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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.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.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%).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.

Aims and methodTo support safe prescribing of antipsychotics in dementia, antipsychotic monitoring forms were embedded into our electronic health records. We present a review of the data collected on these forms to assess prescribing and identify areas for improvement in our practice and processes. Data were extracted from the structured fields of antipsychotic initiation and review forms completed between 1 January 2018 and 31 January 2020.ResultsWe identified gaps in practice where improvements could be made, mainly with regard to physical health monitoring (and particularly electrocardiograms, performed in only 50% of patients) and the low (less than 50%) recorded use of non-pharmacological interventions for behavioural and psychological symptoms of dementia. In addition, antipsychotic treatment was continued despite lack of benefit in almost 10% of reviews.Clinical implicationsWe advocate for recommendations on physical health monitoring of people with dementia taking antipsychotics to be added to the National Institute for Health and Care Excellence guidance on dementia and the Prescribing Observatory for Mental Health (POMH-UK) national audit.

BackgroundCatatonia, 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.MethodsElectronic 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.ResultsWe 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.ConclusionsIn 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.

BACKGROUND: Metabolic abnormalities and peripheral inflammation have been increasingly reported in patients at the onset of psychosis and associated with important physical health disorders and increased mortality. However, the impact of an abnormal metabolic-inflammatory status on the psychiatric outcome of these patients has not yet been investigated.OBJECTIVES: The aims of this study were 1) to explore whether, in a sample of patients at their first episode of psychosis (FEP), an overall metabolic-inflammatory status may be measured, by combining metabolic and inflammatory variables in metabolic-inflammatory factors; 2) to explore the association between these factors and clinical outcome at 1-year follow-up (FU), in terms of symptoms severity and treatment response.METHODS: In this longitudinal study we recruited 42 FEP patients and 46 healthy controls (HC) matched with patients for age, gender and ethnicity. At baseline (T1) we measured high sensitivity C-reactive protein (hsCRP) as biomarker of inflammation, and body mass index (BMI), lipid profile and gluco-metabolic parameters (glycated hemoglobin (HbA1c) and fasting glucose) as metabolic variables. A principal component analysis (PCA) was then used to reduce the dimensionality of the dataset accounting for both inflammation and metabolic status. In FEP patients, we assessed symptoms severity at T1 and at 1-year FU (T2) as well as treatment response to antipsychotics at T2.RESULTS: at T1, FEP showed higher HbA1c (p = 0.034), triglycerides (TG) (p = 0.045) and BMI (p = 0.026) than HC. PCA identified 3 factors: factor 1 accounting for hsCRP, TG and BMI, factor 2 accounting for LDL and cholesterol, and factor 3 accounting for fasting glucose and HbA1c. Factor 1 was associated with T1 negative symptoms severity (p = 0.021) and predicted T2 positive (p = 0.004) and overall symptoms severity (0.001), as well as general psychopathology (p CONCLUSION: In this sample of FEP patients, inflammation and metabolism, closely correlated at the onset of psychosis, proved to play a key role as predictors of the clinical course of psychosis when combined in a single factor. These findings offer an important potential target for early screening and interventions.

ObjectivesWe aimed to apply natural language processing algorithms in routine healthcare records to identify reported somatic passivity (external control of sensations, actions and impulses) and thought interference symptoms (thought broadcasting, insertion, withdrawal), first-rank symptoms traditionally central to diagnosing schizophrenia, and determine associations with prognosis by analysing routine outcomes.DesignFour algorithms were developed on deidentified mental healthcare data and applied to ascertain recorded symptoms over the 3 months following first presentation to a mental healthcare provider in a cohort of patients with a primary schizophreniform disorder (ICD-10 F20-F29) diagnosis.Setting and participantsFrom the electronic health records of a large secondary mental healthcare provider in south London, 9323 patients were ascertained from 2007 to the data extraction date (25 February 2020).OutcomesThe primary binary dependent variable for logistic regression analyses was any negative outcome (Mental Health Act section, >2 antipsychotics prescribed, >22 days spent in crisis care) over the subsequent 2 years.ResultsFinal adjusted models indicated significant associations of this composite outcome with baseline somatic passivity (prevalence 4.9%; adjusted OR 1.61, 95% CI 1.37 to 1.88), thought insertion (10.7%; 1.24, 95% CI 1.15 to 1.55) and thought withdrawal (4.9%; 1.36, 95% CI 1.10 to 1.69), but not independently with thought broadcast (10.3%; 1.05, 95% CI 0.91 to 1.22).ConclusionsSymptoms traditionally central to the diagnosis of schizophrenia, but under-represented in current diagnostic frameworks, were thus identified as important predictors of short-term to medium-term prognosis in schizophreniform disorders.

ObjectivesWe set out to develop, evaluate and implement a novel application using natural language processing to text mine occupations from the free-text of psychiatric clinical notes.DesignDevelopment and validation of a natural language processing application using General Architecture for Text Engineering software to extract occupations from de-identified clinical records.Setting and participantsElectronic health records from a large secondary mental healthcare provider in south London, accessed through the Clinical Record Interactive Search platform. The text mining application was run over the free-text fields in the electronic health records of 341 720 patients (all aged ≥16 years).OutcomesPrecision and recall estimates of the application performance; occupation retrieval using the application compared with structured fields; most common patient occupations; and analysis of key sociodemographic and clinical indicators for occupation recording.ResultsUsing the structured fields alone, only 14% of patients had occupation recorded. By implementing the text mining application in addition to the structured fields, occupations were identified in 57% of patients. The application performed on gold-standard human-annotated clinical text at a precision level of 0.79 and recall level of 0.77. The most common patient occupations recorded were ‘student’ and ‘unemployed’. Patients with more service contact were more likely to have an occupation recorded, as were patients of a male gender, older age and those living in areas of lower deprivation.ConclusionThis is the first time a natural language processing application has been used to successfully derive patient-level occupations from the free-text of electronic mental health records, performing with good levels of precision and recall, and applied at scale. This may be used to inform clinical studies relating to the broader social determinants of health using electronic health records.

We aimed to investigate whether daily fluctuations in mental health-relevant Twitter posts are associated with daily fluctuations in mental health crisis episodes. We conducted a primary and replicated time-series analysis of retrospectively collected data from Twitter and two London mental healthcare providers. Daily numbers of ‘crisis episodes’ were defined as incident inpatient, home treatment team and crisis house referrals between 2010 and 2014. Higher volumes of depression and schizophrenia tweets were associated with higher numbers of same-day crisis episodes for both sites. After adjusting for temporal trends, seven-day lagged analyses showed significant positive associations on day 1, changing to negative associations by day 4 and reverting to positive associations by day 7. There was a 15% increase in crisis episodes on days with above-median schizophrenia-related Twitter posts. A temporal association was thus found between Twitter-wide mental health-related social media content and crisis episodes in mental healthcare replicated across two services. Seven-day associations are consistent with both precipitating and longer-term risk associations. Sizes of effects were large enough to have potential local and national relevance and further research is needed to evaluate how services might better anticipate times of higher risk and identify the most vulnerable groups.

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.

People with psychosis have a reduced life expectancy of 10–20 years, largely due to cardiovascular disease. This trial aimed to determine the effectiveness of a modular health promotion intervention (IMPaCT Therapy) in improving health and reducing cardiovascular risk in psychosis. A multicentre, two arm, parallel cluster RCT was conducted across five UK mental health NHS trusts. Community care coordinators (CC) were randomly assigned to training and supervision in delivering IMPaCT Therapy or treatment as usual (TAU) to current patients with psychosis (cluster). The primary outcome was the physical and mental health subscales of the Short form-36 (SF-36) questionnaire. Of 104 care coordinators recruited, 52 (with 213 patients) were randomised to deliver IMPaCT therapy and 52 (with 193 patients) randomised to TAU. Of 406 patients, 318 (78%) and 301 (74%) attended 12- and 15-month follow-up respectively. IMPaCT therapy showed no significant effect on the physical or mental health component SF-36 scores versus TAU at 12 or 15 months. No effect was observed for cardiovascular risk indicators, except for HDL cholesterol, which improved more with IMPACT therapy than TAU (Treatment effect (95% CI); 0.085 (0.007 to 0.16); p = 0.034). The 22% of patients who received >180 min of IMPACT Therapy in addition to usual care achieved a greater reduction in waist circumference than did controls, which was clinically significant. Training and supervising community care coordinators to use IMPaCT therapy in patients with psychosis is insufficient to significantly improve physical or mental health quality of life. The search for effective, pragmatic interventions deliverable in health care services continues. The trial was retrospectively registered with ISRCTN registry on 23/4/2010 at ISRCTN58667926 ; recruitment started on 01/03/2010 with first randomization on 09.08.2010 ISRCTN58667926 .