Neurocognitive functioning in bipolar disorder: What we know and what we don’t
Bibliographic record
Abstract
Introduction: This narrative review of systematic reviews and meta-analyses aims at compiling available evidence in various aspects of neurocognitive functioning in Bipolar Disorder (BD).Methods: We conducted a MEDLINE literature search and identified 38 relevant systematic reviews and metaanalyses.Results: Current evidence suggests that BD is associated with cognitive impairment across multiple domains and during all clinical states. However, there is a considerable cognitive heterogeneity within BD, which cannot be explained by clinical subtypes, and the pattern of neurocognitive impairment in BD overlaps with other psychiatric conditions such as major depression and schizophrenia. Residual depressive symptoms, poor clinical course and higher number of manic episodes may negatively impact cognitive performance, which is a major predictor of general functioning in BD. Evidence from available prospective studies does not support the notion of progressive cognitive decline in BD while some evidence exists to suggest patients may show some improvements in cognitive functioning following the first manic episode. Furthermore, a subset of patients may show premorbid cognitive abnormalities that could signal an early neurodevelopmental aetiology. Preliminary findings from small studies identify potential pro-cognitive effects of Cognitive Remediation, erythropoietin, intranasal insulin, lurasidone, mifepristone, repetitive Transcranial Magnetic Stimulation and transcranial Direct Current Stimulation in BD.Discussion: Longitudinal studies in high-risk individuals can provide a better understanding of the development and progression of neurocognitive impairment in BD. Largescale randomised control trials are needed to compare the pro-cognitive efficacy of various pharmacological and non-pharmacological interventions in different cognitive subgroups of patients at different stages of BD.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.004 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".