Delays before Diagnosis and Initiation of Treatment in Patients Presenting to Mental Health Services with Bipolar Disorder

Discriminant diagnostic validity of paediatric bipolar disorder screening tests: A systematic review and meta-analysis

INTRODUCTION

Bipolar disorders (BD) are among the most significantly impairing of childhood and adolescent psychiatric disorders. Although BD symptoms may begin in adolescence, they are frequently not diagnosed until adulthood, and accordingly BD scales could aid diagnostic assessment in paediatric populations. This review aims to synthesis the evidence for the accuracy of BD symptom index tests for discriminating BD from non-BD (other diagnoses or healthy controls) in paediatric population. Additionally, several theoretically relevant moderators of diagnostic accuracy were evaluated.

METHODS

A systematic search across three databases were conducted from 1980 to 2022, augmented by grey literature database searches, citation chaining and contacting authors. Data from eligible studies were synthesized using meta-analysis. A multilevel model was fitted to account for nested effect sizes, with 31 potential moderators examined in univariate and multivariate models.

RESULTS

Twenty-Eight studies were eligible, yielding 115 effect sizes for analysis. Meta-analytic modelling indicated BD symptom index tests have a high diagnostic accuracy (g = 1.300; 95% CI: 0.982 - 1.619; p < .001) in paediatric population. Accuracy was relative to the type of comparison group, index test content, index test informant and index test's scale or subscale.

CONCLUSIONS

Screening tests based on mania content, caregiver report and non-healthy comparison groups have clinical utility in identifying paediatric BD. Other informant-and-content combination may not accurately identify paediatric BD. Unlike healthy controls, tests derived from studies using non-healthy comparison groups, represent BD symptom non-specificity and BD symptom overlap with other disorders, providing external validity and clinical utility.

Characterization of substance use in homeless patients with mental disorders

BACKGROUND

In Denmark, 42% of homeless people suffer from dual diagnosis, i.e. the co-occurrence of a substance use of alcohol and/or illegal substances and another psychiatric disorder. Dual diagnosis homeless patients often cause differential diagnostic difficulties and fail to receive effective treatment. A solid grasp of the role of substance use in these patients may inform the diagnostic decision and contribute to improve their treatment. Today, knowledge of these issues remains scarce. The purpose of this study was to explore substance use in homeless patients with mental disorders and their subjective perspectives on their substance use.

METHODS

44 homeless dual diagnosis patients were included in the study. They were examined in interviews focusing on their substance use and their subjective perspective on their substance use.

RESULTS

The most frequently used substances were cannabinoids (70.5%) and alcohol (45.5%), followed by cocaine, sedative/hypnotics, and amphetamine. The finding suggests that substance use in dual diagnosis homeless patients is a complex phenomenon with most patients (56.8%) using multiple substances. While substance use seems to contribute to keep the patients homeless, substance use was also reported to play an important role in coping with life on the streets by offering social contact and some relief from a desperate situation.

CONCLUSION

Substance use, mental disorder, and homelessness seem to be closely entangled, reinforcing each other and making it difficult to help these vulnerable patients. Diagnostic overshadowing may cause delays in adequate diagnosis and treatment of this group of patients.

Identifying prior signals of bipolar disorder using primary care electronic health records: a nested case-control study

BACKGROUND

Bipolar disorders are serious mental illnesses, yet evidence suggests that the diagnosis and treatment of bipolar disorder can be delayed by around 6 years.

AIM

To identify signals of undiagnosed bipolar disorder using routinely collected electronic health records.

DESIGN AND SETTING

A nested case-control study conducted using the UK Clinical Practice Research Datalink (CPRD) GOLD dataset, an anonymised electronic primary care patient database linked with hospital records. 'Cases' were adult patients with incident bipolar disorder diagnoses between 1 January 2010 and 31 July 2017.

METHOD

The patients with bipolar disorder (the bipolar disorder group) were matched by age, sex, and registered general practice to 20 'controls' without recorded bipolar disorder (the control group). Annual episode incidence rates were estimated and odds ratios from conditional logistic regression models were reported for recorded health events before the index (diagnosis) date.

RESULTS

There were 2366 patients with incident bipolar disorder diagnoses and 47 138 matched control patients (median age 40 years and 60.4% female: n = 1430/2366 with bipolar disorder and n = 28 471/47 138 without). Compared with the control group, the bipolar disorder group had a higher incidence of diagnosed depressive, psychotic, anxiety, and personality disorders and escalating self-harm up to 10 years before a bipolar disorder diagnosis. Sleep disturbance, substance misuse, and mood swings were more frequent among the bipolar disorder group than the control group. The bipolar disorder group had more frequent face-to-face consultations, and were more likely to miss multiple scheduled appointments and to be prescribed ≥3 different psychotropic medication classes in a given year.

CONCLUSION

Psychiatric diagnoses, psychotropic prescriptions, and health service use patterns might be signals of unreported bipolar disorder. Recognising these signals could prompt further investigation for undiagnosed significant psychopathology, leading to timely referral, assessment, and initiation of appropriate treatments.

Understanding alcohol use and changes in drinking habits among people with a severe mental illness: a qualitative framework analysis study

Introduction

Individuals with a severe mental illness (SMI) are more likely to drink at harmful levels or abstain. While it is known that drinking patterns change over time, the reasons for this among those with a SMI are unclear. This study aimed to (i) explore the experiences with alcohol, particularly in relation to mental health symptoms, and (ii) how drinking patterns have changed over time, among individuals who have a SMI diagnosis, who either currently drink alcohol or no longer drink.

Methods

One-to-one semi-structured telephone interviews were conducted to address the study aims. Current drinkers' alcohol use was assessed using the Alcohol Use Disorder Identification Test. A framework analysis was used to address the study aims with a specific focus on the differences in the experiences with alcohol use between current and former drinkers.

Results

16 participants were interviewed, and five themes were developed. The analysis highlighted how alcohol was increasingly used to cope with (i) trauma, (ii) SMI-related symptoms, or (iii) stress. Among those with a SMI, non-drinking was facilitated through declines in SMI-related symptoms, previous negative consequences due to alcohol and changing the social environment. Current drinking habits were facilitated through changes in the reasons for drinking and adopting different alcohol moderation techniques.

Discussion

Among those with a SMI diagnosis and who either currently drink alcohol or no longer drink, our findings support the self-medication hypothesis and drinking motives model. However, our findings indicate the need for further development of drinking to cope with a focus on symptoms of a SMI and trauma. Our findings also have implications on specialist alcohol and mental health services, the need to improve individuals' understanding of SMI, and the need to identify reasons for drinking among those with a recent diagnosis of a SMI.

Digital Application of Clinical Staging to Support Stratification in Youth Mental Health Services: Validity and Reliability Study

BACKGROUND

As the demand for youth mental health care continues to rise, managing wait times and reducing treatment delays are key challenges to delivering timely and quality care. Clinical staging is a heuristic model for youth mental health that can stratify care allocation according to individuals' risk of illness progression. The application of staging has been traditionally limited to trained clinicians yet leveraging digital technologies to apply clinical staging could increase the scalability and usability of this model in services.

OBJECTIVE

The aim of this study was to validate a digital algorithm to accurately differentiate young people at lower and higher risk of developing mental disorders.

METHODS

We conducted a study with a cohort comprising 131 young people, aged between 16 and 25 years, who presented to youth mental health services in Australia between November 2018 and March 2021. Expert psychiatrists independently assigned clinical stages (either stage 1a or stage 1b+), which were then compared to the digital algorithm's allocation based on a multidimensional self-report questionnaire.

RESULTS

Of the 131 participants, the mean age was 20.3 (SD 2.4) years, and 72% (94/131) of them were female. Ninety-one percent of clinical stage ratings were concordant between the digital algorithm and the experts' ratings, with a substantial interrater agreement (κ=0.67; P<.001). The algorithm demonstrated an accuracy of 91% (95% CI 86%-95%; P=.03), a sensitivity of 80%, a specificity of 93%, and an F1-score of 73%. Of the concordant ratings, 16 young people were allocated to stage 1a, while 103 were assigned to stage 1b+. Among the 12 discordant cases, the digital algorithm allocated a lower stage (stage 1a) to 8 participants compared to the experts. These individuals had significantly milder symptoms of depression (P<.001) and anxiety (P<.001) compared to those with concordant stage 1b+ ratings.

CONCLUSIONS

This novel digital algorithm is sufficiently robust to be used as an adjunctive decision support tool to stratify care and assist with demand management in youth mental health services. This work could transform care pathways and expedite care allocation for those in the early stages of common anxiety and depressive disorders. Between 11% and 27% of young people seeking care may benefit from low-intensity, self-directed, or brief interventions. Findings from this study suggest the possibility of redirecting clinical capacity to focus on individuals in stage 1b+ for further assessment and intervention.

Incidence and associations of hospital delirium diagnoses in 85,979 people with severe mental illness: A data linkage study

INTRODUCTION

Delirium is an acute neuro-psychiatric disturbance precipitated by a range of physical stressors, with high morbidity and mortality. Little is known about its relationship with severe mental illness (SMI).

METHODS

We conducted a retrospective cohort study using linked data analyses of the UK Clinical Practice Research Datalink (CPRD) and Hospital Episodes Statistics (HES) databases. We ascertained yearly hospital delirium incidence from 2000 to 2017 and used logistic regression to identify associations with delirium diagnosis in a population with SMI.

RESULTS

The cohort included 249,047 people with SMI with median follow-up time in CPRD of 6.4 years. A total of 85,979 patients were eligible for linkage to HES. Delirium incidence increased from 0.04 (95% CI 0.02-0.07) delirium associated admissions per 100 person-years in 2000 to 1.05 (95% CI 0.93-1.17) per 100 person-years in 2017, increasing most notably from 2010 onwards. Delirium was associated with older age at study entry (OR 1.05 per year, 95% CI 1.05-1.06), SMI diagnosis of bipolar affective disorder (OR 1.66, 95% CI 1.44-1.93) or other psychosis (OR 1.56, 95% CI 1.35-1.80) relative to schizophrenia, and more physical comorbidities (OR 1.08 per additional comorbidity of the Charlson Comorbidity Index, 95% CI 1.02-1.14). Patients with delirium received more antipsychotic medication during follow-up (1-2 antipsychotics OR 1.65, 95% CI 1.44-1.90; >2 antipsychotics OR 2.49, 95% CI 2.12-2.92).

CONCLUSIONS

The incidence of recorded delirium diagnoses in people with SMI has increased in recent years. Older people prescribed more antipsychotics and with more comorbidities have a higher incidence. Linked electronic health records are feasible for exploring hospital diagnoses such as delirium in SMI.

A systematic review and meta-analysis of delayed help-seeking, delayed diagnosis and duration of untreated illness in bipolar disorders

OBJECTIVES

To examine the time delay between the age at onset of symptoms or episodes of bipolar disorders (BD) and the age at diagnosis of and/or receipt of clinical practice guideline recommended interventions for BD.

METHODS

Systematic search of five databases to identify publications from January 2000 to July 2022 that reported one or more of the following reliable and valid estimates of latency: delay in help seeking (DHS), delay in diagnosis (DD) and duration of untreated BD (DUB). Eligible studies were included in random effects meta-analyses and multivariate meta-regression was used to assess factors associated with each latency construct.

RESULTS

Screening of 1074 publications identified 59 eligible studies (reported in 66 publications) of >40,000 individuals that estimated DHS (8 studies), DD (20 studies) and/or DUB (45 studies). The median DHS, DD and DUB were 3.5 (IQR: 2.8, 8.48), 6.7 (IQR: 5.6, 8.9) and 5.9 years (IQR: 1.1, 8.2), respectively. Key factors associated with shorter DD included older age and residing outside North America; shorter DUB was associated with psychotic or manic onset and access to early intervention services.

CONCLUSIONS

Greater consensus on definitions of latency constructs and better-quality targeted research is required regarding DHS, DD and DUB. This review suggests that, while the peak age at onset of BD is 15-25, diagnosis and guideline recommended interventions (e.g., mood stabilizers) are likely to be delayed until age 25-35 years except for a minority of individuals with access to early intervention services.

Patients Who Die by Suicide: A Study of Treatment Patterns and Patient Safety Incidents in Norway

Underlying patterns and factors behind suicides of patients in treatment are still unclear and there is a pressing need for more studies to address this knowledge gap. We analysed 278 cases of suicide reported to The Norwegian System of Patient Injury Compensation, drawing on anonymised data, i.e., age group, gender, diagnostic category, type of treatment provided, inpatient vs. outpatient status, type of treatment facility, and expert assessments of medical errors. The data originated from compensation claim forms, expert assessments, and medical records. Chi-square tests for independence, multinominal logistic regression, and Bayes factors for independence were used to analyse whether the age group, gender, diagnostic category, inpatient/outpatient status, type of institution, and type of treatment received by patients that had died by suicide were associated with different types of medical errors. Patients who received medication tended to be proportionally more exposed to an insufficient level of observation. Those who received medication and psychotherapy tended to be proportionally more exposed to inadequate treatment, including inadequate medication. Inpatients were more likely to be exposed to inappropriate diagnostics and inadequate treatment and follow up while outpatients to insufficient level of observation and inadequate suicide risk assessment. We conclude that the patients who had received medication as their main treatment tended to have been insufficiently observed, while patients who had received psychotherapy and medication tended to have been provided insufficient treatment, including inadequate medication. These observations may be used as learning points for the suicide prevention of patients in treatment in Norwegian psychiatric services.

Eosinophils to Lymphocytes Ratio (ELR) as a Potential Inflammatory Biomarker in Patients with Dual Diagnosis of Bipolar and Alcohol Use Disorders: A Retrospective Cohort Study

Objective: It is well-established that Bipolar Disorder (BD) has comorbidity with Alcohol Use Disorder (AUD) and could present the same symptoms of an underlying diagnosis of BD, therefore delaying the proper relevant treatment. Recent studies show the occurrence of alterations in the circulating levels of inflammatory mediators in patients dealing with AUD as well as those with BD. The objective of this study is to get an assessment of whether patients with AUD and BD comorbidity [BD(+)] would present different ratios of the Complete Blood Count (CBC) in comparison with patients with AUD but without a BD comorbidity [BD(-)]. Methods: This is a retrospective study, conducted through a selection of patients files who were admitted to the psychiatric department at Hôtel-Dieu de France University Hospital in Beirut, Lebanon, between January of the year 2016 and May of the year 2021. Overall, 83 files of patients dealing with AUD were included in this study. Results: Patients with BD(+) showed a higher Eosinophils to Lymphocytes Ratio (ELR) in comparison to those with BD(-). The Receiver Operation Characteristic (ROC) analysis had an area under the curve at 0.719 with a p = .001. The cutoff value of ELR that best differentiates BD(-) from BD(+) was 0.087 (Sensitivity = 81.3%; Specificity = 63.6%). The logistic regression analysis showed that an ELR superior to 0.087 presented a statistically significant difference, exposing patients belonging to the BD(+) group (OR = 11.66; p < .001). Conclusions: Our data suggest that ELR may be a valuable, reproducible, easily accessible, and cost-effective inflammatory marker, pointing at the presence of a BD comorbidity with AUD.

Process and Outcome Evaluations of Smartphone Apps for Bipolar Disorder: Scoping Review

Background

Mental health apps (MHAs) provide opportunities for accessible, immediate, and innovative approaches to better understand and support the treatment of mental health disorders, especially those with a high burden, such as bipolar disorder (BD). Many MHAs have been developed, but few have had their effectiveness evaluated.

Objective

This systematic scoping review explores current process and outcome measures of MHAs for BD with the aim to provide a comprehensive overview of current research. This will identify the best practice for evaluating MHAs for BD and inform future studies.

Methods

A systematic literature search of the health science databases PsycINFO, MEDLINE, Embase, EBSCO, Scopus, and Web of Science was undertaken up to January 2021 (with no start date) to narratively assess how studies had evaluated MHAs for BD.

Results

Of 4051 original search results, 12 articles were included. These 12 studies included 435 participants, and of these, 343 had BD type I or II. Moreover, 11 of the 12 studies provided the ages (mean 37 years) of the participants. One study did not report age data. The male to female ratio of the 343 participants was 137:206. The most widely employed validated outcome measure was the Young Mania Rating Scale, being used 8 times. The Hamilton Depression Rating Scale-17/Hamilton Depression Rating Scale was used thrice; the Altman Self-Rating Mania Scale, Quick Inventory of Depressive Symptomatology, and Functional Assessment Staging Test were used twice; and the Coping Inventory for Stressful Situations, EuroQoL 5-Dimension Health Questionnaire, Generalized Anxiety Disorder Scale-7, Inventory of Depressive Symptomatology, Mindfulness Attention Awareness Scale, Major Depression Index, Morisky-Green 8-item, Perceived Stress Scale, and World Health Organization Quality of Life-BREF were used once. Self-report measures were captured in 9 different studies, 6 of which used MONARCA. Mood and energy levels were the most commonly used self-report measures, being used 4 times each. Furthermore, 11 of the 12 studies discussed the various confounding factors and barriers to the use of MHAs for BD.

Conclusions

Reported low adherence rates, usability challenges, and privacy concerns act as barriers to the use of MHAs for BD. Moreover, as MHA evaluation is itself developing, guidance for clinicians in how to aid patient choices in mobile health needs to develop. These obstacles could be ameliorated by incorporating co-production and co-design using participatory patient approaches during the development and evaluation stages of MHAs for BD. Further, including qualitative aspects in trials that examine patient experience of both mental ill health and the MHA itself could result in a more patient-friendly fit-for-purpose MHA for BD.

mHealth Solutions for Mental Health Screening and Diagnosis: A Review of App User Perspectives Using Sentiment and Thematic Analysis

Mental health screening and diagnostic apps can provide an opportunity to reduce strain on mental health services, improve patient well-being, and increase access for underrepresented groups. Despite promise of their acceptability, many mental health apps on the market suffer from high dropout due to a multitude of issues. Understanding user opinions of currently available mental health apps beyond star ratings can provide knowledge which can inform the development of future mental health apps. This study aimed to conduct a review of current apps which offer screening and/or aid diagnosis of mental health conditions on the Apple app store (iOS), Google Play app store (Android), and using the m-health Index and Navigation Database (MIND). In addition, the study aimed to evaluate user experiences of the apps, identify common app features and determine which features are associated with app use discontinuation. The Apple app store, Google Play app store, and MIND were searched. User reviews and associated metadata were then extracted to perform a sentiment and thematic analysis. The final sample included 92 apps. 45.65% (n = 42) of these apps only screened for or diagnosed a single mental health condition and the most commonly assessed mental health condition was depression (38.04%, n = 35). 73.91% (n = 68) of the apps offered additional in-app features to the mental health assessment (e.g., mood tracking). The average user rating for the included apps was 3.70 (SD = 1.63) and just under two-thirds had a rating of four stars or above (65.09%, n = 442). Sentiment analysis revealed that 65.24%, n = 441 of the reviews had a positive sentiment. Ten themes were identified in the thematic analysis, with the most frequently occurring being performance (41.32%, n = 231) and functionality (39.18%, n = 219). In reviews which commented on app use discontinuation, functionality and accessibility in combination were the most frequent barriers to sustained app use (25.33%, n = 19). Despite the majority of user reviews demonstrating a positive sentiment, there are several areas of improvement to be addressed. User reviews can reveal ways to increase performance and functionality. App user reviews are a valuable resource for the development and future improvements of apps designed for mental health diagnosis and screening.

The Purinergic System as a Target for the Development of Treatments for Bipolar Disorder

The neurobiological and neurochemical mechanisms underlying the pathophysiology of bipolar disorder are complex and not yet fully understood. From circadian disruption to neuroinflammation, many pathways and signaling molecules are important contributors to bipolar disorder development, some specific to a disease subtype or a cycling episode. Pharmacological agents for bipolar disorder have shown only partial efficacy, including mood stabilizers and antipsychotics. The purinergic hypothesis for bipolar disorder emerges in this scenario as a promising target for further research and drug development, given its role in neurotransmission and neuroinflammation that results in behavioral and mood regulation. Here, we review the basic concepts of purinergic signaling in the central nervous system and its contribution to bipolar disorder pathophysiology. Allopurinol and novel P2X7 receptor antagonists are promising candidates for treating bipolar disorder. We further explore currently available pharmacotherapies and the emerging new purinergic targets for drug development in bipolar disorder.

Long durations from symptom onset to diagnosis and from diagnosis to treatment in obsessive-compulsive disorder: A retrospective self-report study

BACKGROUND

Although obsessive-compulsive disorder (OCD) is one of the most common mental disorders, it takes up to 17 years for patients with OCD to receive adequate therapy. According to existing outdated literature, this study aimed to investigate the current duration between symptom onset and diagnosis and between diagnosis and the beginning of therapy separately.

METHODS

In a cross-sectional study, N = 100 patients diagnosed with OCD undergoing treatment in a psychiatric outpatient department were assessed, using self-report questionnaires on sociodemographic and clinical variables. Based on self-reported information, the durations between age at symptom onset and age at diagnosis, and between age at diagnosis and beginning of therapy were calculated. To investigate associated factors, two subgroups of patients, one with a short duration between symptom onset and diagnosis < 7 years, and another with a long duration between symptom onset and diagnosis ≥ 7 years, respectively, were compared.

RESULTS AND CONCLUSION

Patients reported first symptoms of OCD at a mean age of 18.72 years. The mean duration between age at symptom onset and age at diagnosis was 12.78 years and the mean duration between age at diagnosis and the beginning of therapy was 1.45 years. Subgroup comparison indicated that patients with a short duration between symptom onset and diagnosis were significantly younger than patients with a long duration. However, patients with a short duration between symptom onset and diagnosis were at an older age when they reported first symptoms of OCD. Further, they showed less severe symptoms of OCD, higher functioning levels, and less self-stigmatization than patients with a long duration. It can be concluded that the duration until patients with OCD are diagnosed correctly and receive adequate treatment is still very long. Therefore, the duration between symptom onset and diagnosis should be shortened. Further, the duration between diagnosis and the beginning of therapy could be a good additional approach to reduce the overall duration of untreated disorder.

Substance use as a risk factor for bipolar disorder: A systematic review

Detecting substance use as a predictor of bipolar disorder (BD) is important for clinicians to perform accurate and early diagnosis, as well as better manage the treatment of individuals with BD. The aim of this systematic review was to describe whether substance use is a predictor of BD. A literature search was conducted using the following databases: PubMed, PsycINFO, and Embase. All eligible studies published up to February 9, 2021 were included. This systematic review included 22 studies. We found that 66.7% of the studies assessing overall substance use found that overall substance use was a risk factor for BD. Regarding the specific substances assessed, cannabis use was described as a risk factor for BD in 55.6% of the studies, nonmedical use of prescription medications was a risk factor for BD in 50% of the studies, nicotine was found as a risk factor for BD in 50% of the studies, and alcohol use was described as a risk factor for BD in 42.9% of the studies assessing it. Only one study assessed whether cocaine use was a risk factor for BD and found a significant association. Interestingly, some studies suggested that the greater frequency of cannabis use was associated with greater risk to develop BD or hypomanic/manic symptoms. In conclusion, there is evidence supporting that substance use is a risk factor for BD. Importantly, when assessing the risk factors for BD related to psychoactive substance use, special attention should be given for the frequency of cannabis use.

Toward an Extended Definition of Major Depressive Disorder Symptomatology: Digital Assessment and Cross-validation Study

Background

Diagnosing major depressive disorder (MDD) is challenging, with diagnostic manuals failing to capture the wide range of clinical symptoms that are endorsed by individuals with this condition.

Objective

This study aims to provide evidence for an extended definition of MDD symptomatology.

Methods

Symptom data were collected via a digital assessment developed for a delta study. Random forest classification with nested cross-validation was used to distinguish between individuals with MDD and those with subthreshold symptomatology of the disorder using disorder-specific symptoms and transdiagnostic symptoms. The diagnostic performance of the Patient Health Questionnaire–9 was also examined.

Results

A depression-specific model demonstrated good predictive performance when distinguishing between individuals with MDD (n=64) and those with subthreshold depression (n=140) (area under the receiver operating characteristic curve=0.89; sensitivity=82.4%; specificity=81.3%; accuracy=81.6%). The inclusion of transdiagnostic symptoms of psychopathology, including symptoms of depression, generalized anxiety disorder, insomnia, emotional instability, and panic disorder, significantly improved the model performance (area under the receiver operating characteristic curve=0.95; sensitivity=86.5%; specificity=90.8%; accuracy=89.5%). The Patient Health Questionnaire–9 was excellent at identifying MDD but overdiagnosed the condition (sensitivity=92.2%; specificity=54.3%; accuracy=66.2%).

Conclusions

Our findings are in line with the notion that current diagnostic practices may present an overly narrow conception of mental health. Furthermore, our study provides proof-of-concept support for the clinical utility of a digital assessment to inform clinical decision-making in the evaluation of MDD.

Cognitive-Behavioral Interventions Targeting Alcohol or Other Drug Use and Co-Occurring Mental Health Disorders: A Meta-Analysis

AIMS

This meta-analysis reviewed 15 clinical trials (18 study sites/arms), examining the efficacy of an integrated cognitive-behavioral intervention (CBI) delivered to individuals with an alcohol or other drug use disorder and a co-occurring mental health disorder (AOD/MHD). Outcomes were alcohol or other drug use and mental health symptoms at post-treatment through follow-up.

METHODS

The inverse-variance weighted effect size was calculated for each study and pooled under random effects assumptions.

RESULTS

Integrated CBI showed a small effect size for AOD (g = 0.188, P = 0.061; I2 = 86%, τ2 = 0.126, k = 18) and MHD (g = 0.169, P = 0.024; I2 = 58%, τ2 = 0.052, k = 18) outcomes, although only MHD outcomes were statistically significant. Analysis by subgroup suggested that effect magnitude varied by type of contrast condition (integrated CBI + usual care vs. usual care only; integrated CBI vs. a single-disorder intervention), follow-up time point (post-treatment vs. 3-6 months) and primary AOD/MHD diagnosis, although these sub-groups often contained significant residual heterogeneity. In a series of mixed effects, meta-regression models, demographic factors were non-significant predictors of between-study heterogeneity. For AOD outcomes, greater effects were observed in higher quality studies, but study quality was not related to effect size variability for MHD outcomes.

CONCLUSIONS

The current meta-analysis shows a small and variable effect for integrated CBI with the most promising effect sizes observed for integrated CBI compared with a single disorder intervention (typically an AOD-only intervention) for follow-up outcomes, and for interventions targeting alcohol use and/or post-traumatic stress disorder. Given the clinical and methodological variability within the sample, results should be considered a preliminary, but important step forward in our understanding of treatment for co-occurring AOD/MHD.

The associations of quality of life and general functioning with trauma, borderline intellectual functioning and mild intellectual disability in outpatients with serious mental illness

BACKGROUND

Trauma and intellectual disability are highly prevalent in the serious mental ill (SMI). Little is known of their impact on general functioning and quality of life.

AIM

This study investigated the association of trauma and intellectual disability (ID) with general functioning and quality of life in SMI.

METHODS

Patient characteristics and diagnoses were extracted from electronic patient records. We used the Trauma Screening Questionnaire (TSQ), the Screener for Intelligence and Learning Disabilities (SCIL), the Health of the Nation Outcome Scale (HoNOS) and the Manchester Short Assessment of Quality of Life (MANSA) to asses trauma, intellectual impairment, general functioning and quality of life. Proportions on cut-off scores were analysed with cross-tabulations, questionnaire scores with t-tests. Multivariable associations were determined by logistic regression analysis.

RESULTS

611 patients from an outpatient service were assessed. Trauma and ID were associated with each other (r = -0.207). Trauma was associated with worse general functioning and a lower quality of life. Mild intellectual disability (MID) or borderline intellectual functioning (BIF) were associated with worse general functioning.

CONCLUSIONS

For patients with SMI, trauma and ID should be identified early in care to treat the lower general functioning and quality of life it caused.

The Delta Study - Prevalence and characteristics of mood disorders in 924 individuals with low mood: Results of the of the World Health Organization Composite International Diagnostic Interview (CIDI)

OBJECTIVES

The Delta Study was undertaken to improve the diagnosis of mood disorders in individuals presenting with low mood. The current study aimed to estimate the prevalence and explore the characteristics of mood disorders in participants of the Delta Study, and discuss their implications for clinical practice.

METHODS

Individuals with low mood (Patients Health Questionnaire-9 score ≥5) and either no previous mood disorder diagnosis (baseline low mood group, n = 429), a recent (≤5 years) clinical diagnosis of MDD (baseline MDD group, n = 441) or a previous clinical diagnosis of BD (established BD group, n = 54), were recruited online. Self-reported demographic and clinical data were collected through an extensive online mental health questionnaire and mood disorder diagnoses were determined with the World Health Organization Composite International Diagnostic Interview (CIDI).

RESULTS

The prevalence of BD and MDD in the baseline low mood group was 24% and 36%, respectively. The prevalence of BD among individuals with a recent diagnosis of MDD was 31%. Participants with BD in both baseline low mood and baseline MDD groups were characterized by a younger age at onset of the first low mood episode, more severe depressive symptoms and lower wellbeing, relative to the MDD or low mood groups. Approximately half the individuals with BD diagnosed as MDD (49%) had experienced (hypo)manic symptoms prior to being diagnosed with MDD.

CONCLUSIONS

The current results confirm high under- and misdiagnosis rates of mood disorders in individuals presenting with low mood, potentially leading to worsening of symptoms and decreased well-being, and indicate the need for improved mental health triage in primary care.

The Potential of Research Drawing on Clinical Free Text to Bring Benefits to Patients in the United Kingdom: A Systematic Review of the Literature

Background: The analysis of clinical free text from patient records for research has potential to contribute to the medical evidence base but access to clinical free text is frequently denied by data custodians who perceive that the privacy risks of data-sharing are too high. Engagement activities with patients and regulators, where views on the sharing of clinical free text data for research have been discussed, have identified that stakeholders would like to understand the potential clinical benefits that could be achieved if access to free text for clinical research were improved. We aimed to systematically review all UK research studies which used clinical free text and report direct or potential benefits to patients, synthesizing possible benefits into an easy to communicate taxonomy for public engagement and policy discussions. Methods: We conducted a systematic search for articles which reported primary research using clinical free text, drawn from UK health record databases, which reported a benefit or potential benefit for patients, actionable in a clinical environment or health service, and not solely methods development or data quality improvement. We screened eligible papers and thematically analyzed information about clinical benefits reported in the paper to create a taxonomy of benefits. Results: We identified 43 papers and derived five themes of benefits: health-care quality or services improvement, observational risk factor-outcome research, drug prescribing safety, case-finding for clinical trials, and development of clinical decision support. Five papers compared study quality with and without free text and found an improvement of accuracy when free text was included in analytical models. Conclusions: Findings will help stakeholders weigh the potential benefits of free text research against perceived risks to patient privacy. The taxonomy can be used to aid public and policy discussions, and identified studies could form a public-facing repository which will help the health-care text analysis research community better communicate the impact of their work.

Individualized prediction of 2-year risk of relapse as indexed by psychiatric hospitalization following psychosis onset: Model development in two first episode samples

BACKGROUND

Although most patients with psychotic disorders experience relapse, it is not possible to predict whether or when an individual patient is going to relapse. We aimed to develop a multifactorial risk prediction algorithm for predicting risk of relapse in first episode psychosis (FEP).

METHODS

Data from two prospectively collected cohorts of FEP patients (N = 1803) were used to develop three multiple logistic prediction models to predict risk of relapse (defined as hospitalization) within the first 2 years of onset of psychosis. Model 1 (M1_S1) used data obtained from clinical notes (Sample 1) while model 2 (M2_S2) applied the same set of predictors using data obtained from research interviews (Sample 2). The final model (Sample 2: M3_S2) used the same predictors plus additional detailed information on predictors. Model performance was evaluated employing measures of overall accuracy, calibration, discrimination and internal validation.

RESULTS

In both samples, the 2-year probability of psychiatric hospitalization was 37%. Of all the models, discrimination accuracy was lowest when limited information (such as socio-demographic and clinical parameters) was included in the prediction model. Model M3_S2 using additional information (descriptors of pattern of cannabis, nicotine, alcohol and other illicit drug use) obtained from research interview had the best discrimination accuracy (Harrell's C index 0.749).

CONCLUSIONS

The measures that contributed most to predicting hospitalization are readily accessible in routine clinical practice, suggesting that a risk prediction tool based on these models would be clinically practicable following validation in independent samples and permit a personalized approach to relapse prevention in psychosis.

Gender and mental health service use in bipolar disorder: national cohort study

BACKGROUND

Despite evidence of gender differences in bipolar disorder characteristics and comorbidity, there is little research on the differences in treatment and service use between men and women with bipolar disorder.

AIMS

To use routine data to describe specialist mental health service contact for bipolar disorder, including in-patient, community and support service contacts; to compare clinical characteristics and mental health service use between men and women in contact with secondary services for bipolar disorder.

METHOD

Cross-sectional analysis of mental health patients with bipolar disorder in New Zealand, based on complete national routine health data.

RESULTS

A total of 3639 individuals were in contact with specialist mental health services with a current diagnosis of bipolar disorder in 2015. Of these 58% were women and 46% were aged 45 and over. The 1-year prevalence rate of bipolar disorder leading to contact with specialist mental health services was 1.56 (95% CI 1.50-1.63) per 100 000 women and 1.20 (95% CI 1.14-1.26) per 100 000 men. Rates of bipolar disorder leading to service contact were 30% higher in women than men (rate ratio 1.30, 95% CI 1.22-1.39). The majority (68%) had a diagnosis of bipolar I disorder. Women were more likely to receive only out-patient treatment and have comorbid anxiety whereas more men had substance use disorder, were convicted for crimes when unwell, received compulsory treatment orders and received in-patient treatment.

CONCLUSIONS

Although the prevalence of bipolar disorder is equal between men and women in the population, women were more likely to have contact with specialist services for bipolar disorder but had a lower intensity of service interaction.

Female survivors of intimate partner violence and risk of depression, anxiety and serious mental illness

BACKGROUND

Internationally, intimate partner violence (IPV) cohorts have demonstrated associations with depression and anxiety. However, this association has not yet been described in a UK population, nor has the association with serious mental illness (SMI).

AIMS

To explore the relationship between IPV exposure and mental illness in a UK population.

METHOD

We designed a retrospective cohort study whereby we matched 18 547 women exposed to IPV to 74 188 unexposed women. Outcomes of interest (anxiety, depression and SMI) were identified through clinical codes.

RESULTS

At baseline, 9174 (49.5%) women in the exposed group had some form of mental illness compared with 17 768 (24.0%) in the unexposed group, described as an adjusted odds ratio of 2.62 (95% CI 2.52-2.72). Excluding those with mental illness at baseline, 1254 exposed women (incidence rate 46.62 per 1000 person-years) went on to present with any type of mental illness compared with 3119 unexposed women (incidence rate 14.93 per 1000 person-years), with an aIRR of 2.77 (95% CI 2.58-2.97). Anxiety (aIRR 1.99, 95% CI 1.80-2.20), depression (aIRR 3.05, 95% CI 2.81-3.31) and SMI (aIRR 3.08, 95% CI 2.19-4.32) were all associated with exposure to IPV.

CONCLUSIONS

IPV remains a significant public health issue in the UK. We have demonstrated the significant recorded mental health burden associated with IPV in primary care, at both baseline and following exposure. Clinicians must be aware of this association to reduce mental illness diagnostic delay and improve management of psychological outcomes in this group of patients.

Exploring the reasons cancer survivors do not seek help for their concerns: a descriptive content analysis

PURPOSE

To understand reasons why adult cancer survivors do not seek assistance as they transition from the end of cancer treatment to follow-up care. Understanding these reasons should inform survivorship care, help reduce the burden of suffering and increase quality of life for survivors.

METHODS

A national survey was conducted in collaboration with ten Canadian provinces to identify unmet needs and experiences with follow-up for cancer survivors between one and 3 years post-treatment. The survey included open-ended questions to allow respondents to add topics of importance and details that offered a deeper insight into their experiences. This publication presents the analysis of the quantitative data and open-ended responses regarding reasons why the adult cancer population does not seek help with their concerns.

RESULTS

In total, 13 319 respondents answered the question about seeking help. 87% had a physical concern of which 76% did not seek help; 77% had an emotional concern of which 82% did not seek help; and 45% had a practical concern of which 71% did not seek help. Frequently identified reasons for not seeking help included being told it was normal and not thinking anything could be done, not wanting to ask, not thinking services were available, handling it on their own and not thinking it was serious enough to seek help.

CONCLUSIONS

Survivors have multiple reasons for not seeking help for their concerns. These findings can be useful to healthcare providers in proactively identifying and addressing the needs of these survivors.

Diagnostic conversion from unipolar depression to bipolar disorder, schizophrenia, or schizoaffective disorder: A nationwide prospective 15-year register study on 43 495 inpatients

OBJECTIVE

To examine temporal patterns and predictors for diagnostic conversion from unipolar depression (UD) to bipolar disorder (BD), schizophrenia, and schizoaffective disorder (SAD).

METHODS

A prospective nationwide register-based cohort (n = 43 495) of all first psychiatric hospitalizations due to UD during 1996-2011 was followed up to 15 years. We used cumulative incidence function (CIF) analyses and the Fine-Gray subdistribution model to define the cumulative incidence of the conversions and subdistribution hazard ratios (SHRs) for predictors.

RESULTS

The overall 15-year cumulative incidence of conversion was 11.1% (95% CI 10.7-11.6): 7.4% (95% CI 7.0-7.8) for BD, 2.5% (95% CI 2.3-2.7) for schizophrenia, and 1.3% (95% CI 1.1-1.4) for SAD. The highest crude incidence rate emerged during the first year. Psychotic depression predicted higher conversion risk to BD (SHR = 2.0, 95% CI 1.5-2.7), schizophrenia (SHR = 5.3, 95% CI 3.3-8.7), and SAD (SHR = 10.6, 95% CI 4.0-28.4) than mild depression. Female sex, greater overall disturbance, and comorbid personality disorder predicted conversion to BD, whereas young age and male sex to psychotic disorders.

CONCLUSIONS

Among patients with first hospitalization due to UD, approximately one in nine converts to another major psychiatric disorder during 15 years, with the highest risk occurring within the first year. Patients with psychotic depression are particularly vulnerable for conversion to other major psychiatric disorders. Conversion to psychotic disorders occurs earlier than to BD. Males are at higher risk for progression to psychotic disorders, whereas females, patients with recurrent depressive episodes, severe disturbance of overall functioning, and personality disorder are at higher risk for converting to BD.

A Combined Digital and Biomarker Diagnostic Aid for Mood Disorders (the Delta Trial): Protocol for an Observational Study

Background

Mood disorders affect hundreds of millions of people worldwide, imposing a substantial medical and economic burden. Existing diagnostic methods for mood disorders often result in a delay until accurate diagnosis, exacerbating the challenges of these disorders. Advances in digital tools for psychiatry and understanding the biological basis of mood disorders offer the potential for novel diagnostic methods that facilitate early and accurate diagnosis of patients.

Objective

The Delta Trial was launched to develop an algorithm-based diagnostic aid combining symptom data and proteomic biomarkers to reduce the misdiagnosis of bipolar disorder (BD) as a major depressive disorder (MDD) and achieve more accurate and earlier MDD diagnosis.

Methods

Participants for this ethically approved trial were recruited through the internet, mainly through Facebook advertising. Participants were then screened for eligibility, consented to participate, and completed an adaptive digital questionnaire that was designed and created for the trial on a purpose-built digital platform. A subset of these participants was selected to provide dried blood spot (DBS) samples and undertake a World Health Organization World Mental Health Composite International Diagnostic Interview (CIDI). Inclusion and exclusion criteria were chosen to maximize the safety of a trial population that was both relevant to the trial objectives and generalizable. To provide statistical power and validation sets for the primary and secondary objectives, 840 participants were required to complete the digital questionnaire, submit DBS samples, and undertake a CIDI.

Results

The Delta Trial is now complete. More than 3200 participants completed the digital questionnaire, 924 of whom also submitted DBS samples and a CIDI, whereas a total of 1780 participants completed a 6-month follow-up questionnaire and 1542 completed a 12-month follow-up questionnaire. The analysis of the trial data is now underway.

Conclusions

If a diagnostic aid is able to improve the diagnosis of BD and MDD, it may enable earlier treatment for patients with mood disorders.

International Registered Report Identifier (IRRID)

DERR1-10.2196/18453

Potential gains in life expectancy from reducing amenable mortality among people diagnosed with serious mental illness in the United Kingdom

BACKGROUND

To estimate the potential gain in life expectancy from addressing modifiable risk factors for all-cause mortality (excluding suicide and deaths from accidents or violence) across specific serious mental illness (SMI) subgroups, namely schizophrenia, schizoaffective disorders, and bipolar disorders in a Western population.

METHODS

We have used relative risks from recent meta-analyses to estimate the population attribution fraction (PAF) due to specific modifiable risk factors known to be associated with all-cause mortality within SMI. The potential gain in life expectancy at birth, age 50 and age 65 years were assessed by estimating the combined effect of modifiable risk factors from different contextual levels (behavioural, healthcare, social) and accounting for the effectiveness of existing interventions tackling these factors. Projections for annual gain in life expectancy at birth during a two-decade was estimated using the Annual Percentage Change (APC) formula. The predicted estimates were based on mortality rates for year 2014-2015.

RESULTS

Based on the effectiveness of existing interventions targeting these modifiable risk factors, we estimated potential gain in life expectancy at birth of four (bipolar disorders), six (schizoaffective disorders), or seven years (schizophrenia). The gain in life expectancy at age 50 years was three (bipolar disorders) or five (schizophrenia and schizoaffective disorders) years. The projected gain in life expectancy at age 65 years was three (bipolar disorders) or four (schizophrenia and schizoaffective disorders) years.

CONCLUSIONS

The implementation of existing interventions targeting modifiable risk factors could narrow the current mortality gap between the general and the SMI populations by 24% (men) to 28% (women). These projections represent ideal circumstances and without the limitation of overestimation which often comes with PAFs.

PRIMARY EPISODE OF BIPOLAR AFFECTIVE DISORDER

Background. Bipolar affective disorder (BAD) is a topical issue of contemporary psychiatry. The features of the primary episode (PE) of the disease are extremely important for prognosis, treatment and rehabilitation measures of BAD. Individual psychological features of the patients with PE of BAD are still unexplored that complicates development of new methods of prediction, treatment and prevention of BAD. Objective. The aim of the study was to investigate individual psychological features of the patients with a primary episode of bipolar affective disorder, taking into account the gender factor and clinical variant of the BAD debut. Methods. 153 patients (65 men and 88 women) with a primary episode of bipolar affective disorder were examined. The patients were divided into three groups according to the clinical variant of the course of PE of BAD: depressive variant, manic variant and mixed variant. The examination was carried out using the Standardized multifactor method of personality research (SMMPR). Statistical processing of the data was performed using the non-parametric Mann-Whitney test. Results. The most significant differences in the quantitative indicators of SMMPR were found when comparing depressive and manic, as well as depressive and mixed variants of PE of BAD, and lesser – when comparing manic and mixed variants. Most of all, these differences were expressed in terms of pessimism, impulsiveness, individualism and optimism.  Conclusions. Some peculiar features of male and female patients with depressive, manic and mixed variants of PE of BAD promoting to search for new methods of prediction, treatment and prevention of BAD have been defined.

Exploring factors of diagnostic delay for patients with bipolar disorder: a population-based cohort study

BACKGROUND

Bipolar disorder if untreated, has severe consequences: severe role impairment, higher health care costs, mortality and morbidity. Although effective treatment is available, the delay in diagnosis might be as long as 10-15 years. In this study, we aim at documenting the length of the diagnostic delay in Hungary and identifying factors associated with it.

METHODS

Kaplan-Meier survival analysis and Cox proportional hazards model was employed to examine factors associated with the time to diagnosis of bipolar disorder measured from the date of the first presentation to any specialist mental healthcare institution. We investigated three types of factors associated with delays to diagnosis: demographic characteristics, clinical predictors and patient pathways (temporal sequence of key clinical milestones). Administrative data were retrieved from specialist care; the population-based cohort includes 8935 patients from Hungary.

RESULTS

In the sample, diagnostic delay was 6.46 years on average. The mean age of patients at the time of the first bipolar diagnosis was 43.59 years. 11.85% of patients were diagnosed with bipolar disorder without any delay, and slightly more than one-third of the patients (35.10%) were never hospitalized with mental health problems. 88.80% of the patients contacted psychiatric care for the first time in outpatient settings, while 11% in inpatient care. Diagnostic delay was shorter, if patients were diagnosed with bipolar disorder by non-specialist mental health professionals before. In contrast, diagnoses of many psychiatric disorders received after the first contact were coupled with a delayed bipolar diagnosis. We found empirical evidence that in both outpatient and inpatient care prior diagnoses of schizophrenia, unipolar depression without psychotic symptoms, and several disorders of adult personality were associated with increased diagnostic delay. Patient pathways played an important role as well: the hazard of delayed diagnosis increased if patients consulted mental healthcare specialists in outpatient care first or they were hospitalized.

CONCLUSIONS

We systematically described and analysed the diagnosis of bipolar patients in Hungary controlling for possible confounders. Our focus was more on clinical variables as opposed to factors controllable by policy-makers. To formulate policy-relevant recommendations, a more detailed analysis of care pathways and continuity is needed.

Unipolar mania: Identification and characterisation of cases in France and the United Kingdom

BACKGROUND

Unipolar mania is a putative subtype of bipolar disorder (BD) in which individuals experience recurrent manic but not major depressive episodes. Few studies of unipolar mania have been conducted in developed countries and none in the UK. This study aimed to identify and characterise people with unipolar mania in the UK and France.

METHODS

People with unipolar mania were ascertained using a South London UK electronic case register and a French BD case series. Each unipolar mania group was compared to a matched group of people with BD who have experienced depressive episodes.

RESULTS

17 people with unipolar mania were identified in South London and 13 in France. The frequency of unipolar mania as a percentage of the BD clinical population was 1.2% for the South London cohort and 3.3% for the French cohort. In both cohorts, people with unipolar mania experienced more manic episodes than people with BD, and in the French cohort were more likely to experience a psychotic illness onset and more psychiatric admissions. Treatment and self-harm characteristics of people with unipolar mania were similar to people with BD.

LIMITATIONS

The relatively small number of people with unipolar mania identified by this study limits its power to detect differences in clinical variables.

CONCLUSIONS

People with unipolar mania can be identified in France and the UK, and they may experience a higher frequency of manic episodes but have similar treatment and self-harm characteristics as people with BD.

Differences in psychiatric care utilisation among unaccompanied refugee minors, accompanied migrant minors, and Swedish-born minors

PURPOSE

To better understand underutilisation of psychiatric care among migrant children, we compared utilisation of psychiatric care among unaccompanied refugee minors and accompanied migrant minors, with Swedish-born minors.

METHODS

Using a large longitudinal database of linked national registers, we established a retrospective cohort of 1,328,397 people born 1984-1988 comparing minors born in Sweden to 2 Swedish-born parents (95.4%) to minors who had been arriving in Sweden between 2002 and 2011 with a permanent resident permit and were either unaccompanied refugee minors (0.4%), or accompanied migrant minors (4.0%). The outcome measures were different measures of psychiatric care including in- and outpatient care, and prescribed psychotropic medication.

RESULT

Compared with the Swedish-born minors the unaccompanied refugee minors had a higher likelihood of utilisation of all psychiatric care except ADHD medication. However, compared with accompanied migrant minors, the Swedish-born minors had a higher likelihood of having utilised psychiatric care.

CONCLUSION

Our study shows that during the first years of living in Sweden, there seems to be fewer barriers to psychiatric care for unaccompanied refugee minors compared to the accompanied migrant minors. There are a number of possible reasons for this including stronger ties with the Swedish society.

Delays to diagnosis among people with severe mental illness in rural Vietnam, a population-based cross-sectional survey

BACKGROUND

People with severe mental illness (SMI) living in low and middle-income countries can experience extended delays to diagnosis, which hinder access to medical treatment. The aims of this study were to describe the interval to diagnosis among these people in rural Vietnam and its associated factors.

METHODS

A population-based cross-sectional study was conducted among people with SMI in two provinces in Vietnam. The delay to diagnosis was defined as the time between the first abnormal behaviour being observed by family members and the formal diagnosis of psychosis. A multilevel linear regression was used to examine the factors associated with the delay to diagnosis.

RESULTS

Among 404 people with SMI from 370 households, the median delay to diagnosis was 11.5 months (IQR 0-168.0). Overall, 53.7% had a delay to diagnosis of less than one year (95% CI: 48.81-58.54). The financial burden of these people on their families was nearly USD 470/year. After adjusting for other factors at individual and household levels, living in a Northern province; older age, and having psychotic diagnosis before the implementation of the National Community Mental Health program (2003) were associated with a delay of more than twelve months to diagnosis.

CONCLUSIONS

These data indicate that the implementation of a national policy for community-based care has been effective in reducing the delay to diagnosis in rural Vietnam. Therefore, there is a need for strengthening the program and mental health policies, focusing on public communication to improve mental health literacy and reduce stigma against SMI.

Prevalence of suicide attempts in bipolar disorder: a systematic review and meta-analysis of observational studies

AIMS

Bipolar disorder (BD) is a severe psychiatric disorder associated with a high risk of suicide. This meta-analysis examined the prevalence of suicide attempts (SA) in patients with BD and its associated factors.

METHODS

A systematic literature search was conducted in the PubMed, PsycINFO, EMBASE and Web of Science databases from their inception to 11 June 2018. The prevalence of SA in BD was synthesised using the random-effects model.

RESULTS

The search identified 3451 articles of which 79 studies with 33 719 subjects met the study entry criteria. The lifetime prevalence of SA was 33.9% (95% CI 31.3-36.6%; I2 = 96.4%). Subgroup and meta-regression analyses revealed that the lifetime prevalence of SA was positively associated with female gender, BD-I, BD Not Otherwise Specified and rapid cycling BD subtypes, income level and geographic region.

CONCLUSION

This meta-analysis confirmed that SA is common in BD and identified a number of factors related to SA. Further efforts are necessary to facilitate the identification and prevention of SA in BD. Long-term use of mood stabilisers coupled with psycho-social interventions should be available to BD patients to reduce the risk of suicidal behaviour.

Is paliperidone palmitate more effective than other long-acting injectable antipsychotics?

BACKGROUND

Paliperidone palmitate is one of the most widely prescribed long-acting injectable (LAI) antipsychotics in the UK. However, it is relatively expensive and there are few data comparing its effectiveness to that of other LAI antipsychotics. We sought to address this issue by analyzing a large anonymized electronic health record (EHR) dataset from patients treated with LAI antipsychotics.

METHODS

EHR data were obtained from 1281 patients in the South London and Maudsley NHS Foundation Trust (SLaM) who started treatment with a LAI antipsychotic between 1 April 2011 and 31 January 2015. The number of days spent as a psychiatric inpatient and the number of admissions to a psychiatric hospital were analyzed in each of the 3 years before and after LAI prescription.

RESULTS

Patients treated with paliperidone palmitate (n = 430; 33.6%) had a greater number of inpatient days and a greater number of admissions in the year prior to treatment than those treated with other LAI antipsychotics. Nevertheless, in the 3 years after initiation there were no significant differences between paliperidone and the other LAI antipsychotics in the number of days as an inpatient (B coefficient 5.4 days, 95% confidence interval (CI) -57.3 to 68.2, p = 0.86) or number of hospital admissions (Incidence rate ratio 1.07, 95% CI 0.62 to 1.83, p = 0.82).

CONCLUSION

Paliperidone palmitate was more likely to be prescribed in patients with more frequent and lengthy hospital admissions prior to initiation. However, the absence of differences in outcomes after initiation indicates that paliperidone palmitate was not more effective than other cheaper LAI antipsychotics.

Bipolar disorder, comorbid anxiety disorders, gynecomastia and dental pain: case analysis with literature review

Bipolar disorder with comorbid anxiety disorders frequently requires rational polypharmacy, including use of serotonergic psychotropics. These may result in adverse effects, influencing adherence, complicating treatment and confounding diagnoses. Serotonergic non-adherence is associated with discontinuation syndromes. In this complex case with an on/off/on/off design, both dose-dependent buspirone-induced gynecomastia and buspirone discontinuation syndrome with dental pain are reported. Clinicians and patients should consider these findings to maximise treatment adherence, minimise any unnecessary interventions and address unusual adverse effects. Since patients may not voluntarily disclose specific adverse effects and often do not acknowledge non-adherence, clinician-directed questions are required. This case further emphasises the importance of medication and symptom timelines to guide determination of causation for adverse effects. Although findings from this case cannot be generalised, they suggest the need for continued clinician and patient education, as well as the benefit from detailed case reports.

DECLARATION OF INTEREST

None.

Assessment of Oropharyngeal and Laryngeal Cancer Treatment Delay in a Private and Safety Net Hospital System

Objective

To examine the impact of treatment setting and demographic factors on oropharyngeal and laryngeal cancer time to treatment initiation (TTI).

Study Design

Retrospective case series.

Setting

Safety net hospital and adjacent private academic hospital.

Subjects and Methods

Demographic, staging, and treatment details were retrospectively collected for 239 patients treated from January 1, 2014, to June 30, 2016. TTI was defined as days between diagnostic biopsy and initiation of curative treatment (defined as first day of radiotherapy [RT], surgery, or chemotherapy).

Results

On multivariable analysis, safety net hospital treatment (vs private academic hospital treatment), initial diagnosis at outside hospital, and oropharyngeal cancer (vs laryngeal cancer) were all associated with increased TTI. Surgical treatment, severe comorbidity, and both N1 and N2 status were associated with decreased TTI.

Conclusion

Safety net hospital treatment was associated with increased TTI. No differences in TTI were found when language spoken and socioeconomic status were examined in the overall cohort.

Socio-demographic and clinical characterization of patients with Bipolar Disorder I vs II: a Nationwide Italian Study

Bipolar disorders (BDs) are prevalent, comorbid and disabling conditions, associated with the highest suicide risk among psychiatric illnesses. In the last few years, new efforts to better characterize the socio-demographic and clinical profiles of BD type I vs II have been documented by several reports, with novel and insightful findings in the field. The present multicenter study aimed to provide a comprehensive and reliable representation of the Italian reality, through the analysis of the largest national sample of bipolar patients collected so far. A total of 1500 patients (BD I n = 963 and BD II n = 537) from different psychiatric departments, participating in the Italian Chapter of the "International Society of Bipolar Disorders" (ISBD), were assessed and divided into two groups on the basis of their diagnostic subtype, and different socio-demographic and clinical variables were compared between the two subgroups. Chi-squared tests for categorical variables and t tests for continuous variables were performed for group comparison. Furthermore, a multivariable logistic regression was performed, considering diagnostic bipolar subtype (type I or II) as dependent variable, and socio-demographic/clinical characteristics as independent variables. BD I vs II patients showed an overall less favorable socio-demographic and clinical profile. In addition, the multivariable logistic regression showed that BD II vs BD I was predicted by the absence of lifetime suicide attempts (OR = 1.58, p = 0.01), a later age of diagnosis (OR = 1.03, p < 0.01), less hypomanic episodes in the last year (OR = 2.29, p < 0.0001) and absence of psycho-educational interventions in the last year (OR = 0.51, p < 0.01). BD I and II patients were found to significantly differ in relation to specific clinical variables, which should be considered within updated diagnostic-therapeutic algorithms.

Polydipsia as a Precursor of Manic Episode in Bipolar Affective Disorder Patients with Alcohol Use Disorder

Bipolar affective disorder (BD) diagnosis and initiation of appropriate treatment are often delayed, and this is associated with poorer outcomes, such as rapid cycling or cognitive decline. Therefore, identifying certain warning signs of a probable successive episode during the inter-episode phase is important for early intervention. We present the retrospective data of three cases of BD. Our first case had a history of alcohol use disorder (AUD), where he drank in a dipsomaniac manner, and the other two cases had dipsomaniac alcohol use before their manic attacks, and none of them had any AUD after the mood episode was over. Two brothers also had hypertensive episodes during the manic attacks. None of the cases reported increased fluid intake when they were euthymic. We suggest that polydipsia in BD may be a warning sign of an upcoming manic episode, especially in those patients with AUD. Polydipsia in BD may be caused or facilitated by a combination of hyperdopaminergic activity, hypothalamic dysfunction, and dysregulated renin-angiotensin system. To be able to prevent new episodes, a patient’s drinking habits and change in fluid intake should be asked at every visit. Those patients with a history of alcohol abuse should especially be informed about polydipsia and manic episode association.

The Camden & Islington Research Database: Using electronic mental health records for research

BACKGROUND

Electronic health records (EHRs) are widely used in mental health services. Case registers using EHRs from secondary mental healthcare have the potential to deliver large-scale projects evaluating mental health outcomes in real-world clinical populations.

METHODS

We describe the Camden and Islington NHS Foundation Trust (C&I) Research Database which uses the Clinical Record Interactive Search (CRIS) tool to extract and de-identify routinely collected clinical information from a large UK provider of secondary mental healthcare, and demonstrate its capabilities to answer a clinical research question regarding time to diagnosis and treatment of bipolar disorder.

RESULTS

The C&I Research Database contains records from 108,168 mental health patients, of which 23,538 were receiving active care. The characteristics of the patient population are compared to those of the catchment area, of London, and of England as a whole. The median time to diagnosis of bipolar disorder was 76 days (interquartile range: 17-391) and median time to treatment was 37 days (interquartile range: 5-194). Compulsory admission under the UK Mental Health Act was associated with shorter intervals to diagnosis and treatment. Prior diagnoses of other psychiatric disorders were associated with longer intervals to diagnosis, though prior diagnoses of schizophrenia and related disorders were associated with decreased time to treatment.

CONCLUSIONS

The CRIS tool, developed by the South London and Maudsley NHS Foundation Trust (SLaM) Biomedical Research Centre (BRC), functioned very well at C&I. It is reassuring that data from different organizations deliver similar results, and that applications developed in one Trust can then be successfully deployed in another. The information can be retrieved in a quicker and more efficient fashion than more traditional methods of health research. The findings support the secondary use of EHRs for large-scale mental health research in naturalistic samples and settings investigated across large, diverse geographical areas.

Big data in mental health research - do the ns justify the means? Using large data-sets of electronic health records for mental health research

Advances in information technology and data storage, so-called 'big data', have the potential to dramatically change the way we do research. We are presented with the possibility of whole-population data, collected over multiple time points and including detailed demographic information usually only available in expensive and labour-intensive surveys, but at a fraction of the cost and effort. Typically, accounts highlight the sheer volume of data available in terms of terabytes (10¹²) and petabytes (10¹⁵) of data while charting the exponential growth in computing power we can use to make sense of this. Presented with resources of such dizzying magnitude it is easy to lose sight of the potential limitations when the amount of data itself appears unlimited. In this short account I look at some recent advances in electronic health data that are relevant for mental health research while highlighting some of the potential pitfalls.

Patient Characteristics Associated with Inpatient Psychiatric Re-admissions and the Utility of the READMIT Clinical Risk Index

In response to the problem of frequent 30-day readmissions to inpatient psychiatric facilities, Vigod and colleagues (2015) developed the READMIT clinical risk index to identify risk factors for psychiatric inpatient readmissions. The purpose of this descriptive retrospective study was to examine the effectiveness of the READMIT clinical risk index to identify patients that are at high risk for a 30-day inpatient psychiatric readmission at a state psychiatric hospital in the southeastern US. Data were extracted from the discharge summaries of patients discharged between September 2013 and December 2014. Data collected included patient demographic variables (age, gender, race/ethnicity, primary diagnosis, housing status at discharge, employment, long-acting injectable at discharge, substance abuse, education, and insurance status) and study variables from the READMIT clinical risk index (repeat admission, emergent admission, age, diagnosis and discharge, medical comorbidity, intensity, and time in hospital). The inclusion criterion was age 18 and above. There were no exclusion criteria. Findings indicated that age, insurance status, previous lifetime admissions, 'diagnoses and discharge' scores, and higher READMIT clinical risk index scores were associated with 30-day readmissions. Future research should include a prospective study of the READMIT clinical risk index to assess its predictability of 30-day readmissions and explore possible use of the minimum clinical risk index score to trigger evaluation of patient need for enhanced transitional care services posthospital discharge.

What proportion of patients with psychosis is willing to take part in research? A mental health electronic case register analysis

OBJECTIVE

The proportion of people with mental health disorders who participate in clinical research studies is much smaller than for those with physical health disorders. It is sometimes assumed that this reflects an unwillingness to volunteer for mental health research studies. We examined this issue in a large sample of patients with psychosis.

DESIGN

Cross-sectional study.

SETTING

Anonymised electronic mental health record data from the South London and Maudsley NHS Foundation Trust (SLaM).

PARTICIPANTS

5787 adults diagnosed with a psychotic disorder.

EXPOSURE

Whether approached prior to 1 September 2014 for consent to be approached about research participation.

MAIN OUTCOME MEASURES

Number of days spent in a psychiatric hospital, whether admitted to hospital compulsorily, and total score on the Health of the Nation Outcome Scale (HoNOS) between 1 September 2014 and 28 February 2015 with patient factors (age, gender, ethnicity, marital status and diagnosis) and treating clinical service as covariates.

RESULTS

1187 patients (20.5% of the total sample) had been approached about research participation. Of those who were approached, 773 (65.1%) agreed to be contacted in future by researchers. Patients who had been approached had 2.3 fewer inpatient days (95% CI -4.4 to -0.3, p=0.03), were less likely to have had a compulsory admission (OR 0.65, 95% CI 0.50 to 0.84, p=0.001) and had a better HoNOS score (β coefficient -0.9, 95% CI -1.5 to -0.4, p=0.001) than those who had not. Among patients who were approached, there was no significant difference in clinical outcomes between those agreed to research contact and those who did not.

CONCLUSIONS

About two-thirds of patients with psychotic disorders were willing to be contacted about participation in research. The patients who were approached had better clinical outcomes than those who were not, suggesting that clinicians were more likely to approach patients who were less unwell.

Analysis of diagnoses extracted from electronic health records in a large mental health case register

The UK government has recently recognised the need to improve mental health services in the country. Electronic health records provide a rich source of patient data which could help policymakers to better understand needs of the service users. The main objective of this study is to unveil statistics of diagnoses recorded in the Case Register of the South London and Maudsley NHS Foundation Trust, one of the largest mental health providers in the UK and Europe serving a source population of over 1.2 million people residing in south London. Based on over 500,000 diagnoses recorded in ICD10 codes for a cohort of approximately 200,000 mental health patients, we established frequency rate of each diagnosis (the ratio of the number of patients for whom a diagnosis has ever been recorded to the number of patients in the entire population who have made contact with mental disorders). We also investigated differences in diagnoses prevalence between subgroups of patients stratified by gender and ethnicity. The most common diagnoses in the considered population were (recurrent) depression (ICD10 codes F32-33; 16.4% of patients), reaction to severe stress and adjustment disorders (F43; 7.1%), mental/behavioural disorders due to use of alcohol (F10; 6.9%), and schizophrenia (F20; 5.6%). We also found many diagnoses which were more likely to be recorded in patients of a certain gender or ethnicity. For example, mood (affective) disorders (F31-F39); neurotic, stress-related and somatoform disorders (F40-F48, except F42); and eating disorders (F50) were more likely to be found in records of female patients, while males were more likely to be diagnosed with mental/behavioural disorders due to psychoactive substance use (F10-F19). Furthermore, mental/behavioural disorders due to use of alcohol and opioids were more likely to be recorded in patients of white ethnicity, and disorders due to use of cannabinoids in those of black ethnicity.

Big data for bipolar disorder

The delivery of psychiatric care is changing with a new emphasis on integrated care, preventative measures, population health, and the biological basis of disease. Fundamental to this transformation are big data and advances in the ability to analyze these data. The impact of big data on the routine treatment of bipolar disorder today and in the near future is discussed, with examples that relate to health policy, the discovery of new associations, and the study of rare events. The primary sources of big data today are electronic medical records (EMR), claims, and registry data from providers and payers. In the near future, data created by patients from active monitoring, passive monitoring of Internet and smartphone activities, and from sensors may be integrated with the EMR. Diverse data sources from outside of medicine, such as government financial data, will be linked for research. Over the long term, genetic and imaging data will be integrated with the EMR, and there will be more emphasis on predictive models. Many technical challenges remain when analyzing big data that relates to size, heterogeneity, complexity, and unstructured text data in the EMR. Human judgement and subject matter expertise are critical parts of big data analysis, and the active participation of psychiatrists is needed throughout the analytical process.

Is treatment for bipolar disorder more effective earlier in illness course? A comprehensive literature review

Background

We aimed to investigate a key element of the early intervention approach; whether treatment at an earlier stage of bipolar disorder is more effective than later in its course.

Methods

A comprehensive literature review using Medline, Embase, Psychinfo, PsycArticle and Web of Science as data sources, with a subsequent narrative synthesis. Study quality was assessed using the Cochrane risk of bias method.

Results

Our search strategy yielded eight primary papers and two meta-analyses (of psychological therapies and Olanzapine) in total representing 8942 patients. Five studies focused on comparisons between first and multiple episode; the others on fewer vs more episode categories. There was a consistent finding suggesting treatment in earlier illness stage resulted in better outcomes in terms of response, relapse rate, time to recurrence, symptomatic recovery, remission, psychosocial functioning and employment. This effect was found for pharmacological (Lithium, Olanzapine, Divalproex) and psychological treatment.

Limitations

There was high risk of selection, performance and attrition bias in most studies. First admission or presentation is unlikely to equate to first episode because of duration of untreated illness. Some patients having experienced multiple episodes could be “treatment resistant”. Study heterogeneity precluded meta-analysis.

Conclusions

Psychological and pharmacological treatment in the early stages of illness is more effective than in later stages of bipolar disorder across multiple domains. There is a first episode and early phase effect. Consistent with the staging model of illness findings provide evidence for the clinical utility of an early intervention approach in bipolar disorder to improve patient outcomes.

Clinical outcomes and mortality associated with weekend admission to psychiatric hospital

BACKGROUND

Studies indicate that risk of mortality is higher for patients admitted to acute hospitals at the weekend. However, less is known about clinical outcomes among patients admitted to psychiatric hospitals.

AIMS

To investigate whether weekend admission to a psychiatric hospital is associated with worse clinical outcomes.

METHOD

Data were obtained from 45 264 consecutive psychiatric hospital admissions. The association of weekend admission with in-patient mortality, duration of hospital admission and risk of readmission was investigated using multivariable regression analyses. Secondary analyses were performed to investigate the distribution of admissions, discharges, in-patient mortality, episodes of seclusion and violent incidents on different days of the week.

RESULTS

There were 7303 weekend admissions (16.1%). Patients who were aged between 26 and 35 years, female or from a minority ethnic group were more likely to be admitted at the weekend. Patients admitted at the weekend were more likely to present via acute hospital services, other psychiatric hospitals and the criminal justice system than to be admitted directly from their own home. Weekend admission was associated with a shorter duration of admission (B coefficient -21.1 days, 95% CI -24.6 to -17.6, P<0.001) and an increased risk of readmission in the 12 months following index admission (incidence rate ratio 1.13, 95% CI 1.08 to 1.18, P<0.001), but in-patient mortality (odds ratio (OR) = 0.79, 95% CI 0.51 to 1.23, P = 0.30) was not greater than for weekday admission. Fewer episodes of seclusion occurred at the weekend but there was no significant variation in deaths during hospital admission or violent incidents on different days of the week.

CONCLUSIONS

Being admitted at the weekend was not associated with an increased risk of in-patient mortality. However, patients admitted at the weekend had shorter admissions and were more likely to be readmitted, suggesting that they may represent a different clinical population to those admitted during the week. This is an important consideration if mental healthcare services are to be implemented across a 7-day week.

Cohort profile of the South London and Maudsley NHS Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register: current status and recent enhancement of an Electronic Mental Health Record-derived data resource

PURPOSE

The South London and Maudsley National Health Service (NHS) Foundation Trust Biomedical Research Centre (SLaM BRC) Case Register and its Clinical Record Interactive Search (CRIS) application were developed in 2008, generating a research repository of real-time, anonymised, structured and open-text data derived from the electronic health record system used by SLaM, a large mental healthcare provider in southeast London. In this paper, we update this register's descriptive data, and describe the substantial expansion and extension of the data resource since its original development.

PARTICIPANTS

Descriptive data were generated from the SLaM BRC Case Register on 31 December 2014. Currently, there are over 250,000 patient records accessed through CRIS.

FINDINGS TO DATE

Since 2008, the most significant developments in the SLaM BRC Case Register have been the introduction of natural language processing to extract structured data from open-text fields, linkages to external sources of data, and the addition of a parallel relational database (Structured Query Language) output. Natural language processing applications to date have brought in new and hitherto inaccessible data on cognitive function, education, social care receipt, smoking, diagnostic statements and pharmacotherapy. In addition, through external data linkages, large volumes of supplementary information have been accessed on mortality, hospital attendances and cancer registrations.

FUTURE PLANS

Coupled with robust data security and governance structures, electronic health records provide potentially transformative information on mental disorders and outcomes in routine clinical care. The SLaM BRC Case Register continues to grow as a database, with approximately 20,000 new cases added each year, in addition to extension of follow-up for existing cases. Data linkages and natural language processing present important opportunities to enhance this type of research resource further, achieving both volume and depth of data. However, research projects still need to be carefully tailored, so that they take into account the nature and quality of the source information.

Do antidepressants increase the risk of mania and bipolar disorder in people with depression? A retrospective electronic case register cohort study

OBJECTIVES

To investigate the association between antidepressant therapy and the later onset of mania/bipolar disorder.

DESIGN

Retrospective cohort study using an anonymised electronic health record case register.

SETTING

South London and Maudsley National Health Service (NHS) Trust (SLaM), a large provider of inpatient and community mental healthcare in the UK.

PARTICIPANTS

21,012 adults presenting to SLaM between 1 April 2006 and 31 March 2013 with unipolar depression.

EXPOSURE

Prior antidepressant therapy recorded in electronic health records.

MAIN OUTCOME MEASURE

Time to subsequent diagnosis of mania or bipolar disorder from date of diagnosis of unipolar depression, censored at 31 March 2014.

METHODS

Multivariable Cox regression analysis with age and gender as covariates.

RESULTS

The overall incidence rate of mania/bipolar disorder was 10.9 per 1000 person-years. The peak incidence of mania/bipolar disorder incidence was seen in patients aged between 26 and 35 years (12.3 per 1000 person-years). 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 selective serotonin reuptake inhibitors (HR 1.34, 95% CI 1.18 to 1.52) and venlafaxine (1.35, 1.07 to 1.70).

CONCLUSIONS

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.