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Record W3163928276 · doi:10.1017/s1092852921000213

Effects of Cariprazine on Cognition in Patients With Bipolar Mania or Mixed States: Post Hoc Analysis From 3 Randomized, Controlled Phase III Studies

2021· article· en· W3163928276 on OpenAlexaff

Bibliographic record

VenueCNS Spectrums · 2021
Typearticle
Languageen
FieldMedicine
TopicBipolar Disorder and Treatment
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsPost-hoc analysisSchizophrenia (object-oriented programming)Bipolar disorderYoung Mania Rating ScalePositive and Negative Syndrome ScaleBipolar I disorderPlaceboPopulation

Abstract

fetched live from OpenAlex

Abstract Introduction Cariprazine, a dopamine D3-preferring D3/D2 and serotonin 5-HT1A receptor partial agonist, is approved for the treatment of schizophrenia and for depressive, manic, or mixed episodes associated with bipolar I disorder. Previous post hoc analyses have demonstrated that cariprazine was effective versus placebo for improving cognitive symptoms in patients with schizophrenia or bipolar depression. This post hoc analysis evaluated the effects of cariprazine on cognitive symptoms in patients with acute manic or mixed bipolar episodes. Methods Data from 3 phase II/III, randomized, double-blind, placebo-controlled studies in patients with manic or mixed episodes associated with bipolar I disorder (NCT00488618, NCT01058096, NCT01058668) were pooled and analyzed. Patients were randomized to placebo or flexibly dosed cariprazine (3-12 mg/d, 3-6 mg/d, or 6-12 mg/d [1 study only]) for 3 weeks of double-blind treatment; all dose groups were combined for the pooled analysis. Cognitive symptoms were assessed using the Positive and Negative Syndrome Scale (PANSS) Cognitive subscale (sum of PANSS items P2, N5, N7, G10, G11); a score of 15 or greater at baseline indicated the presence of cognitive symptoms. Mean changes from baseline to week 3 in PANSS cognitive subscale/item scores and Young Mania Rating Scale (YMRS) total score were evaluated in the overall intent-to-treat (ITT) population and in the subgroup of patients with baseline cognitive symptoms. A mixed-effects model for repeated measures (MMRM) was used to impute missing values. Results Of the 1012 patients in the ITT population, 174 (placebo=71; cariprazine=103) had a PANSS Cognitive subscale score of 15 or greater at baseline. At week 3, the cariprazine group demonstrated significantly greater mean improvement than the placebo group on PANSS cognitive subscale scores in both the ITT population (−2.2 vs −1.3; P<.0001) and the subgroup with baseline cognitive symptoms (−4.0 vs −1.9; P=.0002). In patients with baseline cognitive symptoms, improvement was significantly greater for cariprazine- versus placebo-treated patients on YMRS total score (−16.7 vs −8.2; P<.0001) and the individual PANSS cognitive subscale items of conceptual disorganization (−1.1 vs −0.5; P=.0004), difficulty in abstract thinking (−0.8 vs −0.3; P=.0044), stereotyped thinking (−0.3 vs −0.1; P=.0350), and poor attention (−1.1 vs −0.6; P=.0043). Conclusion In patients with manic or mixed episodes associated with bipolar I disorder, cariprazine versus placebo was effective in improving cognitive symptoms in the overall patient population as well as in patients with baseline cognitive symptoms. In addition, cariprazine versus placebo also demonstrated efficacy in improving manic symptoms in patients with baseline cognitive symptoms. These results suggest that cariprazine may provide benefits for the treatment of cognitive symptoms in patients with bipolar I mania. Funding AbbVie Inc.

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)0.014
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Meta-analysis · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.014
Threshold uncertainty score0.075

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.010
Meta-epidemiology (narrow)0.0030.001
Meta-epidemiology (broad)0.0080.013
Bibliometrics0.0010.001
Science and technology studies0.0010.001
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.007
GPT teacher head0.260
Teacher spread0.253 · 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 designMeta-analysis
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

Citations6
Published2021
Admission routes1
Has abstractyes

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