Suicidal ideation is insensitive to suicide risk after emergency department discharge: Performance characteristics of the Columbia-Suicide Severity Rating Scale Screener

Baseline circulating biomarkers, their changes, and subsequent suicidal ideation and depression severity at 6 months: A prospective analysis in patients with mood disorders

BACKGROUND

Identifying circulating biomarkers associated with prospective suicidal ideation (SI) and depression could help better understand the dynamics of these phenomena and identify people in need of intense care. In this study, we investigated the associations between baseline peripheral biomarkers implicated in neuroplasticity, vascular homeostasis and inflammation, and prospective SI and depression severity during 6 months of follow-up in patients with mood disorders.

METHODS

149 patients underwent a psychiatric evaluation and gave blood to measure 32 plasma soluble proteins. At follow-up, SI incidence over six months was measured with the Columbia Suicide Severity Rating Scale, and depressive symptoms were assessed with the Inventory for Depressive Symptomatology. Ninety-six patients provided repeated blood samples. Statistical analyses included Spearman partial correlation and Elastic Net regression, followed by the covariate-adjusted regression models.

RESULTS

51.4 % (N = 71) of patients reported SI during follow-up. After adjustment for covariates, higher baseline levels of interferon-γ were associated with SI occurrence during follow-up. Higher baseline interferon-γ and lower orexin-A were associated with increased depression severity, and atypical and anxious, but not melancholic, symptoms. There was also a tendency for associations of elevated baseline levels of interferon-γ, interleukin-1β, and lower plasma serotonin levels with SI at the six-month follow-up time point. Meanwhile, reduction in transforming growth factor- β1 (TGF-β1) plasma concentration correlated with atypical symptoms reduction.

CONCLUSION

We identified interferon-γ and orexin-A as potential predictive biomarkers of SI and depression, whereas TGF-β1 was identified as a possible target of atypical symptoms.

Defining Suicidal Thought and Behavior Phenotypes for Genetic Studies

Background

Standardized definitions of suicidality phenotypes, including suicidal ideation (SI), attempt (SA), and death (SD) are a critical step towards improving understanding and comparison of results in suicide research. The complexity of suicidality contributes to heterogeneity in phenotype definitions, impeding evaluation of clinical and genetic risk factors across studies and efforts to combine samples within consortia. Here, we present expert and data-supported recommendations for defining suicidality and control phenotypes to facilitate merging current/legacy samples with definition variability and aid future sample creation.

Methods

A subgroup of clinician researchers and experts from the Suicide Workgroup of the Psychiatric Genomics Consortium (PGC) reviewed existing PGC definitions for SI, SA, SD, and control groups and generated preliminary consensus guidelines for instrument-derived and international classification of disease (ICD) data. ICD lists were validated in two independent datasets (N = 9,151 and 12,394).

Results

Recommendations are provided for evaluated instruments for SA and SI, emphasizing selection of lifetime measures phenotype-specific wording. Recommendations are also provided for defining SI and SD from ICD data. As the SA ICD definition is complex, SA code list recommendations were validated against instrument results with sensitivity (range = 15.4% to 80.6%), specificity (range = 67.6% to 97.4%), and positive predictive values (range = 0.59-0.93) reported.

Conclusions

Best-practice guidelines are presented for the use of existing information to define SI/SA/SD in consortia research. These proposed definitions are expected to facilitate more homogeneous data aggregation for genetic and multisite studies. Future research should involve refinement, improved generalizability, and validation in diverse populations.

Consultation-Liaison Case Conference: Assessment and Management of a Physician With Thoughts of Suicide

We present the case of a physician who engages with a peer response team and discloses suicidal ideation while himself seeing patients in the hospital. Top experts in consultation-liaison psychiatry provide guidance for this clinical case based on their experience and a review of the available literature. Key teaching topics include a general approach to suicide risk assessment, peer response programs for healthcare workers, and ethical and clinical considerations in treating colleagues. Consultation-liaison psychiatrists should be familiar with suicide risk management, take a pro-active approach to addressing modifiable risk factors, and keep in mind unique challenges of treating colleagues referred for care.

Development of a prediction model for suicidal ideation in patients with advanced cancer: A multicenter, real-world, pan-cancer study in China

BACKGROUND

Patients diagnosed with advanced stage cancer face an elevated risk of suicide. We aimed to develop a suicidal ideation (SI) risk prediction model in patients with advanced cancer for early warning of their SI and facilitate suicide prevention in this population.

PATIENTS AND METHODS

We consecutively enrolled patients with multiple types of advanced cancers from 10 cancer institutes in China from August 2019 to December 2020. Demographic characteristics, clinicopathological data, and clinical treatment history were extracted from medical records. Symptom burden, psychological status, and SI were assessed using the MD Anderson Symptom Inventory (MDASI), Hospital Anxiety and Depression Scale (HADS), and Patient Health Questionnaire-9 (PHQ-9), respectively. A multivariable logistic regression model was employed to establish the model structure.

RESULTS

In total, 2814 participants were included in the final analysis. Nine predictors including age, sex, number of household members, history of previous chemotherapy, history of previous surgery, MDASI score, HADS-A score, HADS-D score, and life satisfaction were retained in the final SI prediction model. The model achieved an area under the curve (AUC) of 0.85 (95% confidential interval: 0.82-0.87), with AUCs ranging from 0.75 to 0.95 across 10 hospitals and higher than 0.83 for all cancer types.

CONCLUSION

This study built an easy-to-use, good-performance predictive model for SI. Implementation of this model could facilitate the incorporation of psychosocial support for suicide prevention into the standard care of patients with advanced cancer.

Predicting suicide death after emergency department visits with mental health or self-harm diagnoses

OBJECTIVE

Use health records data to predict suicide death following emergency department visits.

METHODS

Electronic health records and insurance claims from seven health systems were used to: identify emergency department visits with mental health or self-harm diagnoses by members aged 11 or older; extract approximately 2500 potential predictors including demographic, historical, and baseline clinical characteristics; and ascertain subsequent deaths by self-harm. Logistic regression with lasso and random forest models predicted self-harm death over 90 days after each visit.

RESULTS

Records identified 2,069,170 eligible visits, 899 followed by suicide death within 90 days. The best-fitting logistic regression with lasso model yielded an area under the receiver operating curve of 0.823 (95% CI 0.810-0.836). Visits above the 95th percentile of predicted risk included 34.8% (95% CI 31.1-38.7) of subsequent suicide deaths and had a 0.303% (95% CI 0.261-0.346) suicide death rate over the following 90 days. Model performance was similar across subgroups defined by age, sex, race, and ethnicity.

CONCLUSIONS

Machine learning models using coded data from health records have moderate performance in predicting suicide death following emergency department visits for mental health or self-harm diagnosis and could be used to identify patients needing more systematic follow-up.

Associations of potential plasma biomarkers with suicide attempt history, current suicidal ideation and subsequent suicidal events in patients with depression: A discovery study

A growing body of evidences suggests that suicidal ideation (SI) and suicidal behaviors have biological bases. However, no biological marker is currently available to evaluate the suicide risk in individuals with SI or suicide attempt (SA). Moreover, the current risk assessment techniques poorly predict future suicidal events. The aim of this study was to examine the association of 39 new and already described peripheral cells and proteins (implicated in the immune system, oxidative stress and plasticity) with lifetime SA, past month SA, current SI, and future suicidal events (visit to the Emergency Department for SI or SA) in 266 treatment-seeking individuals with mood disorders. Equal parts of patients with and without past history of SA were recruited. All individuals at inclusion gave blood, were evaluated for SA recency, current SI, and were followed for two years afterwards. The 39 peripheral blood cellular and protein markers were entered separately for each outcome in Elastic Net models with 10-fold cross-validation, followed by single-analyte covariate-adjusted regression analyses for pre-selected analytes. Past month SA was associated with increased plasma levels of thrombospondin-2 and C-reactive protein, whereas current SI was associated with lower plasma serotonin levels. These associations were robust to adjustments for key covariates and corrections for multiple testing. The Cox proportional hazards regression showed that higher levels of thrombospondin-1 and of platelet-derived growth factor-AB predicted a future suicidal event. These two associations remained after adjustment for sex, age, and SA history, and outperformed the predictive value of past SA. Thrombospondins and platelet-derived growth factors have never been investigated in the context of suicide. Altogether, our results highlight the involvement in the suicidal process of platelet biological response and plasticity modifiers and also of inflammatory factors. They also suggest that SI and SA may have different biological correlates and that biomarkers associated with past SA or current SI do not automatically also predict future events.

User Feedback on the Use of a Natural Language Processing Application to Screen for Suicide Risk in the Emergency Department

Suicide is the 10th leading cause of death in the USA and globally. Despite decades of research, the ability to predict who will die by suicide is still no better than 50%. Traditional screening instruments have helped identify risk factors for suicide, but they have not provided accurate predictive power for reducing death rates. Over the past decade, natural language processing (NLP), a form of machine learning (ML), has been used to identify suicide risk by analyzing language data. Recent work has demonstrated the successful integration of a suicide risk screening interview to collect language data for NLP analysis from patients in two emergency departments (ED) of a large healthcare system. Results indicated that ML/NLP models performed well identifying patients that came to the ED for suicide risk. However, little is known about the clinician's perspective of how a qualitative brief interview suicide risk screening tool to collect language data for NLP integrates into an ED workflow. This report highlights the feedback and observations of patient experiences obtained from clinicians using brief suicide screening interviews. The investigator used an open-ended, narrative interview approach to inquire about the qualitative interview process. Three overarching themes were identified: behavioral health workflow, clinical implications of interview probes, and integration of an application into provider patient experience. Results suggest a brief, qualitative interview method was feasible, person-centered, and useful as a suicide risk detection approach.

A Mortality Surveillance Collaboration Between a Health System and Public Health Department

We describe a collaboration between a health system and public health department to create a mortality surveillance system. The collaboration enabled the health system to identify more than six times the number of deaths identified through local system medical records alone. This powerful epidemiological process, combining the nuanced data captured through clinical care in health systems with subsequent data on mortality, drives quality improvement, scientific research, and epidemiology that can be of particular benefit to underserved communities. (Am J Public Health. 2023;113(9):943-946. https://doi.org/10.2105/AJPH.2023.307335).

Screening and Assessment of Suicidal Behavior in Transition-Age Youth with Foster Care Involvement

Transition-age youth with foster care involvement (TAY, ages 17-22) are at heightened risk for suicidal behavior. Despite this, mental health screenings are not standardized across child welfare (CW) systems and existing assessment tools are not designed for use with this specific population. As such, TAY are unlikely to be adequately screened for suicide risk and connected with needed services. In this paper, we sought to identify screening and assessment tools that could be effective for use with TAY in CW settings. Using PubMed and PsycINFO, we conducted a search of the current literature to identify some of the most commonly used screening and assessment tools for youth. We then narrowed our focus to those tools that met predefined inclusion criteria indicating appropriateness of use for TAY in CW settings. As a result of this process, we identified one brief screening tool (the ASQ) and four assessments (the SIQ-JR, the C-SSRS, the SHBQ, and the SPS) that demonstrated specific promise for use with TAY. The strengths and limitations of the tools are discussed in detail, as well as the ways that each could be used most effectively in CW settings. We highlight three key points intended to guide social work practice and policy: (1) systematic, routine assessment of mental health and suicide risk across CW settings is critical; (2) the protocol for assessing suicidal behavior in TAY must account for the wide variations in context and service provision; and (3) CW workers administering assessments must be thoughtfully trained on risk identification and the protocol implementation.

Use of an Agitation Measure to Screen for Suicide and Self-Harm Risk Among Emergency Department Patients

BACKGROUND

Suicidality alone is insensitive to suicide risk among emergency department (ED) patients.

OBJECTIVE

We describe the performance of adding an objective assessment of agitation to a suicide screening instrument for predicting suicide and self-harm after an ED encounter.

METHODS

We tested the performance of a novel screener combining the presence of suicidality or agitation for predicting suicide within 90 days or a repeat ED visit for self-harm within 30 days using retrospective data from all patients seen in an urban safety net ED over 27 months. Patients were assessed for suicidality using the Columbia-Suicide Severity Rating Scale-Clinical Practice Screener and for agitation using either the Behavioral Activity Rating Scale or Richmond Agitation Sedation Scale. We hypothesized that a screener based on the presence of either suicidality or agitation would be more sensitive to suicide risk than the Columbia-Suicide Severity Rating Scale-Clinical Practice Screener alone. The screener's performance is described, and multivariable regression evaluates the correlations between screening and outcomes.

RESULTS

The sample comprised 16,467 patients seen in the ED who had available suicide screening and agitation data. Thirteen patients (0.08%) died by suicide within 90 days after ED discharge. The sensitivity and specificity of the screener combining suicidality and agitation for predicting suicide was 0.69 (95% confidence interval, 0.44-0.94) and 0.74 (0.44-0.94), respectively. The sensitivity and specificity for agitation combined with positive suicide screening for self-harm within 30 days were 0.95 (0.89-1.00) and 0.73 (0.73-0.74). For both outcomes, augmenting the Columbia-Suicide Severity Rating Scale-Clinical Practice Screener with a measure of agitation improved both sensitivity and overall performance compared to historical performance of the Columbia-Suicide Severity Rating Scale-Clinical Practice Screener alone.

CONCLUSIONS

Combining a brief objective measure of agitation with a common suicide screening instrument improved sensitivity and predictive performance for suicide and self-harm risk after ED discharge. These findings speak to the importance of assessing agitation not only for imminent safety risk during the patient encounter but also for reducing the likelihood of future adverse events. This work can improve the detection and management of suicide risk in emergency settings.

National estimates of emergency department visits for medication-related self-harm: United States, 2016-2019

BACKGROUND

Medication poisoning is a common form of self-harm injury, and increases in injuries due to self-harm, including suicide attempts, have been reported over the last two decades.

METHODS

Cross-sectional (2016-2019) data from 60 emergency departments (EDs) participating in an active, nationally representative public health surveillance system were analysed and US national estimates of ED visits for medication-related self-harm injuries were calculated.

RESULTS

Based on 18 074 surveillance cases, there were an estimated 269 198 (95% CI 222 059 to 316 337) ED visits for medication-related self-harm injuries annually in 2016-2019 compared with 1 404 090 visits annually from therapeutic use of medications. Population rates of medication-related self-harm ED visits were highest among persons aged 11-19 years (58.5 (95% CI 45.0 to 72.0) per 10 000) and lowest among those aged ≥65 years (6.6 (95% CI 4.4 to 8.8) per 10 000). Among persons aged 11-19 years, the ED visit rate for females was four times that for males (95.4 (95% CI 74.2 to 116.7) vs 23.0 (95% CI 16.4 to 29.6) per 10 000). Medical or psychiatric admission was required for three-quarters (75.1%; 95% CI 70.0% to 80.2%) of visits. Concurrent use of alcohol or illicit substances was documented in 40.2% (95% CI 36.8% to 43.7%) of visits, and multiple medication products were implicated in 38.6% (95% CI 36.8% to 40.4%). The most frequently implicated medication categories varied by patient age.

CONCLUSIONS

Medication-related self-harm injuries are an important contributor to the overall burden of ED visits and hospitalisations for medication-related harm, with the highest rates among adolescent and young adult females. These findings support continued prevention efforts targeting patients at risk of self-harm.

A Quality Measurement Framework for Emergency Department Care of Psychiatric Emergencies

As a primary access point for crisis psychiatric care, the emergency department (ED) is uniquely positioned to improve the quality of care and outcomes for patients with psychiatric emergencies. Quality measurement is the first key step in understanding the gaps and variations in emergency psychiatric care to guide quality improvement initiatives. Our objective was to develop a quality measurement framework informed by a comprehensive review and gap analysis of quality measures for ED psychiatric care. We conducted a systematic literature review and convened an expert panel in emergency medicine, psychiatry, and quality improvement to consider if and how existing quality measures evaluate the delivery of emergency psychiatric care in the ED setting. The expert panel reviewed 48 measures, of which 5 were standardized, and 3 had active National Quality Forum endorsement. Drawing from the measure appraisal, we developed a quality measurement framework with specific structural, process, and outcome measures across the ED care continuum. This framework can help shape an emergency medicine roadmap for future clinical quality improvement initiatives, research, and advocacy work designed to improve outcomes for patients presenting with psychiatric emergencies.

Outpatient Mental Health Follow-up and Recurrent Self-harm and Suicide Among Patients Admitted to the ICU for Self-harm: A Population-based Cohort Study

BACKGROUND

Patients surviving an ICU admission for deliberate self-harm are at high risk of recurrent self-harm or suicide after discharge. It is unknown whether mental health follow-up after discharge (with either a family physician or psychiatrist) reduces this risk.

RESEARCH QUESTION

What is the association between mental health follow-up after discharge and recurrent self-harm among patients admitted to the ICU for intentional self-harm?

STUDY DESIGN AND METHODS

Population-based cohort study of consecutive adults (≥ 18 years of age) from Ontario, Canada, who were admitted to ICU because of intentional self-harm between 2009 and 2017. We categorized patients according to follow-up, with 'early follow-up' indicating 1 to 21 days after discharge, 'late follow-up' indicating 22 to 60 days after discharge, and 'no follow-up' indicating no follow-up within 60 days of discharge. We conducted analyses using a cause-specific extended Cox regression model to account for varying time for mental health follow-up relative to the outcomes of interest. The primary outcome was recurrent ICU admission for self-harm within 1 year of discharge.

RESULTS

We included 9,569 consecutive adults admitted to the ICU for deliberate self-harm. Compared with receiving no mental health follow-up, both early follow-up (hazard ratio [HR], 1.37; 95% CI, 1.07-1.75) and late follow-up (HR, 1.69; 95% CI, 1.22-2.35) were associated with increased risk in recurrent ICU admission for self-harm. As compared with no follow-up, neither early follow-up (HR, 1.10; 95% CI, 0.70-1.73) nor late follow-up (HR, 1.54; 95% CI, 0.84-2.83) were associated with increased risk of death by suicide.

INTERPREATION

Among adults admitted to the ICU for deliberate self-harm, mental health follow-up after discharge was not associated with reduced risk of recurrent ICU admission for self-harm or death resulting from suicide, and patients seeking outpatient follow-up may be those at highest risk of these outcomes. Future research should focus on additional and novel methods of risk mitigation in this vulnerable population.

Utilizing digital predictive biomarkers to identify Veteran suicide risk

Veteran suicide is one of the most complex and pressing health issues in the United States. According to the 2020 National Veteran Suicide Prevention Annual Report, since 2018 an average of 17.2 Veterans died by suicide each day. Veteran suicide risk screening is currently limited to suicide hotlines, patient reporting, patient visits, and family or friend reporting. As a result of these limitations, innovative approaches in suicide screening are increasingly garnering attention. An essential feature of these innovative methods includes better incorporation of risk factors that might indicate higher risk for tracking suicidal ideation based on personal behavior. Digital technologies create a means through which measuring these risk factors more reliably, with higher fidelity, and more frequently throughout daily life is possible, with the capacity to identify potentially telling behavior patterns. In this review, digital predictive biomarkers are discussed as they pertain to suicide risk, such as sleep vital signs, sleep disturbance, sleep quality, and speech pattern recognition. Various digital predictive biomarkers are reviewed and evaluated as well as their potential utility in predicting and diagnosing Veteran suicidal ideation in real time. In the future, these digital biomarkers could be combined to generate further suicide screening for diagnosis and severity assessments, allowing healthcare providers and healthcare teams to intervene more optimally.

Scores on the suicide cognitions scale-revised (SCS-R) predict future suicide attempts among primary care patients denying suicide ideation and prior attempts

BACKGROUND

Approximately half of patients who attempt or die by suicide screened negative for suicidal ideation during their most recent medical visit. Maladaptive beliefs and schemas can increase cognitive vulnerability to suicidal behavior, even among patients without recent or past suicidal thoughts and behaviors. Assessing these beliefs could improve the detection of patients who will engage in suicidal behavior after screening negative for elevated suicide risk.

METHODS

Primary care patients who completed the Patient Health Questionnaire-9 and the Suicide Cognitions Scale-Revised (SCS-R) during routine clinic visits and denied suicidal ideation at baseline (N = 2417) were included in the study sample. Suicidal behaviors during the 12 months after baseline were assessed. Logistic regression analyses examined the association of baseline SCS-R scores with later suicidal behavior.

RESULTS

In both univariate and multivariate analyses, SCS-R total scores were associated with significantly increased risk of suicidal behavior within 90, 180, and 365 days post-baseline. Results were unchanged when patients who reported prior suicidal behavior were excluded (N = 2178). In item-level analyses, all 16 SCS-R items significantly differentiated patients with and without follow-up suicidal behavior.

LIMITATIONS

Study limitations included missing follow-up data, restriction of sample to U.S. military medical beneficiaries, and inability to assess representativeness of the sample relative to the full primary care population.

CONCLUSIONS

SCS-R scores are elevated among patients who attempt suicide after denying both suicidal ideation and prior suicide attempts, suggesting the scale may reflect enduring suicide risk. The SCS-R could enhance suicide risk screening and assessment.

A virtual, pilot randomized trial of a brief intervention to prevent suicide in an integrated healthcare setting

OBJECTIVE

Patients who die by suicide are often seen in primary care settings in the weeks leading to their death. There has been little study of brief interventions to prevent suicide in these settings.

METHOD

We conducted a virtual, pilot, randomized controlled trial of a brief suicide prevention strategy called Veterans Affairs Brief Intervention and Contact Program (VA BIC) in patients who presented to a primary care mental health walk-in clinic for a new mental health intake appointment and were at risk for suicide. Our primary aim was to assess feasibility. We measured our ability to recruit 20 patients. We measured the proportion of enrolled patients who completed all study assessments. We assessed adherence among patients assigned to VA BIC.

RESULTS

Twenty patients were enrolled and 95% (N = 19) completed all study assessments. Among the 10 patients assigned to VA BIC, 90% (N = 9) of patients completed all required intervention visits, and 100% (N = 10) completed ≥70% of the required interventions visits.

CONCLUSION

It is feasible to conduct a virtual trial of VA BIC in an integrated care setting. Future research should clarify the role of VA BIC as a suicide prevention strategy in integrated care settings using an adequately powered design.

CLINICAL TRIAL REGISTRATION

NCT04054947.

Integration and Validation of a Natural Language Processing Machine Learning Suicide Risk Prediction Model Based on Open-Ended Interview Language in the Emergency Department

BACKGROUND

Emergency departments (ED) are an important intercept point for identifying suicide risk and connecting patients to care, however, more innovative, person-centered screening tools are needed. Natural language processing (NLP) -based machine learning (ML) techniques have shown promise to assess suicide risk, although whether NLP models perform well in differing geographic regions, at different time periods, or after large-scale events such as the COVID-19 pandemic is unknown.

OBJECTIVE

To evaluate the performance of an NLP/ML suicide risk prediction model on newly collected language from the Southeastern United States using models previously tested on language collected in the Midwestern US.

METHOD

37 Suicidal and 33 non-suicidal patients from two EDs were interviewed to test a previously developed suicide risk prediction NLP/ML model. Model performance was evaluated with the area under the receiver operating characteristic curve (AUC) and Brier scores.

RESULTS

NLP/ML models performed with an AUC of 0.81 (95% CI: 0.71-0.91) and Brier score of 0.23.

CONCLUSION

The language-based suicide risk model performed with good discrimination when identifying the language of suicidal patients from a different part of the US and at a later time period than when the model was originally developed and trained.

More than Suicide: Mortality after Emergency Psychiatric Care and Implications for Practice

BACKGROUND

Emergency departments (EDs) provide vital mental health services. ED patients with behavioral health presentations, particularly suicidal ideation, are at increased risk of death by suicide, medical illness, trauma, or overdose. Causes of death for patients who receive specialty emergency psychiatric services remain undescribed.

OBJECTIVE

We describe the incidence and cause of death after care in a psychiatric emergency service (PES).

METHODS

Mortality data were obtained for all adult patients treated in a safety net ED from April 2016 to June 2020. Causes of death were categorized as medical, external (accidents, overdoses, and homicide), or suicide and compared between PES patients and ED patients who were not treated in the PES. Correlates of mortality were described for PES patients.

RESULTS

We analyzed 164,422 encounters including 6,063 PES visits. Mortality in the 30 days after discharge was 0.3% among PES patients and 0.6% among medical ED patients. At both 30 and 365 days, PES patients were more likely to die by suicide than were medical ED patients, and ED patients were more likely to die by medical causes. Among PES patients who died within 365 days, 46% died by medical causes, 32% by external causes, and 23% by suicide. In multivariable analyses, age was associated with all-cause, medical, and external mortality after a PES visit; opioid and stimulant use disorders were associated with all-cause and external mortality.

CONCLUSIONS

Most patients who die after receiving emergency psychiatric care die by medical and external causes such as accidents, overdose, and homicide. Patients who are older and have opioid or stimulant use disorders are at higher risk of non-suicide mortality. We propose interventions to re-imagine emergency psychiatric care and address non-suicide mortality among psychiatric patients treated in emergency and crisis settings.

Observing time effect of SSRIs on suicide risk and suicide-related behaviour: a network meta-analysis protocol

INTRODUCTION

Suicide is a serious problem worldwide and 90% cases are associated with pre-existing or underlying mental illness. As a common treatment for depressive symptoms that suicidal people may receive, selective serotonin reuptake inhibitors (SSRIs) have been linked to a possible increase in suicide rates. Studies focusing on SSRIs and suicide have produced inconsistent results, suggesting that use of SSRIs decreases, increases, has no effect on suicide rates, or that the effect of SSRIs on suicide is age-dependent. This protocol of network meta-analysis aims to precisely evaluate the time effects of SSRIs by observing weekly changes of suicidality in the first 2 months of the treatment, and consequently, to explore whether the effect of the SSRIs on suicide varies depending on the stages of the treatment; if so, we will identify the turning point.

METHODS AND ANALYSIS

We will search in the following databases: PubMed, Web of science, China National Knowledge Infrastructure and Wanfang Data, from dates of inception to 9 July 2021, with language restricted to English and Chinese. Studies focusing on the time effect of SSRIs on suicide will be retrieved. Then, the study selection process will follow the Preferred Reporting Items for Systematic Reviews and Meta-Analyses guideline, and the quality assessment will be conducted with Cochrane Collaboration's tool. Two researchers will work independently on data extraction using a standardised data extraction spreadsheet. Any disagreement between two researchers will be discussed and determined by a third researcher.

ETHICS AND DISSEMINATION

This work does not require ethics approval as it will be based on published studies. This review will be published in peer-reviewed journals.

PROSPERO REGISTRATION NUMBER

CRD42021244779.

Suicide and Self-Harm Outcomes Among Psychiatric Emergency Service Patients Diagnosed As Malingering

BACKGROUND

Malingering is a common and challenging clinical presentation in emergency departments (EDs).

OBJECTIVE

This study describes characteristics and outcomes among patients diagnosed as malingering in a psychiatric emergency service.

METHODS

Index psychiatric ED encounters were identified for all adult patients seen during a 27-month period. Mortality data were obtained for patients from the state public health authority, and repeat ED visits for self-harm were obtained from the state hospital association. Patients with a diagnosis of malingering were compared with those without a malingering diagnosis using correlative statistics and multivariable analyses.

RESULTS

Of 4710 encounters analyzed, 236 (5%) had a malingering diagnosis. No patients diagnosed as malingering died of suicide within 365 days of discharge, compared with 16 (0.4%) nonmalingering patients. Self-harm outcomes were available for 2689 encounters; 129 (5%) had a malingering diagnosis. Malingering was significantly associated with a repeat ED visit for self-harm within 365 days in multivariable analyses (adjusted odds ratio 2.52; 95% confidence interval 1.35-4.70); p < 0.01).

CONCLUSIONS

No psychiatric emergency service patients diagnosed as malingering died by suicide after discharge. New clinical approaches must balance malingering patients' apparent low suicide risk with their other substantial comorbidities and risk for self-harm.

The Brief Suicide Cognitions Scale: Development and Clinical Application

The study explored the development of the Brief Suicide Cognitions Scale (B-SCS), a simple and brief measure of suicide risk. The B-SCS provides a brief measure that captures critical aspects of suicide risk embedded in core beliefs about the self as unlovable, one's emotional experience as unbearable, and life problems as unsolvable (i.e., the suicidal belief system), resulting in chronic or enduring suicide risk and heightened vulnerability for acute episodes secondary to internal and external triggers. Data were analyzed from three diverse samples, including a student sample (N = 349), an inpatient psychiatric sample (N = 160), and a sample of emergency department (ED) patients presenting secondary to a suicidal crisis (N = 94). Those in the student and inpatient samples completed additional symptom measures (hopelessness, anxiety, depression) and the ED sample provided 6-month follow-up data for suicide attempts. Reliability (internal consistency, test-retest), concurrent validity, construct (divergent, convergent) validity, factorial, incremental, and predictive validity were evaluated, along with calculation of predictive value of negative and positive tests, sensitivity, and specificity estimates. The B-SCS demonstrated good reliability and validity, a unidimensional factor structure across samples, along with good predictive validity and value in real-world clinical settings. The B-SCS is a brief, reliable and valid measure of suicide risk, with good ability to identify those with enduring risk for subsequent suicide attempts. The B-SCS offers a unique contribution to understanding and assessing the nature of suicide risk over time targeting the suicidal belief system, with easy application across inpatient and outpatient clinical settings, and good predictive value.