Attention Deficits in a Comorbidity-Free Sample of Euthymic Pediatric Bipolar Disorder
Bibliographic record
Abstract
Attention deficits are considered one of the potential endophenotypic markers of Bipolar Disorder (BD). Pediatric bipolar disorder (PBD) likely has stronger genetic underpinnings than adult onset BD; therefore, demonstrating attention deficits in PBD can be both strategic and convincing in attesting their status as one of the potential endophenotypic markers of BD. However, unlike adult literature, uncertainty exists regarding the magnitude of attention deficits in PBD. In this regard, one key unresolved question is the potential impact of attention deficit hyperactivity disorder (ADHD). The main goal of the study was to examine attention deficits in a comorbidity-free sample of euthymic PBD patients. Thirty (21 boys, 9 girls) remitted PBD patients without co-morbidity and thirty age (<17 years), sex, handedness, and Full-Scale IQ matched control subjects were compared on performance on attention tasks. Working memory (WM), which might potentially confound with the attention task performances, was also examined. Compared to controls, PBD patients performed poorly on various tests of attention, but not on any WM tasks. Further, it was found that observed attention deficits were independent of residual mood symptoms, medication effect or illness characteristics. Such attention deficits in this comorbidity-free PBD sample further endorses its status as an endophenotypic marker of bipolar disorders and establishes continuity with deficits found in adult bipolar patients.
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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 | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 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) | 0.001 | 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".