INTERIM REPORT ON OUTCOMES OF ACQUIRED BRAIN INJURY SEEN IN A NEWLY ESTABLISHED NEUROREHABILIATION PROGRAM
Bibliographic record
Abstract
Objectives: To incorporate follow-up measures into a newly-established neurorehabilitation program for children following acquired brain injury (ABI). Methods: All children and their families attending the BI clinic over the period of a year were invited to complete a series of outcome measures. Outcome measures were chosen to provide a global picture of each patient's recovery including their quality of life, function, family stress and support service usage. The most recent outcome scores of 46 consenting patients were correlated with length of follow-up, injury severity and other outcome scores. Results: Families of children with mild injuries reported the highest stress levels (r=0.407, p=0.035). High family stress levels were also associated with increased length of follow-up and increased disability. Decreased quality of life was associated with increased length of follow-up (r=-0.414, p=0.04) and level of disability. Level of disability was associated with length of follow-up but surprisingly, not with injury severity. Conclusion: Children who suffer mild head injuries usually recover fully, however a subset of these patients experience significant long-term sequelae and their families report high levels of stress and poor quality-of-life. High stress levels are associated with ongoing disability requiring longterm neurorehabilitation from the BI program.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".