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Background: Antipsychotic polypharmacy (APP) occurs commonly but it is unclear whether it is associated with an increased risk of adverse drug reactions (ADRs). Electronic health records (EHRs) offer an opportunity to examine APP using real-world data. In this study, we use EHR data to identify periods when patients were prescribed 2 + antipsychotics and compare these with periods of antipsychotic monotherapy. To determine the relationship between APP and subsequent instances of ADRs: QT interval prolongation, hyperprolactinaemia, and increased body weight [body mass index (BMI) ⩾ 25]., Methods: We extracted anonymised EHR data. Patients aged 16 + receiving antipsychotic medication at Camden & Islington NHS Foundation Trust between 1 January 2008 and 31 December 2018 were included. Multilevel mixed-effects logistic regression models were used to elucidate the relationship between APP and the subsequent presence of QT interval prolongation, hyperprolactinaemia, and/or increased BMI following a period of APP within 7, 30, or 180 days respectively., Results: We identified 35 409 observations of antipsychotic prescribing among 13 391 patients. Compared with antipsychotic monotherapy, APP was associated with a subsequent increased risk of hyperprolactinaemia (adjusted odds ratio 2.46; 95% CI 1.87-3.24) and of registering a BMI > 25 (adjusted odds ratio 1.75; 95% CI 1.33-2.31) in the period following the APP prescribing., Conclusions: Our observations suggest that APP should be carefully managed with attention to hyperprolactinaemia and obesity.

Background: Characteristics and outcomes of patients presenting to Emergency Departments (EDs) have been under-examined. This paper describes the characteristics and risk of repeat suicidality amongst patients presenting to EDs with (1) suicidal ideation and (2) self-harm, compared to (3) controls in mental health crisis., Methods: The Clinical Record Interactive Search tool identified 2211 patients who presented to three London EDs with suicidal ideation or self-harm, and 1108 control patients. All patients received a full psychosocial assessment. Chi-squared tests examined group characteristics. Cox regression models assessed the risk of re-presentation with suicidal ideation or self-harm within one year., Results: There were a higher proportion of females and individuals under the age of 25 in the self-harm group. Patients presenting with suicidal ideation or self-harm were more likely to be white, live in more deprived areas, and less likely to receive a psychiatric diagnosis within one year compared to controls. Risk of repeat suicidality within one year was 3-4 times higher in those with baseline suicidal ideation (adjusted HR = 3.66, 95% CI 2.44-5.48) or self-harm (HR = 3.53 95% CI 2.47-5.04) compared to controls., Limitations: To be included patients needed to have a full psychosocial assessment. Incomplete records meant 21.4% of the sample was excluded. This will have introduced bias which might confound observed associations., Conclusion: Individuals presenting with either suicidal ideation or self-harm have similar risk for re-presentation within one year. Both groups would benefit from personalised risk management plans and active follow-up to reduce the risk of repeat suicidal behaviour., Competing Interests: Declaration of Competing Interest None., (Copyright © 2020 Elsevier B.V. All rights reserved.)

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.