facilities, electronic health records (EHRs) are a potential source of information on this pain. Mental health EHRs could be particularly beneficial since they can show the overlap of pain with mental health. Most mental health EHRs contain the majority of their information within the free-text sections of the records. However, it is challenging to extract information from free text. Natural language processing (NLP) methods are therefore required to extract this information from the text. This research describes the development of a corpus of manually labeled mentions of pain and pain-related entities from the documents of a mental health EHR database, for use in the development and evaluation of future NLP methods. The EHR database used, Clinical Record Interactive Search, consists of anonymized patient records from The South London and Maudsley National Health Service Foundation Trust in the United Kingdom. The corpus was developed through a process of manual annotation where pain mentions were marked as relevant (ie, referring to physical pain afflicting the patient), negated (ie, indicating absence of pain), or not relevant (ie, referring to pain affecting someone other than the patient, or metaphorical and hypothetical mentions). Relevant mentions were also annotated with additional attributes such as anatomical location affected by pain, pain character, and pain management measures, if mentioned. A total of 5644 annotations were collected from 1985 documents (723 patients). Over 70% (n=4028) of the mentions found within the documents were annotated as relevant, and about half of these mentions also included the anatomical location affected by the pain. The most common pain character was chronic pain, and the most commonly mentioned anatomical location was the chest. Most annotations (n=1857, 33%) were from patients who had a primary diagnosis of mood disorders (International Classification of Diseases-10th edition, chapter F30-39). This research has helped better understand how pain is mentioned within the context of mental health EHRs and provided insight into the kind of information that is typically mentioned around pain in such a data source. In future work, the extracted information will be used to develop and evaluate a machine learning-based NLP application to automatically extract relevant pain information from EHR databases.

34.2 IMPROVING THE DETECTION OF INDIVIDUALS AT RISK OF PSYCHOSIS IN SECONDARY MENTAL HEALTH CARE

BackgroundThe overall effect of At Risk Mental State (ARMS) services for the detection of individuals who will develop psychosis in secondary mental health care is undetermined. The objective of the study presented in this lecture is to measure the proportion of individuals with a first episode of psychosis detected by ARMS services in secondary mental health services, and to develop and externally validate a practical web-based individualized risk calculator tool for the transdiagnostic prediction of psychosis in secondary mental health care.MethodsClinical register-based cohort study. Patients were drawn from electronic, real-world, real-time clinical records relating to 2008 to 2015 routine secondary mental health care in the South London and the Maudsley National Health Service Foundation Trust. The study included all patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within the South London and the Maudsley National Health Service Foundation Trust in the period between January 1, 2008, and December 31, 2015. Data analysis began on September 1, 2016.The main outcome is risk of development of nonorganic International Statistical Classification of Diseases and Related Health Problems, Tenth Revision psychotic disorders.ResultsA total of 91 199 patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within South London and the Maudsley National Health Service Foundation Trust were included in the derivation (n=33 820) or external validation (n=54 716) data sets. The mean age was 32.97 years, 50.88% were men, and 61.05% were white race/ethnicity. The mean follow-up was 1588 days. The overall 6-year risk of psychosis in secondary mental health care was 3.02 (95% CI, 2.88–3.15), which is higher than the 6-year risk in the local general population (0.62). Compared with the ARMS designation, all of the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnoses showed a lower risk of psychosis, with the exception of bipolar mood disorders (similar risk) and brief psychotic episodes (higher risk). The ARMS designation accounted only for a small proportion of transitions to psychosis (n=52 of 1001; 5.19% in the derivation data set), indicating the need for transdiagnostic prediction of psychosis in secondary mental health care. A prognostic risk stratification model based on preselected variables, including index diagnosis, age, sex, age by sex, and race/ethnicity, was developed and externally validated, showing good performance and potential clinical usefulness.DiscussionThis lecture will introduce a new online individualized risk calculator which can be of clinical usefulness for the transdiagnostic prediction of psychosis in secondary mental health care. The risk calculator can help to identify those patients at risk of developing psychosis who require an ARMS assessment and specialized care. The use of this calculator may eventually facilitate the implementation of an individualized provision of preventive focused interventions and improve outcomes of first episode psychosis.

What is the impact of research champions on integrating research in mental health clinical practice? A quasiexperimental study in South London, UK

ObjectivesKey challenges for mental health healthcare professionals to implement research alongside clinical activity have been highlighted, such as insufficient time to apply research skills and lack of support and resources....

Effect of implementation of a smoke-free policy on physical violence in a psychiatric inpatient setting: an interrupted time series analysis

Smoke-free policies are important to protect health and reduce health inequalities. A major barrier to policy implementation in psychiatric hospitals is staff concern that physical violence will increase. We aimed to assess the effect of implementing a comprehensive smoke-free policy on rates of physical assaults in a large UK mental health organisation. We did an interrupted time series analysis of incident reports of physical assault 30 months before and 12 months after the implementation of the policy in the inpatient wards of South London and Maudsley National Health Service Foundation Trust, London, UK. We used a quasi-Poisson generalised additive mixed model to model the monthly incidence of physical assaults as a function of several explanatory variables. 4550 physical assaults took place between April 1, 2012, and Sept 30, 2015; 225 (4·9%) of which were smoking-related. After adjustment for temporal and seasonal trends and key confounders (sex, age, schizophrenia or related disorders, or having been sectioned under the Mental Health Act), there was a 39% reduction in the number of physical assaults per month after the policy introduction compared with beforehand (incidence rate ratio 0·61, 95% CI 0·53-0·70; p<0·0001). Introduction of a comprehensive smoke-free policy appeared to reduce the incidence of physical assaults. Adequately resourced smoke-free policies could be part of broader violence reduction strategies in psychiatric settings. National Institute for Health Research Collaboration for Leadership in Applied Health Research and Care South London (King's College Hospital NHS Foundation Trust).

Development and Validation of a Clinically Based Risk Calculator for the Transdiagnostic Prediction of Psychosis

The overall effect of At Risk Mental State (ARMS) services for the detection of individuals who will develop psychosis in secondary mental health care is undetermined. To measure the proportion of individuals with a first episode of psychosis detected by ARMS services in secondary mental health services, and to develop and externally validate a practical web-based individualized risk calculator tool for the transdiagnostic prediction of psychosis in secondary mental health care. Clinical register-based cohort study. Patients were drawn from electronic, real-world, real-time clinical records relating to 2008 to 2015 routine secondary mental health care in the South London and the Maudsley National Health Service Foundation Trust. The study included all patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within the South London and the Maudsley National Health Service Foundation Trust in the period between January 1, 2008, and December 31, 2015. Data analysis began on September 1, 2016. Risk of development of nonorganic International Statistical Classification of Diseases and Related Health Problems, Tenth Revision psychotic disorders. A total of 91 199 patients receiving a first index diagnosis of nonorganic and nonpsychotic mental disorder within South London and the Maudsley National Health Service Foundation Trust were included in the derivation (n = 33 820) or external validation (n = 54 716) data sets. The mean age was 32.97 years, 50.88% were men, and 61.05% were white race/ethnicity. The mean follow-up was 1588 days. The overall 6-year risk of psychosis in secondary mental health care was 3.02 (95% CI, 2.88-3.15), which is higher than the 6-year risk in the local general population (0.62). Compared with the ARMS designation, all of the International Statistical Classification of Diseases and Related Health Problems, Tenth Revision diagnoses showed a lower risk of psychosis, with the exception of bipolar mood disorders (similar risk) and brief psychotic episodes (higher risk). The ARMS designation accounted only for a small proportion of transitions to psychosis (n = 52 of 1001; 5.19% in the derivation data set), indicating the need for transdiagnostic prediction of psychosis in secondary mental health care. A prognostic risk stratification model based on preselected variables, including index diagnosis, age, sex, age by sex, and race/ethnicity, was developed and externally validated, showing good performance and potential clinical usefulness. This online individualized risk calculator can be of clinical usefulness for the transdiagnostic prediction of psychosis in secondary mental health care. The risk calculator can help to identify those patients at risk of developing psychosis who require an ARMS assessment and specialized care. The use of this calculator may eventually facilitate the implementation of an individualized provision of preventive focused interventions and improve outcomes of first episode psychosis.

Predictors of care home and hospital admissions and their costs for older people with Alzheimer's disease: findings from a large London case register

ObjectivesTo examine links between clinical and other characteristics of people with Alzheimer's disease living in the community, likelihood of care home or hospital admission, and associated costs.DesignObservational data extracted from...

Model of understanding fatigue after stroke.

Fatigue is ubiquitous but it is more common and more severe in patients with acute and chronic conditions, including stroke. The reported proportion of people with fatigue after stroke ranges from 23% to 75%.1 The variation in proportion between studies reflects the heterogeneity in the studied populations, time since stroke, and assessment methods for fatigue. Fatigue is common immediately after stroke, and it tends to persist in most but not all patients. It contributes to lower quality of life and a higher risk of death.2,3 How to manage and prevent fatigue is ranked by stroke survivors and health professionals among the top 10 research priorities relating to life after stroke.4 However, there is no effective treatment, which is partly because of our lack of knowledge of its mechanisms. Fatigue after stroke may share some common underlying mechanisms with other conditions. For example, Zedlitz and colleagues found that the psychosocial profiles of stroke patients with fatigue were similar to those reported in patients with cancer, multiple sclerosis, and chronic fatigue syndrome.5 Several fatigue models have been developed for patients with other conditions; a myriad of biological,6,7 psychosocial,8,9 and behavioral factors,9 as well as other symptoms, such as pain and sleep problems,10 are involved. In this review, we explored whether these factors contribute to fatigue after stroke. We systematically reviewed studies of post-stroke fatigue (PSF) and discussed the definition of PSF, its natural history, and its associations. By drawing on literature of fatigue in other conditions alongside evidence from stroke studies, we propose a conceptual model of PSF. This model is potentially useful in understanding the mechanisms of PSF and informing the development of its treatment. In stroke studies, PSF is usually defined by cut-off scores on fatigue …

Social Disadvantage: Cause or Consequence of Impending Psychosis?

Background: An association between social disadvantage and established psychosis is well documented in the literature, but there remains a lack of data on the social circumstances of patients before they became ill. We investigated whether social disadvantage at, and prior to, first contact with psychiatric services, is associated with psychosis. Method: We collected information on social disadvantage in childhood and adulthood from 278 cases presenting with their first episode of psychosis to the South London and Maudsley National Health Service Foundation Trust and from 226 controls recruited from the local population. Three markers of childhood social disadvantage and 3 markers of disadvantage in adulthood were analyzed. Results: Long term separation from, and death of, a parent before the age of 17 years were both strongly associated with a 2- to 3-fold-increased odds of psychosis. Cases were also significantly more likely to report 2 or more markers of adult social disadvantage than healthy controls (OR = 9.03) at the time of the first presentation with psychosis, independent of a number of confounders. When we repeated these analyses for long-standing adult social disadvantage, we found that the strength of the association decreased but still remained significant for 1 year (OR = 5.67) and 5 years (OR = 2.57) prior to the first contact. Conclusions: Social disadvantage indexes exposure to factors operating prior to onset that increase the risk of psychosis, both during childhood and adulthood.

Brain-Cell Discovery Suggests New Antidepressant Target

Back to table of contents Previous article Next article Clinical & Research NewsFull AccessBrain-Cell Discovery Suggests New Antidepressant TargetJoan Arehart-TreichelJoan Arehart-TreichelSearch for more papers by this authorPublished Online:2 Sep 2011https://doi.org/10.1176/pn.46.17.psychnews_46_17_22AbstractDuring the past few years, it has become apparent that antidepressants activate the birth of new neurons in the hippocampus. But how do they do it? Via glucocorticoid receptors present on hippocampal neural progenitor cells, British scientists have found.The findings also have clinical implications, the scientists believe. Glucocorticoid receptors on hippocampal neural progenitor cells might offer a novel target for the development of new, more effective antidepressants. Scientists cultured hippocampal neural progenitor cells, then exposed them to the antidepressant sertraline. The treatment stimulated the cells to differentiate into neurons (pictured here).Credit: Carmine Pariante, MD, PhD, et al., Molecular Psychiatry, July 2011The lead investigator was Christoph Anacker, a doctoral student at the Institute of Psychiatry, King's College, London. The senior investigator was Carmine Pariante, M.D., Ph.D., a reader in biological psychiatry at the Institute. The results appeared in the July Molecular Psychiatry.Glucocorticoids are a class of steroid hormones, such as cortisol, that regulate the metabolism of glucose. They exert their effects through the glucocorticoid receptors. Anacker and his group had previously found that antidepressants influence the function of glucocorticoid receptors. So this time they looked to see whether glucocorticoid receptors might be involved in antidepressants' ability to stimulate nerve generation in the hippocampus. They cultured hippocampal neural progenitor cells, then exposed them to the SSRI sertraline. They found that the treatment not only stimulated the cells to differentiate into nerve cells, but that it evoked certain changes in glucocorticoid receptors present on the cells, for example, in the receptors' phosphorylation by cyclic AMP-protein kinase activities. They also found that when they added a glucocorticoid receptor antagonist to their culture, the SSRI-prompted nerve differentiation effect was abolished. These findings, they concluded, suggest that glucocorticoid receptors are pivotal to antidepressant-induced hippocampal formation of new neurons. Yet if glucocorticoid receptors are crucial for antidepressant-induced hippocampal nerve differentiation, then why is this the case? "Glucocorticoid receptors, it is true, are receptors for glucocorticoid hormones, yet while these hormones are involved in glucose metabolism, the receptor is not itself affected by glucose," Pariante told Psychiatric News. "So glucose is unlikely to be the mechanism. On the other hand, the glucocorticoid receptors are also transcription factors—that is, they regulate the synthesis of other genes. What likely happens is that antidepressants activate the glucocorticoid receptors, and the receptors in turn increase the synthesis of genes that increase neurogenesis." In an interview, still another possible scenario was suggested by Maura Boldrini, M.D., Ph.D., an assistant professor of psychiatry at Columbia University and an expert on the subject. "Stress is known to reduce hippocampal neurogenesis throughout species.... Antidepressants have shown a significant role in reversing the negative effect of stress on neurogenesis.... Therefore the study by Anacker et al. confirms in human progenitor cells that one of the mechanisms of action of antidepressants on neurogenesis might be via the reversal of the glucocorticoid receptor changes induced by stress. Such a finding should be confirmed in postmortem human brains comparing subjects with mood disorders treated with antidepressants and untreated cases." Whether either of these explanations is correct, the findings definitely have clinical implications, Pariante said. The glucocorticoid receptors on the hippocampal progenitor cells offer "a novel potential target for the development of new and more effective antidepressants." The study was funded by the Institute of Psychiatry, the South London and Maudsley National Health Service Foundation Trust, the United Kingdom Medical Research Council, and the Commission of European Communities. "Antidepressants Increase Human Hippocampal Neurogenesis by Activating the Glucocorticoid Receptor" is posted at <www.nature.com/mp/journal/v16/n7/pdf/mp201126a.pdf>. ISSUES NewArchived

Stress and Inflammation Reduce Brain-Derived Neurotrophic Factor Expression in First-Episode Psychosis

Reduced brain-derived neurotrophic factor (BDNF) levels have been reported in the serum and plasma of patients with psychosis. The aim of this cross-sectional case-control study was to investigate potential causes and consequences of reduced BDNF expression in these patients by examining the association between BDNF levels and measures of stress, inflammation, and hippocampal volume in first-episode psychosis. Brain-derived neurotrophic factor, interleukin (IL)-6, and tumor necrosis factor (TNF)-α messenger RNA levels were measured in the leukocytes of 49 first-episode psychosis patients (DSM-IV criteria) and 30 healthy controls, all aged 18 to 65 years, recruited between January 2006 and December 2008. Patients were recruited from inpatient and outpatient units of the South London and Maudsley National Health Service Foundation Trust in London, United Kingdom, and the healthy controls were recruited from the same catchment area via advertisement and volunteer databases. In these same subjects, we measured salivary cortisol levels and collected information about psychosocial stressors (number of childhood traumas, number of recent stressors, and perceived stress). Finally, hippocampal volume was measured using brain magnetic resonance imaging in a subsample of 19 patients. Patients had reduced BDNF (effect size, d = 1.3; P < .001) and increased IL-6 (effect size, d = 1.1; P < .001) and TNF-α (effect size, d = 1.7; P < .001) gene expression levels when compared with controls, as well as higher levels of psychosocial stressors. A linear regression analysis in patients showed that a history of childhood trauma and high levels of recent stressors predicted lower BDNF expression through an inflammation-mediated pathway (adjusted R(2) = 0.23, P = .009). In turn, lower BDNF expression, increased IL-6 expression, and increased cortisol levels all significantly and independently predicted a smaller left hippocampal volume (adjusted R(2) = 0.71, P < .001). Biological changes activated by stress represent a significant factor influencing brain structure and function in first-episode psychosis through an effect on BDNF.

Psychiatrists and electronic patient records: the South London and Maudsley experience

Aims and MethodTo explore the experiences and attitudes of psychiatrists to a new electronic patient records system. A questionnaire was emailed to 115 psychiatrists across the South London &amp; Maudsley National Health Service Foundation Trust.ResultsThe total response rate was 66% (senior house officers 75%, specialist registrars 57%, consultants 56%). Technical problems, difficulty with patient confidentiality, administrative burden and impact on clinical work were identified as concerns. However, psychiatrists recognised the potential benefits and the majority did not wish to return to using paper records.Clinical ImplicationsElectronic patient records are rapidly being integrated into the daily practice of psychiatrists. More administrative assistance and specific training should be provided to support clinicians who use this system.