Colour vision impairments in bipolar disorder: A systematic review
Bibliographic record
Abstract
Visual impairments are common in patients with bipolar disorder (BD), and the neuropathophysiology may suggest a potential influence on colour vision. This systematic review aimed to assess existing data of colour vision impairment, including chromatic discrimination and colour blindness in patients with BD. Comprehensive literature search compliant with PRISMA 2020 was conducted in Medline, Embase, and Google Scholar from inception to February 28th, 2023. Our inclusion criteria were: (1) patients with a diagnosis of bipolar I or II disorder based on DSM, ICD, or clinical diagnosis, and (2) study investigating colour vision (i.e., including colour blindness and discrimination), with (3) no restrictions on the condition of the comparator group. Study quality appraisal was performed using the NIH Study Quality Assessment Tool. Five studies from Brazil, Netherlands, and USA, with 338 patients were included. Three cross-sectional studies assessed chromatic discrimination and two case-series assessed colour blindness in patients with BD. The three cross-sectional studies support reduced chromatic discrimination during mild to moderate mania in BD when compared to healthy comparators. The latter two articles presented low evidence of an X-linked inheritance of BD. Our review indicates evidence of reduced chromatic discrimination in mild to moderate mania. However, further research is needed to validate these findings and to extend to other mood states in BD given current limitations. Future studies can benefit from further multi-institutional data, larger sample sizes, appropriate blinding, the use of biomarkers, and statistical adjustment to confounders to fully elucidate the role of chromatic discrimination in 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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.006 |
| Bibliometrics | 0.009 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.000 |
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.
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".