Investigating the Relationship between Sleep Duration, Symptom Burden and Cerebral Blood Flow in Pediatric Concussion Recovery
Bibliographic record
Abstract
This thesis investigated sleep duration in behavioral and neurophysiological recovery of pediatric concussion. N=291 concussed youth wore an accelerometer and completed daily sleep logs throughout 2-weeks, and completed self-report questionnaires on personal and injury characteristics throughout 4-weeks. A subsample (n=81) completed a perfusion neuroimaging session at 72+/-48-hours post-injury. Mean sleep duration beyond 9.9-hours throughout the first 2-weeks of recovery was associated with increased symptom burden at 1-week, 2-weeks, and 4-weeks, and predicted risk of persistent symptoms at 4-weeks. Increased sleep duration predicted reduced hyper-perfusion volume at 72-hours, and a negative trend between sleep duration and symptom burden was observed at 72-hours. The negative relationship between sleep and hyper-perfusion may suggest an influence of increased sleep duration on acute neurophysiological recovery. However, long sleep durations throughout 2-weeks were associated with increased symptom burden. Therefore, increased sleep duration may be required in the first few days following injury, but not thereafter.
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 | 0.000 | 0.002 |
| 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) | 0.001 | 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".