Associations between general sleep quality and measures of functioning and cognition in subjects recently diagnosed with bipolar disorder
Bibliographic record
Abstract
Abstract The present study aims to assess the association between sleep quality and the functional and cognitive impairment in subjects that recently converted to bipolar disorder (BD), subjects with past major depressive disorder (MDD) and subjects with recurrent MDD. This was a cross-sectional study corresponding to a second wave of a cohort study with a community sample. The first wave included 585 subjects diagnosed with MDD. Mood episodes were assessed through structured clinical interview. Functional and objective cognitive impairments were measured by the Functional Assessment Short Test (FAST) and Letter-number sequencing from Wechsler Adult Intelligence Scale III, respectively, and Cognitive Complaints in Bipolar Disorder Rating Assessment (COBRA) was used for subjective cognition measure. Sleep quality was assessed by Pittsburgh Sleep Quality Index (PSQI). In PSQI, FAST and COBRA, we found significantly worse scores in the BD and recurrent MDD groups when compared to past MDD group. Our findings also showed a significant association between functioning and subjective cognition with general sleep quality in all observed groups. We reinforce the need to follow-up for maintenance of functional and cognitive impairment, notably with BD patients, who may suffer in addition to damage caused by sleep alterations, also with neuroprogression in the long term.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".