Efficacy and acceptability of pharmacotherapy for comorbid anxiety symptoms in bipolar disorder: A systematic review and meta‐analysis

Cullen, Clare; Kappelmann, Nils; Umer, Madeha; Abdolizadeh, Ali; Husain, Muhammad; Bonato, Sarah; Sharma, Gaurav; Xue, Siqi; Ortiz, Abigail; Kloiber, Stefan; Mulsant, Benoit H.

doi:10.1111/bdi.13125

Cited by 7 publications

(5 citation statements)

References 71 publications

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“…Interestingly, also presence of psychiatric comorbidities was one of the most valuable predictive features, in particular substance or alcohol use disorders [ 57 , 61 , 71 , 72 , 92 ]. These results emphasize the importance of a comprehensive evaluation of psychiatric patients and of the burden that comorbidities represent, also given their frequent occurrence [ 102 ]. This is particularly important for the comorbid use of alcohol and drug abuse, since they can reduce compliance to treatments [ 103 ] and increase impulsive behaviors [ 104 ], which in turn may act as risk factors for suicide.…”

Section: Discussionmentioning

confidence: 99%

Machine learning and the prediction of suicide in psychiatric populations: a systematic review

Pigoni,

Delvecchio,

Turtulici

et al. 2024

Transl Psychiatry

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Machine learning (ML) has emerged as a promising tool to enhance suicidal prediction. However, as many large-sample studies mixed psychiatric and non-psychiatric populations, a formal psychiatric diagnosis emerged as a strong predictor of suicidal risk, overshadowing more subtle risk factors specific to distinct populations. To overcome this limitation, we conducted a systematic review of ML studies evaluating suicidal behaviors exclusively in psychiatric clinical populations. A systematic literature search was performed from inception through November 17, 2022 on PubMed, EMBASE, and Scopus following the PRISMA guidelines. Original research using ML techniques to assess the risk of suicide or predict suicide attempts in the psychiatric population were included. An assessment for bias risk was performed using the transparent reporting of a multivariable prediction model for individual prognosis or diagnosis (TRIPOD) guidelines. About 1032 studies were retrieved, and 81 satisfied the inclusion criteria and were included for qualitative synthesis. Clinical and demographic features were the most frequently employed and random forest, support vector machine, and convolutional neural network performed better in terms of accuracy than other algorithms when directly compared. Despite heterogeneity in procedures, most studies reported an accuracy of 70% or greater based on features such as previous attempts, severity of the disorder, and pharmacological treatments. Although the evidence reported is promising, ML algorithms for suicidal prediction still present limitations, including the lack of neurobiological and imaging data and the lack of external validation samples. Overcoming these issues may lead to the development of models to adopt in clinical practice. Further research is warranted to boost a field that holds the potential to critically impact suicide mortality.

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Section: Discussionmentioning

confidence: 99%

Machine learning and the prediction of suicide in psychiatric populations: a systematic review

Pigoni,

Delvecchio,

Turtulici

et al. 2024

Transl Psychiatry

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“…In general, people with comorbidities tend to have greater symptom burden and functional impairment and have lower response rates to treatment 4647. Data on approaches to treat specific comorbid disorders in bipolar disorder are limited,4849 and clinicians are often left to rely on their clinical judgment. The most parsimonious approach is to treat primary illness as fully as possible before considering additional treatment options for remaining comorbid symptoms.…”

Section: Epidemiologymentioning

confidence: 99%

Diagnosis and management of bipolar disorders

Goes

2023

BMJ

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Bipolar disorders (BDs) are recurrent and sometimes chronic disorders of mood that affect around 2% of the world’s population and encompass a spectrum between severe elevated and excitable mood states (mania) to the dysphoria, low energy, and despondency of depressive episodes. The illness commonly starts in young adults and is a leading cause of disability and premature mortality. The clinical manifestations of bipolar disorder can be markedly varied between and within individuals across their lifespan. Early diagnosis is challenging and misdiagnoses are frequent, potentially resulting in missed early intervention and increasing the risk of iatrogenic harm. Over 15 approved treatments exist for the various phases of bipolar disorder, but outcomes are often suboptimal owing to insufficient efficacy, side effects, or lack of availability. Lithium, the first approved treatment for bipolar disorder, continues to be the most effective drug overall, although full remission is only seen in a subset of patients. Newer atypical antipsychotics are increasingly being found to be effective in the treatment of bipolar depression; however, their long term tolerability and safety are uncertain. For many with bipolar disorder, combination therapy and adjunctive psychotherapy might be necessary to treat symptoms across different phases of illness. Several classes of medications exist for treating bipolar disorder but predicting which medication is likely to be most effective or tolerable is not yet possible. As pathophysiological insights into the causes of bipolar disorders are revealed, a new era of targeted treatments aimed at causal mechanisms, be they pharmacological or psychosocial, will hopefully be developed. For the time being, however, clinical judgment, shared decision making, and empirical follow-up remain essential elements of clinical care. This review provides an overview of the clinical features, diagnostic subtypes, and major treatment modalities available to treat people with bipolar disorder, highlighting recent advances and ongoing therapeutic challenges.

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“…Based on these findings, Olanzapine and Quetiapine may have some beneficial short-term effects on anxiety symptoms in adult BD patients, when compared with antiepileptic mood stabilizers (Lamotrigine and Valproic Acid), likely due to their sedative properties related to the blockade of a wide range of receptors, including histamine H1 receptors [ 191 ]. Indeed, several other randomized-controlled trials on the efficacy of atypical antipsychotics for anxiety symptoms in adults with BD have been conducted, with multiple studies showing modest efficacy of Quetiapine over placebo [ 192 ]. However, only a few studies are available overall, and most are limited by using outcome measures focusing on any type of anxiety morbidity, while none was directed at specific anxiety syndromes.…”

Section: Anxiety Disordersmentioning

confidence: 99%

Comorbidities in Youth with Bipolar Disorder: Clinical Features and Pharmacological Management

Sesso

Brancati

Masi

2023

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Background: Bipolar Disorder (BD) is a highly comorbid condition, and rates of co-occurring disorders are even higher in youth. Comorbid disorders strongly affect clinical presentation, natural course, prognosis, and treatment. Method: This review focuses on the clinical and treatment implications of the comorbidity between BD and Attention-Deficit/Hyperactivity Disorder (ADHD), disruptive behavior disorders (Oppositional Defiant Disorder and/or Conduct Disorder), alcohol and substance use disorders, Autism Spectrum Disorder, anxiety disorders, Obsessive-Compulsive Disorder, and eating disorders. Results: These associations define specific conditions which are not simply a sum of different clinical pictures, but occur as distinct and complex combinations with specific developmental pathways over time and selective therapeutic requirements. Pharmacological treatments can improve these clinical pictures by addressing the comorbid conditions, though the same treatments may also worsen BD by inducing manic or depressive switches. Conclusion: The timely identification of BD comorbidities may have relevant clinical implications in terms of symptomatology, course, treatment and outcome. Specific studies addressing the pharmacological management of BD and comorbidities are still scarce, and information is particularly lacking in children and adolescents; for this reason, the present review also included studies conducted on adult samples. Developmentally-sensitive controlled clinical trials are thus warranted to improve the prognosis of these highly complex patients, requiring timely and finely personalized therapies.

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Efficacy and acceptability of pharmacotherapy for comorbid anxiety symptoms in bipolar disorder: A systematic review and meta‐analysis

Cited by 7 publications

References 71 publications

Machine learning and the prediction of suicide in psychiatric populations: a systematic review

Machine learning and the prediction of suicide in psychiatric populations: a systematic review

Diagnosis and management of bipolar disorders

Comorbidities in Youth with Bipolar Disorder: Clinical Features and Pharmacological Management

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