Risk of suicide attempt and suicide death in patients treated for bipolar disorder

2007 ◽  
Vol 9 (5) ◽  
pp. 526-530 ◽  
Author(s):  
Gregory E Simon ◽  
Enid Hunkeler ◽  
Bruce Fireman ◽  
Janelle Y Lee ◽  
James Savarino
2020 ◽  
Author(s):  
Mbemba Jabbi ◽  
Wade Weber ◽  
Jeffrey Welge ◽  
Fabiano Nery ◽  
Maxwell Tallman ◽  
...  

ABSTRACTOver 2.3 million people in the United States live with bipolar disorder. Sixty percent of those with a bipolar disorder diagnosis attempt suicide at least once in their lifetime, and up to 19% die by suicide. However, the neurobiology of suicide attempts in bipolar disorder remains unclear. Here, we studied the neuroanatomical basis for suicide attempt history in bipolar disorder by measuring gray matter volumes (GMV) to identify differences in brain-volumes in 121 participants with bipolar disorder type I, and healthy participants (n=40). The bipolar group consisted of individuals with suicide attempt history (n=23) and no suicide attempt history (n=58). All participants completed behavioral/diagnostic assessments and MRI measures of GMV. We focused on a predefined frontolimbic circuitry in bipolar disorder versus (vs.) healthy to first identify diagnostic GMV markers and to specifically identify markers for suicide attempt history. We found reduced GMV markers for bipolar diagnosis (i.e., bipolar<healthy) in the anterior cingulate cortex (ACC), and dorsolateral prefrontal cortices (DLPFC). Our observed frontolimbic GMV abnormalities were associated with suicide attempt history and measures of individual variations in current suicidal ideation at the time of scanning. These results identified a frontolimbic-GMV marker for bipolar diagnosis and suicidal behavioral risk tendencies.HighlightsSuicide is a major health problem especially in bipolar disorder but the neurobiological basis for suicide attempts remains obscure. We identified an anterior cingulate and dorsolateral prefrontal cortical volume correlate for suicide attempt history and suicidal ideation and thereby demonstrates a convergent brain marker for suicidal behaviors.


2020 ◽  
Vol 11 (02) ◽  
pp. 291-298
Author(s):  
Karthick Subramanian ◽  
Vikas Menon ◽  
Siddharth Sarkar ◽  
Vigneshvar Chandrasekaran ◽  
Nivedhitha Selvakumar

Abstract Background Suicide is the leading contributor to mortality in bipolar disorder (BD). A history of suicidal attempt is a robust predictive marker for future suicide attempts. Personality profiles and coping strategies are the areas of contemporary research in bipolar suicides apart from clinical and demographic risk factors. However, similar research in developing countries is rarer. Objectives The present study aimed to identify the risk factors associated with suicidal attempts in BD type I (BD-I). Materials and Methods Patients with BD-I currently in clinical remission (N = 102) were recruited. Sociodemographic details and the clinical data were collected using a semistructured pro forma. The psychiatric diagnoses were confirmed using the Mini-International Neuropsychiatric Interview 5.0. The National Institute of Mental Health–Life Chart Methodology Clinician Retrospective Chart was used to chart the illness course. Presumptive Stressful Life Events Scale, Coping Strategies Inventory Short Form, Buss–Perry aggression questionnaire, Past Feelings and Acts of Violence, and Barratt Impulsivity scale were used to assess the patient’s stress scores, coping skills, aggression, violence, and impulsivity, respectively. Statistical Analysis Descriptive statistics were used for demographic details and characteristics of the illness course. Binary logistic regression analyses were performed to identify the predictors for lifetime suicide attempt in BD-I. Results A total of 102 patients (males = 49 and females = 53) with BD-I were included. Thirty-seven subjects (36.3%) had a history of suicide attempt. The illness course in suicide attempters more frequently had an index episode of depression, was encumbered with frequent mood episodes, especially in depression, and had a higher propensity for psychiatric comorbidities. On binary logistic regression analysis, the odds ratios (ORs) for predicting a suicide attempt were highest for positive family history of suicide (OR: 13.65, 95% confidence interval [CI]: 1.28–145.38, p = 0.030), followed by the presence of an index depressive episode (OR: 6.88, 95% CI: 1.70–27.91, p = 0.007), and lower scores on problem-focused disengagement (OR: 0.72, 95% CI: 0.56–0.92, p = 0.009). Conclusion BD-I patients with lifetime suicide attempt differ from non-attempters on various course-related and temperamental factors. However, an index episode depression, family history of suicide, and lower problem-focused engagement can predict lifetime suicide attempt in patients with BD-I.


2018 ◽  
Vol 8 (3) ◽  
pp. 138-147 ◽  
Author(s):  
Charles F. Caley ◽  
Emily Perriello ◽  
Julia Golden

Abstract Introduction: In January 2008 the US Food and Drug Administration issued a warning to healthcare professionals about the potential for an increased risk of suicidal thinking and behavior associated with antiepileptic drugs (AEDs). Given that AEDs are important for treating bipolar disorder (BD), a better understanding of suicide-related events is necessary. Methods: A PubMed search was performed using the following search terms: anticonvulsant OR valpro* OR carbamazepine OR lamotrigine OR oxcarbazepine OR topiramate AND bipolar AND suicid*. The objective was to identify published investigations reporting rate and/or risk data of suicide-related outcomes in BD patients treated with AED monotherapy. Results: The search identified 323 reviewable citations, with 13 of these studies (4.0%) being reviewed. Valproate was studied most often, and lithium treatment was frequently used as a reference group. Carbamazepine and lamotrigine had small treatment exposure durations. Suicide attempts and suicide deaths were studied the most; a few trials investigated suicidal thinking and/or hospitalizations for suicidal behavior. Suicide attempt rates occurred in the following order: no treatment &gt; carbamazepine &gt; valproate &gt; lithium, while suicide death rates were: no treatment &gt; valproate &gt; lithium &gt; carbamazepine. For valproate, the risk of suicide attempts and suicide death appeared higher than lithium, but lower than no treatment. Discussion: Investigating suicide-related events for AEDs in BD is difficult; more data are necessary for valproate, carbamazepine, and lamotrigine. An improved understanding of AED treatment and suicide-related events in BD may help pharmacists become more effective at supporting their patients with BD.


2015 ◽  
Vol 38 (3) ◽  
pp. e282-e291 ◽  
Author(s):  
Jalal Poorolajal ◽  
Tahereh Haghtalab ◽  
Mehran Farhadi ◽  
Nahid Darvishi

2013 ◽  
Vol 64 (12) ◽  
pp. 1195-1202 ◽  
Author(s):  
Gregory E. Simon ◽  
Carolyn M. Rutter ◽  
Do Peterson ◽  
Malia Oliver ◽  
Ursula Whiteside ◽  
...  

2013 ◽  
Vol 13 (1) ◽  
Author(s):  
Ali Bani-Fatemi ◽  
Gina Polsinelli ◽  
James L Kennedy ◽  
Vincenzo De Luca

2011 ◽  
Vol 26 (S2) ◽  
pp. 238-238
Author(s):  
V. Nogueira ◽  
J. Valente ◽  
M.J. Soares ◽  
A.T. Pereira ◽  
B. Maia ◽  
...  

IntroductionBipolar Disorder is a serious, common and disabling mental disorder which is associated to high morbidity and high suicide attempt rates.ObjectivesTo identify clinical and social-demographic variables associated to suicidal behaviour in Bipolar Disorder.MethodsThe samples comprises 124 patients (62.1% females) diagnosed with Bipolar Disorder (ICD-10 diagnosis following DIGS/OPCRIT). The variables selected to the analysis were extracted from DIGS and OPCRIT.ResultsSuicidal behaviour occurs in 27.1% of the patients; the most used method was voluntary drug poisoning; it's more frequent in females, with males using more violent methods - remaining results still unavailable.ConclusionsThis study identifies several clinical and social-demographic variables that can help the clinician to delineate a suicidal profile among his Bipolar patients, hence improving his ability to develop an early intervention plan and suicide prevention strategies.


2021 ◽  
Vol 12 (04) ◽  
pp. 778-787
Author(s):  
Rod L. Walker ◽  
Susan M. Shortreed ◽  
Rebecca A. Ziebell ◽  
Eric Johnson ◽  
Jennifer M. Boggs ◽  
...  

Abstract Background Suicide risk prediction models have been developed by using information from patients' electronic health records (EHR), but the time elapsed between model development and health system implementation is often substantial. Temporal changes in health systems and EHR coding practices necessitate the evaluation of such models in more contemporary data. Objectives A set of published suicide risk prediction models developed by using EHR data from 2009 to 2015 across seven health systems reported c-statistics of 0.85 for suicide attempt and 0.83 to 0.86 for suicide death. Our objective was to evaluate these models' performance with contemporary data (2014–2017) from these systems. Methods We evaluated performance using mental health visits (6,832,439 to mental health specialty providers and 3,987,078 to general medical providers) from 2014 to 2017 made by 1,799,765 patients aged 13+ across the health systems. No visits in our evaluation were used in the previous model development. Outcomes were suicide attempt (health system records) and suicide death (state death certificates) within 90 days following a visit. We assessed calibration and computed c-statistics with 95% confidence intervals (CI) and cut-point specific estimates of sensitivity, specificity, and positive/negative predictive value. Results Models were well calibrated; 46% of suicide attempts and 35% of suicide deaths in the mental health specialty sample were preceded by a visit (within 90 days) with a risk score in the top 5%. In the general medical sample, 53% of attempts and 35% of deaths were preceded by such a visit. Among these two samples, respectively, c-statistics were 0.862 (95% CI: 0.860–0.864) and 0.864 (95% CI: 0.860–0.869) for suicide attempt, and 0.806 (95% CI: 0.790–0.822) and 0.804 (95% CI: 0.782–0.829) for suicide death. Conclusion Performance of the risk prediction models in this contemporary sample was similar to historical estimates for suicide attempt but modestly lower for suicide death. These published models can inform clinical practice and patient care today.


2021 ◽  
pp. 1-9
Author(s):  
Ikuo Otsuka ◽  
Hanga Galfalvy ◽  
Jia Guo ◽  
Masato Akiyama ◽  
Dan Rujescu ◽  
...  

Abstract Background Suicidal behavior is moderately heritable and a consequence of a combination of the diathesis traits for suicidal behavior and suicide-related major psychiatric disorders. Here, we sought to examine shared polygenic effects between various psychiatric disorders/traits and suicidal behavior and to compare the shared polygenic effects of various psychiatric disorders/traits on non-fatal suicide attempt and suicide death. Methods We used our genotyped European ancestry sample of 260 non-fatal suicide attempters, 317 suicide decedents and 874 non-psychiatric controls to test whether polygenic risk scores (PRSs) obtained from large GWASs for 22 suicide-related psychiatric disorders/traits were associated with suicidal behavior. Results were compared between non-fatal suicide attempt and suicide death in a sensitivity analysis. Results PRSs for major depressive disorder, bipolar disorder, schizophrenia, ADHD, alcohol dependence, sensitivity to environmental stress and adversity, educational attainment, cognitive performance, and IQ were associated with suicidal behavior (Bonferroni-corrected p < 2.5 × 10−4). The polygenic effects of all 22 psychiatric disorders/traits had the same direction (p for binomial tests = 4.8 × 10−7) and were correlated (Spearman's ρ = 0.85) between non-fatal suicide attempters and suicide decedents. Conclusions We found that polygenic effects for major psychiatric disorders and diathesis-related traits including stress responsiveness and intellect/cognitive function contributed to suicidal behavior. While we found comparable polygenic architecture between non-fatal suicide attempters and suicide decedents based on correlations with PRSs of suicide-related psychiatric disorders/traits, our analyses are limited by small sample size resulting in low statistical power to detect difference between non-fatal suicide attempt and suicide death.


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