Natural language processing to extract symptoms of severe mental illness from clinical text: the Clinical Record Interactive Search Comprehensive Data Extraction (CRIS-CODE) project.

OBJECTIVES: We sought to use natural language processing to develop a suite of language models to capture key symptoms of severe mental illness (SMI) from clinical text, to facilitate the secondary use of mental healthcare data in research. DESIGN: Development and validation of information extraction applications for ascertaining symptoms of SMI in routine mental health records using the Clinical Record Interactive Search (CRIS) data resource; description of their distribution in a corpus of discharge summaries. SETTING: Electronic records from a large mental healthcare provider serving a geographic catchment of 1.2 million residents in four boroughs of south London, UK. PARTICIPANTS: The distribution of derived symptoms was described in 23 128 discharge summaries from 7962 patients who had received an SMI diagnosis, and 13 496 discharge summaries from 7575 patients who had received a non-SMI diagnosis. OUTCOME MEASURES: Fifty SMI symptoms were identified by a team of psychiatrists for extraction based on salience and linguistic consistency in records, broadly categorised under positive, negative, disorganisation, manic and catatonic subgroups. Text models for each symptom were generated using the TextHunter tool and the CRIS database. RESULTS: We extracted data for 46 symptoms with a median F1 score of 0.88. Four symptom models performed poorly and were excluded. From the corpus of discharge summaries, it was possible to extract symptomatology in 87% of patients with SMI and 60% of patients with non-SMI diagnosis. CONCLUSIONS: This work demonstrates the possibility of automatically extracting a broad range of SMI symptoms from English text discharge summaries for patients with an SMI diagnosis. Descriptive data also indicated that most symptoms cut across diagnoses, rather than being restricted to particular groups

Novel psychoactive substances: An investigation of temporal trends in social media and electronic health records

Background: Public health monitoring is commonly undertaken in social media but has never been combined with data analysis from electronic health records. This study aimed to investigate the relationship between the emergence of novel psychoactive substances (NPS) in social media and their appearance in a large mental health database. Methods: Insufficient numbers of mentions of other NPS in case records meant that the study focused on mephedrone. Data were extracted on the number of mephedrone (i) references in the clinical record at the South London and Maudsley NHS Trust, London, UK, (ii) mentions in Twitter, (iii) related searches in Google and (iv) visits in Wikipedia. The characteristics of current mephedrone users in the clinical record were also established. Results: Increased activity related to mephedrone searches in Google and visits in Wikipedia preceded a peak in mephedrone-related references in the clinical record followed by a spike in the other 3 data sources in early 2010, when mephedrone was assigned a ‘class B’ status. Features of current mephedrone users widely matched those from community studies. Conclusions: Combined analysis of information from social media and data from mental health records may assist public health and clinical surveillance for certain substance-related events of interest. There exists potential for early warning systems for health-care practitioners

Predictors of dentists' behaviours in delivering prevention in primary dental care in England: using the theory of planned behaviour.

This article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were madeBACKGROUND: To explore the factors predicting preventive behaviours among NHS dentists in Camden, Islington and Haringey in London, using constructs from the Theory of Planned Behaviour. METHODS: A cross-sectional survey of NHS dentists working in North Central London was conducted. A self-completed questionnaire based on the theoretical framework of the Theory of Planned Behaviour was developed. It assessed dentists' attitudes, current preventive activities, subjective norms and perceived behavioural control in delivering preventive care. In model 1, logistic regression was conducted to assess the relationship between a range of preventive behaviours (diet, smoking and alcohol) and the three TPB constructs attitude, subjective norms and perceived behavioural control. Model 2 was adjusted for intention. RESULTS: Overall, 164 questionnaires were returned (response rate: 55.0%). Dentists' attitudes were important predictors of preventive behaviours among a sample of dentists in relation to asking and providing diet, alcohol and tobacco advice. A dentist was 3.73 times (95 % CI: 1.70, 8.18) more likely ask about a patient's diet, if they had a positive attitude towards prevention, when adjusted for age, sex and intention. A similar pattern emerged for alcohol advice (OR 2.35, 95 % CI 1.12, 4.96). Dentists who had a positive attitude were also 2.59 times more likely to provide smoking cessation advice. CONCLUSIONS: The findings of this study have demonstrated that dentists' attitudes are important predictors of preventive behaviours in relation to delivery of diet, smoking and alcohol advice.This paper presents independent research funded by the National Institute for Health Research (NIHR) under its Research for Patient Benefit (RfPB) Programme (Grant Reference Number- PB PG 1207 14085)

Catatonia: demographic, clinical and laboratory associations

Background: Catatonia, a severe neuropsychiatric syndrome, has few studies of sufficient scale to clarify its epidemiology or pathophysiology. We aimed to characterise demographic associations, peripheral inflammatory markers and outcome of catatonia. / Methods: Electronic healthcare records were searched for validated clinical diagnoses of catatonia. In a case–control study, demographics and inflammatory markers were compared in psychiatric inpatients with and without catatonia. In a cohort study, the two groups were compared in terms of their duration of admission and mortality. / Results: We identified 1456 patients with catatonia (of whom 25.1% had two or more episodes) and 24 956 psychiatric inpatients without catatonia. Incidence was 10.6 episodes of catatonia per 100 000 person-years. Patients with and without catatonia were similar in sex, younger and more likely to be of Black ethnicity. Serum iron was reduced in patients with catatonia [11.6 v. 14.2 μmol/L, odds ratio (OR) 0.65 (95% confidence interval (CI) 0.45–0.95), p = 0.03] and creatine kinase was raised [2545 v. 459 IU/L, OR 1.53 (95% CI 1.29–1.81), p < 0.001], but there was no difference in C-reactive protein or white cell count. N-Methyl-D-aspartate receptor antibodies were significantly associated with catatonia, but there were small numbers of positive results. Duration of hospitalisation was greater in the catatonia group (median: 43 v. 25 days), but there was no difference in mortality after adjustment. / Conclusions: In the largest clinical study of catatonia, we found catatonia occurred in approximately 1 per 10 000 person-years. Evidence for a proinflammatory state was mixed. Catatonia was associated with prolonged inpatient admission but not with increased mortality

Clinical Neuroimaging Findings in Catatonia: Neuroradiological Reports of MRI Scans of Psychiatric Inpatients With and Without Catatonia

OBJECTIVE: Catatonia is a debilitating psychomotor disorder. Previous neuroimaging studies have used small samples with inconsistent results. The authors aimed to describe the structural neuroradiological abnormalities in clinical magnetic resonance imaging (MRI) brain scans of patients with catatonia, comparing them with scans of psychiatric inpatients without catatonia. They report the largest study of catatonia neuroimaging to date. METHODS: In this retrospective case-control study, neuroradiological reports of psychiatric inpatients who had undergone MRI brain scans for clinical reasons were examined. Abnormalities were classified by lateralization, localization, and pathology. The primary analysis was prediction of catatonia by presence of an abnormal MRI scan, adjusted for age, sex, Black race-ethnicity, and psychiatric diagnosis. RESULTS: Scan reports from 79 patients with catatonia and 711 other psychiatric inpatients were obtained. Mean age was 36.4 (SD=17.3) for the cases and 44.5 (SD=19.9) for the comparison group. Radiological abnormalities were reported in 27 of 79 cases (34.2%) and in 338 of 711 in the comparison group (47.5%) (odds ratio [OR]=0.57, 95% confidence interval [CI]=0.35, 0.93; adjusted OR=1.11, 95% CI=0.58, 2.14). Among the cases, most abnormal scans had bilateral abnormalities (N=23, 29.1%) and involved the forebrain (N=25, 31.6%) and atrophy (N=17, 21.5%). CONCLUSIONS: Patients with catatonia were commonly reported to have brain MRI abnormalities, which largely consisted of diffuse cerebral atrophy rather than focal lesions. No evidence was found that these abnormalities were more common than in other psychiatric inpatients undergoing neuroimaging, after adjustment for demographic variables. Study limitations included a heterogeneous control group and selection bias in requesting scans

Utilising symptom dimensions with diagnostic categories improves prediction of time to first remission in first-episode psychosis

There has been much recent debate concerning the relative clinical utility of symptom dimensions versus conventional diagnostic categories in patients with psychosis. We investigated whether symptom dimensions rated at presentation for first-episode psychosis (FEP) better predicted time to first remission than categorical diagnosis over a four-year follow-up. The sample comprised 193 FEP patients aged 18–65 years who presented to psychiatric services in South London, UK, between 2006 and 2010. Psychopathology was assessed at baseline with the Positive and Negative Syndrome Scale and five symptom dimensions were derived using Wallwork/Fortgang's model; baseline diagnoses were grouped using DSM-IV codes. Time to start of first remission was ascertained from clinical records. The Bayesian Information Criterion (BIC) was used to find the best fitting accelerated failure time model of dimensions, diagnoses and time to first remission. Sixty percent of patients remitted over the four years following first presentation to psychiatric services, and the average time to start of first remission was 18.3 weeks (SD = 26.0, median = 8). The positive (BIC = 166.26), excited (BIC = 167.30) and disorganised/concrete (BIC = 168.77) symptom dimensions, and a diagnosis of schizophrenia (BIC = 166.91) predicted time to first remission. However, a combination of the DSM-IV diagnosis of schizophrenia with all five symptom dimensions led to the best fitting model (BIC = 164.35). Combining categorical diagnosis with symptom dimension scores in FEP patients improved the accuracy of predicting time to first remission. Thus our data suggest that the decision to consign symptom dimensions to an annexe in DSM-5 should be reconsidered at the earliest opportunity

Differences in cannabis-related experiences between patients with a first episode of psychosis and controls

Background Many studies have reported that cannabis use increases the risk of a first episode of psychosis (FEP). However, only a few studies have investigated the nature of cannabis-related experiences in FEP patients, and none has examined whether these experiences are similar in FEP and general populations. The aim of this study was to explore differences in self-reported cannabis experiences between FEP and non-psychotic populations. Method A total of 252 subjects, who met International Classification of Diseases (ICD)-10 criteria for FEP, and 217 controls who reported cannabis use were selected from the Genetics and Psychosis (GAP) study. The Medical Research Council Social Schedule and the Cannabis Experience Questionnaire were used to collect sociodemographic data and cannabis use information, respectively. Results Both 'bad' and 'enjoyable' experiences were more commonly reported by FEP subjects than controls. Principal components factor analysis identified four components which explained 62.3% of the variance. Linear regression analysis on the whole sample showed that the type of cannabis used and beliefs about the effect of cannabis on health all contributed to determining the intensity and frequency of experiences. Linear regression analysis on FEP subjects showed that the duration of cannabis use and amount of money spent on cannabis were strongly related to the intensity and frequency of enjoyable experiences in this population. Conclusions These results suggest a higher sensitivity to cannabis effects among people who have suffered their first psychotic episode; this hypersensitivity results in them reporting both more 'bad' and 'enjoyable' experiences. The greater enjoyment experienced may provide an explanation of why FEP patients are more likely to use cannabis and to continue to use it despite experiencing an exacerbation of their psychotic symptoms

Different types of childhood adversity and 5-year outcomes in a longitudinal cohort of first-episode psychosis patients

Little is known about the impact of different forms of childhood adversity on outcomes in first-episode psychosis (FEP) patients beyond the first year of treatment. We investigated associations between different types of childhood adversity and outcomes of FEP patients over the 5 years following their first contact with mental health services for psychosis. 237 FEP cases aged 18–65 years were followed on average for 5 years after first presentation to psychiatric services in South London, UK. Childhood adversity prior to 17 years of age was assessed at baseline using the Childhood Experience of Care and Abuse Questionnaire (CECA.Q). The results showed that exposure to at least one type of childhood adversity was significantly associated with a lower likelihood of achieving symptomatic remission, longer inpatient stays, and compulsory admission over the 5-year follow-up. There was no evidence though of a dose-response effect. Some specificity was evident. Childhood parental separation was associated with significantly greater likelihood of non-compliance with antipsychotic medications, compulsory admission, and substance dependence. Institutional care was significantly associated with longer total length of inpatient stays; and parental death was significantly associated with compulsory admissions. Clinicians should screen FEP patients for childhood adversity and tailor interventions accordingly to improve outcomes