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Record W2899284153 · doi:10.9740/mhc.2018.11.256

Treatment of anxiety disorders in patients with comorbid bipolar disorder

2018· article· en· W2899284153 on OpenAlexaboutno aff
Carol A. Ott

Bibliographic record

VenueMental Health Clinician · 2018
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsnot available
Fundersnot available
KeywordsAnxietyBipolar disorderMoodPsychiatryGeneralized anxiety disorderMood disordersPsychosocialComorbidityAnxiety disorderPsychologyAntidepressantClinical psychologyMedicine

Abstract

fetched live from OpenAlex

Anxiety disorders are the most prevalent comorbid diagnoses in patients with bipolar disorder (BD). A comorbid anxiety diagnosis can significantly impact the severity of bipolar symptoms, increase the risk of suicidality, and decrease psychosocial functioning and quality of life. The Canadian Network for Mood and Anxiety Treatments (CANMAT) task force published recommendations for treatment in 2012 suggesting that specific anticonvulsant mood stabilizers and second-generation antipsychotics are the medications of choice to treat these comorbidities. Serotonergic antidepressant medications are first-line medications for the treatment of most anxiety disorders; however, this can be problematic for a patient with BD. Antidepressant use in BD has been associated with a risk of manic switch as well as potential destabilization of mood. Mood stabilizer therapy should be established for patients with comorbid BD and an anxiety disorder before other medications are added to address the anxiety disorder. While benzodiazepine medications are recommended as third-line therapy in the CANMAT task force recommendations, their use should be avoided in patients with comorbid BD, posttraumatic stress disorder, and substance use disorders. The use of benzodiazepines should in general be avoided for all patients if possible, based upon current clinical research. Interpersonal, cognitive behavioral, and relaxation therapy are effective for the treatment of anxiety symptoms, especially emotional experiences, in patients who are euthymic.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.230
Threshold uncertainty score0.994

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.014
GPT teacher head0.325
Teacher spread0.311 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations20
Published2018
Admission routes1
Has abstractyes

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