To understand the transmission dynamics of severe acute respiratory coronavirus virus 2 (SARS-CoV-2) in a hospital outbreak to inform infection control actions.

Retrospective cohort study.

General medical and elderly inpatient wards in a hospital in England.

Coronavirus disease 2019 (COVID-19) patients were classified as community or healthcare associated by time from admission to onset or positivity using European Centre for Disease Prevention and Control definitions. COVID-19 symptoms were classified as asymptomatic, nonrespiratory, or respiratory. Infectiousness was calculated from 2 days prior to 14 days after symptom onset or positive test. Cases were defined as healthcare-associated COVID-19 when infection was acquired from the wards under investigation. COVID-19 exposures were calculated based on symptoms and bed proximity to an infectious patient. Risk ratios and adjusted odds ratios (aORs) were calculated from univariable and multivariable logistic regression.

Of 153 patients, 65 were COVID-19 patients and 45 of these were healthcare-associated cases. Exposure to a COVID-19 patient with respiratory symptoms was associated with healthcare-associated infection irrespective of proximity (aOR, 3.81; 95% CI, 1.6.3–8.87). Nonrespiratory exposure was only significant within 2.5 m (aOR, 5.21; 95% CI, 1.15–23.48). A small increase in risk ratio was observed for exposure to a respiratory patient for >1 day compared to 1 day from 2.04 (95% CI, 0.99–4.22) to 2.36 (95% CI, 1.44–3.88).

Respiratory exposure anywhere within a 4-bed bay was a risk, whereas nonrespiratory exposure required bed distance ≤2.5 m. Standard infection control measures required beds to be >2 m apart. Our findings suggest that this may be insufficient to stop SARS-CoV-2 transmission. We recommend improving cohorting and further studies into bed distance and transmission factors.

The Cognitive Battery of the National Institutes of Health Toolbox (NIH-TB) is a collection of assessments that have been adapted and normed for administration across the lifespan and is increasingly used in large-scale population-level research. However, despite increasing adoption in longitudinal investigations of neurocognitive development, and growing recommendations that the Toolbox be used in clinical applications, little is known about the long-term temporal stability of the NIH-TB, particularly in youth.

The present study examined the long-term temporal reliability of the NIH-TB in a large cohort of youth (9–15 years-old) recruited across two data collection sites. Participants were invited to complete testing annually for 3 years.

Reliability was generally low-to-moderate, with intraclass correlation coefficients ranging between 0.31 and 0.76 for the full sample. There were multiple significant differences between sites, with one site generally exhibiting stronger temporal stability than the other.

Reliability of the NIH-TB Cognitive Battery was lower than expected given early work examining shorter test-retest intervals. Moreover, there were very few instances of tests meeting stability requirements for use in research; none of the tests exhibited adequate reliability for use in clinical applications. Reliability is paramount to establishing the validity of the tool, thus the constructs assessed by the NIH-TB may vary over time in youth. We recommend further refinement of the NIH-TB Cognitive Battery and its norming procedures for children before further adoption as a neuropsychological assessment. We also urge researchers who have already employed the NIH-TB in their studies to interpret their results with caution.

Compulsory admission procedures of patients with mental disorders vary between countries in Europe. The Ethics Committee of the European Psychiatric Association (EPA) launched a survey on involuntary admission procedures of patients with mental disorders in 40 countries to gather information from all National Psychiatric Associations that are members of the EPA to develop recommendations for improving involuntary admission processes and promote voluntary care.

The survey focused on legislation of involuntary admissions and key actors involved in the admission procedure as well as most common reasons for involuntary admissions.

We analyzed the survey categorical data in themes, which highlight that both medical and legal actors are involved in involuntary admission procedures.

We conclude that legal reasons for compulsory admission should be reworded in order to remove stigmatization of the patient, that raising awareness about involuntary admission procedures and patient rights with both patients and family advocacy groups is paramount, that communication about procedures should be widely available in lay-language for the general population, and that training sessions and guidance should be available for legal and medical practitioners. Finally, people working in the field need to be constantly aware about the ethical challenges surrounding compulsory admissions.

The symptoms of bipolar disorder are sometimes misrecognised for unipolar depression and inappropriately treated with antidepressants. This may be associated with increased risk of developing mania. However, the extent to which this depends on what type of antidepressant is prescribed remains unclear.

To investigate the association between different classes of antidepressants and subsequent onset of mania/bipolar disorder in a real-world clinical setting.

Data on prior antidepressant therapy were extracted from 21,012 adults with unipolar depression receiving care from the South London and Maudsley NHS Foundation Trust (SLaM). multivariable Cox regression analysis (with age and gender as covariates) was used to investigate the association of antidepressant therapy with risk of developing mania/bipolar disorder.

In total, 91,110 person-years of follow-up data were analysed (mean follow-up: 4.3 years). The overall incidence rate of mania/bipolar disorder was 10.9 per 1000 person-years. The peak incidence of mania/bipolar disorder was seen in patients aged between 26 and 35 years (12.3 per 1000 person-years). The most frequently prescribed antidepressants were SSRIs (35.5%), mirtazapine (9.4%), venlafaxine (5.6%) and TCAs (4.7%). Prior antidepressant treatment was associated with an increased incidence of mania/bipolar disorder ranging from 13.1 to 19.1 per 1000 person-years. Multivariable analysis indicated a significant association with SSRIs (hazard ratio 1.34, 95% CI 1.18–1.52) and venlafaxine (1.35, 1.07–1.70).

In people with unipolar depression, antidepressant treatment is associated with an increased risk of subsequent mania/bipolar disorder. These findings highlight the importance of considering risk factors for mania when treating people with depression.

The authors have not supplied their declaration of competing interest.

In the UK, mental illness is a major source of disease burden costing in the region of £105 billion pounds. mHealth is a novel and emerging field in psychiatric and psychological care for the treatment of mental health difficulties such as psychosis.

To develop an intelligent real-time therapy (iRTT) mobile intervention (TechCare) which assesses participant's symptoms in real-time and responds with a personalised self-help based psychological intervention, with the aim of reducing participant's symptoms. The system will utilise intelligence at two levels:

– intelligently increasing the frequency of assessment notifications if low mood/paranoia is detected;

– an intelligent machine learning algorithm which provides interventions in real-time and also provides recommendations on the most popular selected interventions.

The aim of the current project is to develop a mobile phone intervention for people with psychosis, and to conduct a feasibility study of the TechCare App.

The study consists of both qualitative and quantitative components. The study will be run across three strands:

– qualitative work;

– test run and intervention refinement;

– feasibility trial.

Preliminary analysis of qualitative data from Strand 2 (test run and intervention refinement) in-depth interviews with service users (n = 2) and focus group with health professionals (n = 1), highlighted main themes around security of the device, multimedia and the acceptability of psychological interventions being delivered via the TechCare App.

Research in this area can be potentially helpful in addressing the demand on mental health services globally, particularly improving access to psychological interventions.

The authors have not supplied their declaration of competing interest.

Mood instability is an important problem but has received relatively little research attention. Natural language processing (NLP) is a novel method, which can used to automatically extract clinical data from electronic health records (EHRs).

To extract mood instability data from EHRs and investigate its impact on people with mental health disorders.

Data on mood instability were extracted using NLP from 27,704 adults receiving care from the South London and Maudsley NHS Foundation Trust (SLaM) for affective, personality or psychotic disorders. These data were used to investigate the association of mood instability with different mental disorders and with hospitalisation and treatment outcomes.

Mood instability was documented in 12.1% of people included in the study. It was most frequently documented in people with bipolar disorder (22.6%), but was also common in personality disorder (17.8%) and schizophrenia (15.5%). It was associated with a greater number of days spent in hospital (B coefficient 18.5, 95% CI 12.1–24.8), greater frequency of hospitalisation (incidence rate ratio 1.95, 1.75–2.17), and an increased likelihood of prescription of antipsychotics (2.03, 1.75–2.35).

Using NLP, it was possible to identify mood instability in a large number of people, which would otherwise not have been possible by manually reading clinical records. Mood instability occurs in a wide range of mental disorders. It is generally associated with poor clinical outcomes. These findings suggest that clinicians should screen for mood instability across all common mental health disorders. The data also highlight the utility of NLP for clinical research.

The authors have not supplied their declaration of competing interest.

There are often substantial delays before diagnosis and initiation of treatment in people bipolar disorder. Increased delays are a source of considerable morbidity among affected individuals.

To investigate the factors associated with delays to diagnosis and treatment in people with bipolar disorder.

Retrospective cohort study using electronic health record data from the South London and Maudsley NHS Foundation Trust (SLaM) from 1364 adults diagnosed with bipolar disorder. The following predictor variables were analysed in a multivariable Cox regression analysis on diagnostic delay and treatment delay from first presentation to SLaM: age, gender, ethnicity, compulsory admission to hospital under the UK Mental Health Act, marital status and other diagnoses prior to bipolar disorder.

The median diagnostic delay was 62 days (interquartile range: 17–243) and median treatment delay was 31 days (4–122). Compulsory hospital admission was associated with a significant reduction in both diagnostic delay (hazard ratio 2.58, 95% CI 2.18–3.06) and treatment delay (4.40, 3.63–5.62). Prior diagnoses of other psychiatric disorders were associated with increased diagnostic delay, particularly alcohol (0.48, 0.33–0.41) and substance misuse disorders (0.44, 0.31–0.61). Prior diagnosis of schizophrenia and psychotic depression were associated with reduced treatment delay.

Some individuals experience a significant delay in diagnosis and treatment of bipolar disorder, particularly those with alcohol/substance misuse disorders. These findings highlight a need to better identify the symptoms of bipolar disorder and offer appropriate treatment sooner in order to facilitate improved clinical outcomes. This may include the development of specialist early intervention services.

The authors have not supplied their declaration of competing interest.

Transoral laser microsurgery for glottic squamous cell carcinoma is the standard of care at many institutions. Repeat transoral laser microsurgery for recurrence may avoid the need for radiotherapy and total laryngectomy. This study aimed to identify oncological and functional outcomes in a cohort of patients who had undergone repeat transoral laser microsurgery procedures.

A retrospective review of prospectively collected data of patients treated with transoral laser microsurgery for carcinoma in situ or tumour stages T1 or T2 glottic cancer, from 2003 to 2018.

Twenty patients were identified. Additional treatment was not needed in 45 per cent of patients. The five-year overall survival rate was 90 per cent. The disease-specific survival rate was 100 per cent. The laryngeal preservation rate was 85 per cent. There was improvement in mean Voice Handicap Index-10 scores following repeat transoral laser microsurgery treatment, when comparing the pre- and post-operative periods (mean scores = 15.5 vs 11.5, p = 0.373).

Repeat transoral laser microsurgery can be an oncologically safe alternative to other salvage therapies for glottic squamous cell carcinoma recurrence, without sacrificing functional outcomes.