1-year health outcomes associated with systemic corticosteroids for COVID-19: a longitudinal cohort study.

Background: In patients with coronavirus disease 2019 (COVID-19) requiring supplemental oxygen, dexamethasone reduces acute severity and improves survival, but longer-term effects are unknown. We hypothesised that systemic corticosteroid administration during acute COVID-19 would be associated with improved health-related quality of life (HRQoL) 1 year after discharge. Methods: Adults admitted to hospital between February 2020 and March 2021 for COVID-19 and meeting current guideline recommendations for dexamethasone treatment were included using two prospective UK cohort studies (Post-hospitalisation COVID-19 and the International Severe Acute Respiratory and emerging Infection Consortium). HRQoL, assessed by the EuroQol-Five Dimensions-Five Levels utility index (EQ-5D-5L UI), pre-hospital and 1 year after discharge were compared between those receiving corticosteroids or not after propensity weighting for treatment. Secondary outcomes included patient-reported recovery, physical and mental health status, and measures of organ impairment. Sensitivity analyses were undertaken to account for survival and selection bias. Findings: Of the 1888 participants included in the primary analysis, 1149 received corticosteroids. There was no between-group difference in EQ-5D-5L UI at 1 year (mean difference 0.004, 95% CI -0.026-0.034). A similar reduction in EQ-5D-5L UI was seen at 1 year between corticosteroid exposed and nonexposed groups (mean±sd change -0.12±0.22 versus -0.11±0.22). Overall, there were no differences in secondary outcome measures. After sensitivity analyses modelled using a cohort of 109 318 patients admitted to hospital with COVID-19, EQ-5D-5L UI at 1 year remained similar between the two groups. Interpretation: Systemic corticosteroids for acute COVID-19 have no impact on the large reduction in HRQoL 1 year after hospital discharge. Treatments to address the persistent reduction in HRQoL are urgently needed.

Artificial intelligence and cybercrime: implications for individuals and the healthcare sector.

The malicious use of artificial intelligence is growing rapidly, creating major security threats for individuals and the healthcare sector. Individuals with mental illness may be especially vulnerable. Healthcare provider data are a prime target for cybercriminals. There is a need to improve cybersecurity to detect and prevent cyberattacks against individuals and the healthcare sector, including the use of artificial intelligence predictive tools.

Cognitive and psychiatric symptom trajectories 2-3 years after hospital admission for COVID-19: a longitudinal, prospective cohort study in the UK.

BACKGROUND: COVID-19 is known to be associated with increased risks of cognitive and psychiatric outcomes after the acute phase of disease. We aimed to assess whether these symptoms can emerge or persist more than 1 year after hospitalisation for COVID-19, to identify which early aspects of COVID-19 illness predict longer-term symptoms, and to establish how these symptoms relate to occupational functioning. METHODS: The Post-hospitalisation COVID-19 study (PHOSP-COVID) is a prospective, longitudinal cohort study of adults (aged ≥18 years) who were hospitalised with a clinical diagnosis of COVID-19 at participating National Health Service hospitals across the UK. In the C-Fog study, a subset of PHOSP-COVID participants who consented to be recontacted for other research were invited to complete a computerised cognitive assessment and clinical scales between 2 years and 3 years after hospital admission. Participants completed eight cognitive tasks, covering eight cognitive domains, from the Cognitron battery, in addition to the 9-item Patient Health Questionnaire for depression, the Generalised Anxiety Disorder 7-item scale, the Functional Assessment of Chronic Illness Therapy Fatigue Scale, and the 20-item Cognitive Change Index (CCI-20) questionnaire to assess subjective cognitive decline. We evaluated how the absolute risks of symptoms evolved between follow-ups at 6 months, 12 months, and 2-3 years, and whether symptoms at 2-3 years were predicted by earlier aspects of COVID-19 illness. Participants completed an occupation change questionnaire to establish whether their occupation or working status had changed and, if so, why. We assessed which symptoms at 2-3 years were associated with occupation change. People with lived experience were involved in the study. FINDINGS: 2469 PHOSP-COVID participants were invited to participate in the C-Fog study, and 475 participants (191 [40·2%] females and 284 [59·8%] males; mean age 58·26 [SD 11·13] years) who were discharged from one of 83 hospitals provided data at the 2-3-year follow-up. Participants had worse cognitive scores than would be expected on the basis of their sociodemographic characteristics across all cognitive domains tested (average score 0·71 SD below the mean [IQR 0·16-1·04]; p<0·0001). Most participants reported at least mild depression (263 [74·5%] of 353), anxiety (189 [53·5%] of 353), fatigue (220 [62·3%] of 353), or subjective cognitive decline (184 [52·1%] of 353), and more than a fifth reported severe depression (79 [22·4%] of 353), fatigue (87 [24·6%] of 353), or subjective cognitive decline (88 [24·9%] of 353). Depression, anxiety, and fatigue were worse at 2-3 years than at 6 months or 12 months, with evidence of both worsening of existing symptoms and emergence of new symptoms. Symptoms at 2-3 years were not predicted by the severity of acute COVID-19 illness, but were strongly predicted by the degree of recovery at 6 months (explaining 35·0-48·8% of the variance in anxiety, depression, fatigue, and subjective cognitive decline); by a biocognitive profile linking acutely raised D-dimer relative to C-reactive protein with subjective cognitive deficits at 6 months (explaining 7·0-17·2% of the variance in anxiety, depression, fatigue, and subjective cognitive decline); and by anxiety, depression, fatigue, and subjective cognitive deficit at 6 months. Objective cognitive deficits at 2-3 years were not predicted by any of the factors tested, except for cognitive deficits at 6 months, explaining 10·6% of their variance. 95 of 353 participants (26·9% [95% CI 22·6-31·8]) reported occupational change, with poor health being the most common reason for this change. Occupation change was strongly and specifically associated with objective cognitive deficits (odds ratio [OR] 1·51 [95% CI 1·04-2·22] for every SD decrease in overall cognitive score) and subjective cognitive decline (OR 1·54 [1·21-1·98] for every point increase in CCI-20). INTERPRETATION: Psychiatric and cognitive symptoms appear to increase over the first 2-3 years post-hospitalisation due to both worsening of symptoms already present at 6 months and emergence of new symptoms. New symptoms occur mostly in people with other symptoms already present at 6 months. Early identification and management of symptoms might therefore be an effective strategy to prevent later onset of a complex syndrome. Occupation change is common and associated mainly with objective and subjective cognitive deficits. Interventions to promote cognitive recovery or to prevent cognitive decline are therefore needed to limit the functional and economic impacts of COVID-19. FUNDING: National Institute for Health and Care Research Oxford Health Biomedical Research Centre, Wolfson Foundation, MQ Mental Health Research, MRC-UK Research and Innovation, and National Institute for Health and Care Research.

Implications of Online Self-Diagnosis in Psychiatry.

Online self-diagnosis of psychiatric disorders by the general public is increasing. The reasons for the increase include the expansion of Internet technologies and the use of social media, the rapid growth of direct-to-consumer e-commerce in healthcare, and the increased emphasis on patient involvement in decision making. The publicity given to artificial intelligence (AI) has also contributed to the increased use of online screening tools by the general public. This paper aims to review factors contributing to the expansion of online self-diagnosis by the general public, and discuss both the risks and benefits of online self-diagnosis of psychiatric disorders. A narrative review was performed with examples obtained from the scientific literature and commercial articles written for the general public. Online self-diagnosis of psychiatric disorders is growing rapidly. Some people with a positive result on a screening tool will seek professional help. However, there are many potential risks for patients who self-diagnose, including an incorrect or dangerous diagnosis, increased patient anxiety about the diagnosis, obtaining unfiltered advice on social media, using the self-diagnosis to self-treat, including online purchase of medications without a prescription, and technical issues including the loss of privacy. Physicians need to be aware of the increase in self-diagnosis by the general public and the potential risks, both medical and technical. Psychiatrists must recognize that the general public is often unaware of the challenging medical and technical issues involved in the diagnosis of a mental disorder, and be ready to treat patients who have already obtained an online self-diagnosis.

Post-acute COVID-19 neuropsychiatric symptoms are not associated with ongoing nervous system injury.

A proportion of patients infected with severe acute respiratory syndrome coronavirus 2 experience a range of neuropsychiatric symptoms months after infection, including cognitive deficits, depression and anxiety. The mechanisms underpinning such symptoms remain elusive. Recent research has demonstrated that nervous system injury can occur during COVID-19. Whether ongoing neural injury in the months after COVID-19 accounts for the ongoing or emergent neuropsychiatric symptoms is unclear. Within a large prospective cohort study of adult survivors who were hospitalized for severe acute respiratory syndrome coronavirus 2 infection, we analysed plasma markers of nervous system injury and astrocytic activation, measured 6 months post-infection: neurofilament light, glial fibrillary acidic protein and total tau protein. We assessed whether these markers were associated with the severity of the acute COVID-19 illness and with post-acute neuropsychiatric symptoms (as measured by the Patient Health Questionnaire for depression, the General Anxiety Disorder assessment for anxiety, the Montreal Cognitive Assessment for objective cognitive deficit and the cognitive items of the Patient Symptom Questionnaire for subjective cognitive deficit) at 6 months and 1 year post-hospital discharge from COVID-19. No robust associations were found between markers of nervous system injury and severity of acute COVID-19 (except for an association of small effect size between duration of admission and neurofilament light) nor with post-acute neuropsychiatric symptoms. These results suggest that ongoing neuropsychiatric symptoms are not due to ongoing neural injury.

Artificial intelligence and increasing misinformation.

With the recent advances in artificial intelligence (AI), patients are increasingly exposed to misleading medical information. Generative AI models, including large language models such as ChatGPT, create and modify text, images, audio and video information based on training data. Commercial use of generative AI is expanding rapidly and the public will routinely receive messages created by generative AI. However, generative AI models may be unreliable, routinely make errors and widely spread misinformation. Misinformation created by generative AI about mental illness may include factual errors, nonsense, fabricated sources and dangerous advice. Psychiatrists need to recognise that patients may receive misinformation online, including about medicine and psychiatry.

Individual-level risk factors for suicide mortality in the general population: an umbrella review.

BACKGROUND: Deaths by suicide remain a major public health challenge worldwide. Identifying and targeting risk factors for suicide mortality is a potential approach to prevention. We aimed to summarise current knowledge on the range and magnitude of individual-level risk factors for suicide mortality in the general population and evaluate the quality of the evidence. METHODS: In this umbrella review, five bibliographic databases were systematically searched for articles published from database inception to Aug 31, 2022. We included meta-analyses of observational studies on individual-level risk factors for suicide mortality in the general population. Biological, genetic, perinatal, and ecological risk factors were beyond the scope of this study. Effect sizes were synthesised and compared across domains. To test robustness and consistency of the findings, evidence for small-study effects and excess significance bias (ie, the ratio between the overall meta-analysis effect size and that of its largest included study) was examined, and prediction intervals were calculated. Risk of bias was assessed by the Risk of Bias in Systematic Reviews instrument. The protocol was pre-registered with PROSPERO (CRD42021230119). FINDINGS: We identified 33 meta-analyses on 38 risk factors for suicide mortality in the general population. 422 (93%) of the 454 primary studies included in the meta-analyses were from high-income countries. A previous suicide attempt and suicidal ideation emerged as strong risk factors (with effect sizes ranging from 6 to 16). Psychiatric disorders were associated with a greatly elevated risk of suicide mortality, with risk ratios in the range of 4-13. Suicide risk for physical illnesses (such as cancer and epilepsy) and sociodemographic factors (including unemployment and low education) were typically increased two-fold. Contact with the criminal justice system, state care in childhood, access to firearms, and parental death by suicide also increased the risk of suicide mortality. Among risk factors for which sex-stratified analyses were available, associations were generally similar for males and females. However, the quality of the evidence was limited by excess significance and high heterogeneity, and prediction intervals suggested poor replicability for almost two-thirds of identified risk factors. INTERPRETATION: A wide range of risk factors were identified across various domains, which underscores suicide mortality as a multifactorial phenomenon. Prevention strategies that span individual and population approaches should account for the identified factors and their relative strengths. Despite the large number of risk factors investigated, few associations were supported by robust evidence. Evidence of causal inference will need to be tested in high-quality study designs. FUNDING: Wellcome Trust.

Acute blood biomarker profiles predict cognitive deficits 6 and 12 months after COVID-19 hospitalization.

Post-COVID cognitive deficits, including 'brain fog', are clinically complex, with both objective and subjective components. They are common and debilitating, and can affect the ability to work, yet their biological underpinnings remain unknown. In this prospective cohort study of 1,837 adults hospitalized with COVID-19, we identified two distinct biomarker profiles measured during the acute admission, which predict cognitive outcomes 6 and 12 months after COVID-19. A first profile links elevated fibrinogen relative to C-reactive protein with both objective and subjective cognitive deficits. A second profile links elevated D-dimer relative to C-reactive protein with subjective cognitive deficits and occupational impact. This second profile was mediated by fatigue and shortness of breath. Neither profile was significantly mediated by depression or anxiety. Results were robust across secondary analyses. They were replicated, and their specificity to COVID-19 tested, in a large-scale electronic health records dataset. These findings provide insights into the heterogeneous biology of post-COVID cognitive deficits.

Challenges and Ethical Considerations to Successfully Implement Artificial Intelligence in Clinical Medicine and Neuroscience: a Narrative Review.

This narrative review discusses how the safe and effective use of clinical artificial intelligence (AI) prediction tools requires recognition of the importance of human intelligence. Human intelligence, creativity, situational awareness, and professional knowledge, are required for successful implementation. The implementation of clinical AI prediction tools may change the workflow in medical practice resulting in new challenges and safety implications. Human understanding of how a clinical AI prediction tool performs in routine and exceptional situations is fundamental to successful implementation. Physicians must be involved in all aspects of the selection, implementation, and ongoing product monitoring of clinical AI prediction tools.

Telepsychiatry in an Era of Digital Mental Health Startups.

PURPOSE OF REVIEW: Telepsychiatry practiced by psychiatrists is evidence-based, regulated, private, and effective in diverse settings. The use of telemedicine has grown since the COVID-19 pandemic as people routinely obtain more healthcare services online. At the same time, there has been a rapid increase in the number of digital mental health startups that offer various services including online therapy and access to prescription medications. These digital mental health firms advertise directly to the consumer primarily through digital advertising. The purpose of this narrative review is to contrast traditional telepsychiatry and the digital mental health market related to online therapy. RECENT FINDINGS: In contrast to standard telepsychiatry, most of the digital mental health startups are unregulated, have unproven efficacy, and raise concerns related to self-diagnosis, self-medicating, and inappropriate prescribing. The role of digital mental health firms for people with serious mental illness has not been determined. There are inadequate privacy controls for the digital mental health firms, including for online therapy. We live in an age where there is widespread admiration for technology entrepreneurs and increasing emphasis on the role of the patient as a consumer. Yet, the business practices of digital mental health startups may compromise patient safety for profits. There is a need to address issues with the digital mental health startups and to educate patients about the differences between standard medical care and digital mental health products.

Community interventions for anxiety and depression in adults and young people: A systematic review.

BACKGROUND: Growing evidence suggests that community-based interventions may be effective for anxiety and depression. This study aimed to describe studies of community interventions delivered to adults and/or young people, either in person or online, evaluated in randomised controlled trials and provide an indication as to their effectiveness, acceptability, quality of data and where possible, mechanisms of action. We included interventions delivered at and/or by museums, art galleries, libraries, gardens, music groups/choirs and sports clubs. METHOD: We developed and followed a preregistered protocol: PROSPERO CRD42020204471. Randomised controlled trials in adults and young people were identified in an extensive search with no date/time, language, document type and publication status limitations. Studies were selected according to predetermined eligibility criteria and data independently extracted and then assessed using Risk of Bias 1. The studies were deemed too heterogeneous for meta-analysis and were therefore reported using a narrative synthesis. RESULTS: Our analysis included 31 studies, with 2898 participants. Community interventions most studied in randomised controlled trials were community music (12 studies, 1432 participants), community exercise (14 studies, 955 participants) and community gardens/gardening (6 studies, 335 participants). The majority of studies were from high-income countries - many were in specific populations (such as those with physical health problems) and were generally of low quality. Dropout rates across the included studies were low (1 participant on average per 100 participants). The inadequate description of interventions limited identification of potential mechanisms of action. DISCUSSION: The uncertainty of the evidence allows only a weak recommendation in support of community interventions for anxiety and depression. The results suggest community engagement is a promising area for wide-reaching interventions to be implemented and evaluated, but more high-quality trials are needed, especially in young people and under-represented communities.

A co-produced online cultural experience compared to a typical museum website for mental health in people aged 16-24: A proof-of-principle randomised controlled trial.

OBJECTIVE: We aimed to compare a co-produced online intervention encompassing the diverse human stories behind art and artefacts, named Ways of Being (WoB), with a typical museum website, the Ashmolean (Ash) on negative affect (NA), positive affect (PA) and psychological distress (K10). METHODS: In this parallel group RCT, 463 YP aged 16-24 were randomly assigned, 231 to WoB and 232 to Ash. RESULTS: Over the intervention phase (an aggregate score including all post-allocation timepoints to day-five) a group difference was apparent in favour of WoB for NA (WoB-Ash n=448, NA -0.158, p=0.010) but no differences were detected for PA or K10 and differences were not detected at week six. Group differences in NA in favour of WoB were detected in specific subgroups, e.g. ethnic minorities and males. Across participants (from both groups) mean K10 and NA improved between baseline and six weeks despite increased COVID-19 restrictions. Trial recruitment was rapid, retention high and feedback positive with broad geographical, occupational and ethnic diversity. CONCLUSIONS: Online engagement with arts and culture has the potential to impact on mental health in a measurable way in YP with high unmet mental health needs.

Impact of the COVID-19 Pandemic on the Global Delivery of Mental Health Services and Telemental Health: Systematic Review.

BACKGROUND: The COVID-19 pandemic required mental health services around the world to adapt quickly to the new restrictions and regulations put in place to reduce the risk of transmission. As face-to-face contact became difficult, virtual methods were implemented to continue to safely provide mental health care. However, it is unclear to what extent service provision transitioned to telemental health worldwide. OBJECTIVE: We aimed to systematically review the global research literature on how mental health service provision adapted during the first year of the pandemic. METHODS: We searched systematically for quantitative papers focusing on the impact of the COVID-19 pandemic on mental health services published until April 13, 2021, in the PubMed, Embase, medRxiv, and bioXriv electronic bibliographic databases, using the COVID-19 Open Access Project online platform. The screening process and data extraction were independently completed by at least two authors, and any disagreement was resolved by discussion with a senior member of the team. The findings were summarized narratively in the context of each country's COVID-19 Stringency Index, which reflects the stringency of a government's response to COVID-19 restrictions at a specific time. RESULTS: Of the identified 24,339 records, 101 papers were included after the screening process. Reports on general services (n=72) showed that several countries' face-to-face services reduced their activities at the start of the pandemic, with reductions in the total number of delivered visits and with some services forced to close. In contrast, telemental health use rapidly increased in many countries across the world at the beginning of the pandemic (n=55), with almost complete virtualization of general and specialistic care services by the end of the first year. Considering the reported COVID-19 Stringency Index values, the increased use of virtual means seems to correspond to periods when the Stringency Index values were at their highest in several countries. However, due to specific care requirements, telemental health could not be used in certain subgroups of patients, such as those on clozapine or depot treatments and those who continued to need face-to-face visits. CONCLUSIONS: During the pandemic, mental health services had to adapt quickly in the short term, implementing or increasing the use of telemental health services across the globe. Limited access to digital means, poor digital skills, and patients' preferences and individual needs may have contributed to differences in implementing and accessing telemental health services during the pandemic. In the long term, a blended approach, combining in-person and virtual modalities, that takes into consideration the needs, preferences, and digital skills of patients may better support the future development of mental health services. It will be required to improve confidence with digital device use, training, and experience in all modalities for both clinicians and service users.

Using a generative model of affect to characterize affective variability and its response to treatment in bipolar disorder.

The affective variability of bipolar disorder (BD) is thought to qualitatively differ from that of borderline personality disorder (BPD), with changes in affect persisting longer in BD. However, quantitative studies have not been able to confirm this distinction. It has therefore not been possible to accurately quantify how treatments like lithium influence affective variability in BD. We assessed the affective variability associated with BD and BPD as well as the effect of lithium using a computational model that defines two subtypes of variability: affective changes that persist (volatility) and changes that do not (noise). We hypothesized that affective volatility would be raised in the BD group, noise would be raised in the BPD group, and that lithium would impact affective volatility. Daily affect ratings were prospectively collected for up to 3 y from patients with BD or BPD and nonclinical controls. In a separate experimental medicine study, patients with BD were randomized to receive lithium or placebo, with affect ratings collected from week -2 to +4. We found a diagnostically specific pattern of affective variability. Affective volatility was raised in patients with BD, whereas affective noise was raised in patients with BPD. Rather than suppressing affective variability, lithium increased the volatility of positive affect in both studies. These results provide a quantitative measure of the affective variability associated with BD and BPD. They suggest a mechanism of action for lithium, whereby periods of persistently low or high affect are avoided by increasing the volatility of affective responses.

Sleep deprivation as a treatment for major depressive episodes: A systematic review and meta-analysis.

Sleep deprivation, alone or in combination with pharmacological treatment and as part of a chronotherapy package, is of potential use for people with major depressive episodes, however the evidence base is still conflicting. The aim of this systematic review and meta-analysis is to assess the clinical effects of sleep deprivation in comparison to any other intervention for the acute and long-term treatment of mood disorders. We searched electronic databases and trial registries (last update: 16th October 2021) for published and unpublished randomised controlled trials recruiting participants with a major depressive episode in unipolar or bipolar affective disorder. The clinical outcomes of interest were the reduction in depressive symptoms at different timepoints and the number of participants experiencing at least one side effect. Overall, 29 trials (1246 participants) were included. We did not find any difference in change in symptoms or all-cause discontinuation between interventions including SD compared to a control of the same intervention except without SD. In the included studies there were no available data for adverse events. Using the most methodologically rigorous approach, we did not find evidence that the addition of sleep deprivation to treatment packages leads to enhanced depressive outcomes.

Patient perspectives of lithium and quetiapine augmentation treatment in treatment-resistant depression: A qualitative assessment.

BACKGROUND: Treatment-resistant depression (TRD) has a profound cost to patients and healthcare services worldwide. Pharmacological augmentation is one therapeutic option for TRD, with lithium and quetiapine currently recommended as first-line agents. Patient opinions about pharmacological augmentation may affect treatment outcomes, yet these have not been systematically explored. AIMS: This study aimed to qualitatively assess patient experiences of lithium and quetiapine augmentation. METHODS: Semi-structured interviews were conducted with 32 patients from the ongoing lithium versus quetiapine open-label trial comparing these augmentation agents in patients with TRD. Interviews were audio recorded, transcribed and a thematic analysis was used to assess patient opinions of each agent. RESULTS: Four main themes were generated from the thematic analysis: 'Initial concerns', 'Experience of side effects', 'Perception of treatment efficacy' and 'Positive perception of treatment monitoring'. Patient accounts indicated a predominantly positive experience of lithium and quetiapine augmentation. Greater apprehension about side effects was reported for lithium prior to treatment initiation, but greater experience of negative side effects was reported for quetiapine. Clinical monitoring was perceived positively. CONCLUSION: Patient accounts suggested treatment augmentation with lithium or quetiapine was acceptable and helpful for most patients. However, anticipation and experiences of adverse side effects may prevent some patients from benefitting from these treatments.