ABSTRACT 365
Bibliographic record
Abstract
Background and aims: When parents are asked to describe their long-term concerns for their child with TBI, they often target executive dysfunction. Executive functions (EFs) are those cognitive abilities that regulate, control, and manage other cognitive processes. The mechanism of TBI-related EF changes is not well understood. Aims: We assessed the pattern of EF changes over the first year post-injury, including what EFs are affected, whether and how they recover, and potential predictors of these changes. Methods: 53 youth, age 5 to 18 years, who had sustained complicated mild to severe TBIs were recruited from five children’s hospitals in Canada (Institutional Review Boards provided approval of the study). Parents completed rating of EF symptoms (Behaviour Rating Inventory of Executive Function) at time of injury (baseline) and at 3, 6, and 12 months post-injury. Serum protein and brain neuroimaging analysis provided potential biomarkers of TBI-related EF changes. Results: Parent reports of EF changes are heterogeneous following pediatric TBI with some abilities reportedly minimally affected (inhibition, planning, organization), while others exhibit decline in the first 3 months (working memory and initiation) or 6 months (emotional control, flexibility, and monitoring behaviour). Many EFs fail to fully recover one year following injury. Serum and brain biomarkers may predict persisting changes in EF. Conclusions: An acute brain MRI and serum biomarkers of brain injury may be important prognostic tools for predicting the course of EF changes following TBI, which is important for patients and their families because EFs are known to affect cognitive processes (memory and attention), academic achievement, and behaviour regulation.
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 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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.723 | 0.597 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".