Post-Concussion Syndrome and Sleep Apnea: A Retrospective Study
Bibliographic record
Abstract
BACKGROUND: Concussion symptoms typically resolve within 7-10 days, but 10%-25% of patients do not fully recover. They can develop post-concussion syndrome (PCS), which includes sleep abnormalities such as obstructive sleep apnea. It is unclear how specific sleep problems manifest in PCS and how it relates to cognition and symptomology. METHODS: A retrospective chart review was conducted on PCS patients seen at the University Health Network (UHN) Concussion Clinic and sent for sleep study. Neuropsychology tests, concussion features, PCS symptoms, and demographics were abstracted from clinical charts. Sleep measures were abstracted from the overnight sleep study. Data were analyzed using chi-squared tests and linear regression. RESULTS: Fifty-one patients completed the sleep study; 78% of these were diagnosed with sleep apnea. Patients with sleep apnea reported significantly more memory symptoms. A trend existed for higher total symptom number. Age was significantly different between the two groups. Women and men were equally at risk of being diagnosed with sleep apnea. CONCLUSIONS: Sleep apnea is common in PCS patients complaining of non-restorative sleep and/or waking up with headaches. Sleep apnea was associated with more memory symptoms. PCS patients are at higher risk for sleep apnea and sleep study should be considered if complaining of non-restorative sleep and/or waking up with headaches, regardless of sex and other known risk factors.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".