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Record W6903363376 · doi:10.1192/j.eurpsy.2023.259

Combination therapy for bipolar disorder : What to combine and which cautions to take ?

2023· article· en· W6903363376 on OpenAlexaboutno aff

Bibliographic record

VenuePubMed Central · 2023
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsBipolar disorderLamotrigineDivalproexLurasidoneAsenapineCombination therapyRisperidoneTreatment of bipolar disorderMood

Abstract

fetched live from OpenAlex

INTRODUCTION: Bipolar disorder is one of the leading causes of disability among young adults. Given the heterogeneity of the disorder and the complexity of its etiopathogenesis, combination therapy is often considered as part of the treatment regimen. OBJECTIVES: To assess the place of non-pharmacological interventions as a co-adjuvant to pharmacological treatment, to discuss the role of polytherapy in the management of bipolar disorder and to underline the drug to drug interactions to keep in mind. METHODS: We present a critical review of recent international recommendations for the management of bipolar disorder. Two main evidence-based guidelines were included: The 2020 Royal Australian and New Zealand College of Psychiatrists clinical practice guidelines for mood disorders and The 2018 Canadian Network for Mood and Anxiety Treatment. RESULTS: According to guidelines, the outcomes in bipolar disorder are improved when medication is combined with evidence-based psychological treatment and lifestyle changes. As to polytherapy, it is often recommended to maximise the treatment efficacy. Studies have shown that combination treatments tend to work faster and more effectively than monotherapy especially in episodes with higher index severity. For the management of agitation, an adjuctive treatment by Haloperidol with midazolam or promethazine can be prescribed. In acute mania, combination therapy with quetiapine, aripiprazole, risperidone or asenapine and lithium or divalproex is recommended as first-line treatment options. Combinations of mood-stabilizing drugs may be more often necessary when rapid cycling is present. In a manic episode with mixed features the use of divalproex with an atypical antipyshcotic is recommended. In bipolar I depression, lurasidone and lamotrigine are often used as adjunctive therapies. When anxious distress is present, the combination of olanzapine and fluoxetine has shown to be effective. In a depression with atypical features, tranylcypromine (IMAO) can be added to lithium, divalproex or a second generation antipsychotic for a better result. Adjunctive treatment of olanzapine with fluoxetine may be necessary in a depression with mixed features. However, in bipolar II depression and for maintenance treatment no adjunctive therapies are recommended. Finally, it is important to consider the adverse effects resulting from polytherapy. Using lithium as an adjunctive medication may increase the risk of tremor and acute dystonic reactions and can be a contributing factor for neuroleptic malignant syndrome, whereas divalproex can be an inducer or an inhibitor of some atypical antipsychotics. CONCLUSIONS: Rational polytherapy allows better and faster control over symptoms of bipolar disorder and should be considered after a detailed discussion of risks and benefits. DISCLOSURE OF INTEREST: None Declared

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.025
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.007
Threshold uncertainty score0.039

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.025
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0020.002
Science and technology studies0.0010.002
Scholarly communication0.0030.006
Open science0.0020.001
Research integrity0.0040.007
Insufficient payload (model declined to judge)0.0060.003

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.021
GPT teacher head0.267
Teacher spread0.246 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2023
Admission routes1
Has abstractyes

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