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SummaryDigital phenotyping (such as using live data from personal digital devices on sleep, activity and social media interactions) to monitor and interpret people's current mental state is a newly emerging development in psychiatry. This article offers an imaginary insight into its future potential for both psychiatrist and patient.

Background: Remote monitoring and digital phenotyping harbor potential to aid clinical diagnosis, predict episode course and recognize early signs of mental health crises. Digital communication metrics, such as phone call and short message service (SMS) use may represent novel biomarkers of mood and diagnosis in Bipolar Disorder (BD) and Borderline Personality Disorder (BPD).Materials and Methods: BD (n = 17), BPD (n = 17) and Healthy Control (HC, n = 21) participants used a smartphone application which monitored phone calls and SMS messaging, alongside self-reported mood. Linear mixed-effects regression models were used to assess the association between digital communications and mood symptoms, mood state, trait-impulsivity, diagnosis and the interaction effect between mood and diagnosis.Results: Transdiagnostically, self-rated manic symptoms and manic state were positively associated with total and outgoing call frequency and cumulative total, incoming and outgoing call duration. Manic symptoms were also associated with total and outgoing SMS frequency. Transdiagnostic depressive symptoms were associated with increased mean incoming call duration. For the different diagnostic groups, BD was associated with increased total call frequency and BPD with increased total and outgoing SMS frequency and length compared to HC. Depression in BD, but not BPD, was associated with decreased total and outgoing call frequency, mean total and outgoing call duration and total and outgoing SMS frequency. Finally, trait-impulsivity was positively associated with total call frequency, total and outgoing SMS frequency and cumulative total and outgoing SMS length.Conclusion: These results identify a general increase in phone call and SMS communications associated with self-reported manic symptoms and a diagnosis-moderated decrease in communications associated with depression in BD, but not BPD, participants. These findings may inform the development of clinical tools to aid diagnosis and remote symptom monitoring, as well as informing understanding of differential psychopathologies in BD and BPD.

A previously healthy 51-year-old woman presented to the ED with a one-week history of malaise, myalgia, unsteadiness, and an intermittent mild headache. Physical examination revealed neurological signs including a broad-based gait and bilateral low amplitude tremor. Laboratory testing of electrolytes revealed acute severe hyponatremia (115 mmol/L). Further, history-taking revealed increased urinary frequency following regular consumption of an over-the-counter detoxification tea product. The patient made a good recovery following admission to the intensive care unit. We identify similar cases in the literature and explore potential causal mechanisms. This case highlights the importance of enquiring about the use of supplementary health products when taking a history, and specifically identifies a growing number of reports of acute severe hyponatremia following the use of “detox teas”.

The normal spectrum trait measures of mood instability and impulsivity are implicated in and comprise core symptoms of several psychiatric disorders. A bidirectional relationship between these traits and sleep disturbance and circadian rhythm dysfunction has been hypothesised, although has not been systematically assessed using objective measures in naturalistic settings. We systematically reviewed the literature following PRISMA guidelines, according to a pre-registered protocol (PROSPERO: CRD 42018108213). Peer-reviewed quantitative studies assessing an association between actigraphic variables and any measure of mood instability or impulsivity in participants aged 12–65 years old were included. Studies were critically appraised using the AXIS tool. Twenty-three articles were retained for inclusion. There was significant heterogeneity in the selection and reporting of actigraphic variables and metrics of mood instability and impulsivity. We identified emerging evidence of a positive association between circadian rest-activity pattern disturbance and delayed sleep timing with both mood instability and impulsivity. Evidence for an association with sleep duration, sleep efficiency or sleep quality was inconsistent. Future research should focus on longitudinal intra-individual associations to establish the directionality between these measures and may lead to the development of chronotherapeutic interventions for a number of psychiatric disorders.

AimsPrevious research suggests the prevalence of mental health conditions among medical inpatients may be as high as 38%. Anecdotally, junior doctors report lacking the confidence, knowledge and skills to assess and treat patients with psychiatric conditions. Identifying this unmet need offers potential to improve standards of care and achieve parity of esteem between psychiatric and medical conditions within the general hospital. Aims:To assess self-reported preparedness of newly-qualified Foundation Doctors to care for patients with acute or chronic psychiatric symptoms in comparison to physical health conditions.MethodIn September of each year (2017, 2018, 2019), a survey was cascaded to all incoming Foundation Year 1 Doctors. For each respective year there were 1673, 961 & 1301 respondents. Respondents were asked to rate their agreement with statements on a Likert scale. Statements pertaining to mental health included “a) I am competent in acute mental health care provision, b) I am competent in chronic mental health care provision” and “I feel confident in prescribing the following drugs; c) drugs for mental health problems”. Comparison statements assessed confidence caring for medically unwell patients, performing practical procedures and prescribing drugs for physical health conditions.ResultPreparedness for acute and chronic mental health were lower than both physical health comparison items; preparedness to care for patients with critical illness (acute: r = 0.794, p < 0.001, chronic: r = 0.556, p < 0.001) and preparedness to perform practical procedures (acute: r = 0.724, p < 0.001, chronic: r = 0.433, p < 0.001).Confidence prescribing mental health drugs was lower than all other comparison items (simple analgesia: r = 0.854, bronchodilators: r = 0.789, antimicrobials: r = 0.772, inhaled steroids: r = 0.720, intravenous fluids: r = 0.702, oral anti-diabetics: r = 0.611, anticoagulants: r = 0.515, narcotics: r = 0.514, insulin: r = 0.206; p < 0.001)ConclusionThese results identify a disparity in foundation doctors’ self-reported preparedness to treat acute and chronic mental health conditions and prescribe psychotropic medications, compared to a variety of physical health domains. To our knowledge this is the first large-scale study to empirically test a potential discrepancy between newly-qualified doctors’ preparedness to treat patients’ mental and physical health needs. Medical school education and foundation training may therefore present a fruitful opportunity to improve care for patients with psychiatric conditions within general hospital settings.

AimsTo assess concordance with guidelines on monitoring vitamin D levels and prescribing prophylaxis or replacement. To assess the association between the implementation of local guidelines and prevalence of vitamin D deficiency.BackgroundVitamin D deficiency is associated with various adverse health outcomes including osteoporosis, fractures and myalgia. Most recently, vitamin D deficiency has been hypothesised as a risk factor for severe COVID-19 infection. Risk factors for vitamin D deficiency include incarceration, ethnicity, diet and a diagnosis of psychiatric disorder. Vitamin D deficiency is known to be prevalent among individuals within forensic mental health institutions.Local Trust guidelines advise that vitamin D levels should be checked within one-month of hospital admission, followed by checks at three-monthly intervals. Recommendations for prescribing depend on patients’ vitamin D levels; deficient (MethodMedical records, laboratory results and drug charts were assessed for a total of 75 patients across 15 wards. Data were collected using a standardised audit tool, including; date of admission, admission vitamin D level, most recent vitamin D level and the dose and frequency of vitamin D prescribed.Result76.4% of patients had their vitamin D levels checked within one month of admission. 66.7% of patients had their vitamin D checked within the last 3 months. For patients with an admission vitamin D level recorded, 43.6% had deficient vitamin D levels, 43.6% had insufficient levels and 12.7% had adequate levels. For patients with a more recent serum vitamin D level, 14.5% had deficient levels, 38.7% had insufficient levels and 46.8% had adequate levels. For patients with a documented serum vitamin D level, 21.4% were prescribed the correct dose, 22.9% were under-dosed, 14.3% were over-dosed and 41.4% received no dose where guidelines suggested they should.ConclusionComparison of admission and most recent vitamin D levels suggests a general improvement in prevalence of vitamin D deficiency associated with the implementation of local guidelines. However, we identify significant areas for improvement. A substantial proportion of patients lacked admission or regular monitoring of vitamin D levels and a substantial proportion of patients were under-dosed or received no dose where guidelines suggested they should have. We propose that better concordance with guidelines may improve clinical outcomes further. This may prove especially important during the COVID-19 pandemic, given a potential association between vitamin D deficiency and severity of respiratory infection.

A previously fit and well 37-year-old male healthcare worker presented with confusion, psychotic symptoms and a suicide attempt in the context of a new COVID-19 diagnosis. Following surgical interventions and an extended admission to the intensive care unit, he made a good recovery in terms of both his physical and mental health. A number of factors likely contributed to his presentation, including SARS-CoV-2 infection, severe insomnia, worry, healthcare worker-related stress, and the unique social and psychological stressors associated with the COVID-19 pandemic. This case highlights the need to further characterise the specific psychiatric sequelae of COVID-19 in community settings, and should remind general medical clinicians to be mindful of comorbid psychiatric symptoms when assessing patients with newly diagnosed COVID-19.

There is increasing interest in clinical prediction models in psychiatry, which focus on developing multivariate algorithms to guide personalized diagnostic or management decisions. The main target of these models is the prediction of treatment response to different antidepressant therapies. This is because the ability to predict response based on patients' personal data may allow clinicians to make improved treatment decisions, and to provide more efficacious or more tolerable medications to the right patient. We searched the literature for systematic reviews about treatment prediction in the context of existing treatment modalities for adult unipolar depression, until July 2019. Treatment effect is defined broadly to include efficacy, safety, tolerability and acceptability outcomes. We first focused on the identification of individual predictor variables that might predict treatment response, and second, we considered multivariate clinical prediction models. Our meta-review included a total of 10 systematic reviews; seven (from 2014 to 2018) focusing on individual predictor variables and three focusing on clinical prediction models. These identified a number of sociodemographic, phenomenological, clinical, neuroimaging, remote monitoring, genetic and serum marker variables as possible predictor variables for treatment response, alongside statistical and machine-learning approaches to clinical prediction model development. Effect sizes for individual predictor variables were generally small and clinical prediction models had generally not been validated in external populations. There is a need for rigorous model validation in large external data-sets to prove the clinical utility of models. We also discuss potential future avenues in the field of personalized psychiatry, particularly the combination of multiple sources of data and the emerging field of artificial intelligence and digital mental health to identify new individual predictor variables.

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The regulator has invited students to give feedback on new guidance on maintaining professional standards