Post-Concussion Symptoms in Older Adults Following a Mild Traumatic Brain Injury
Bibliographic record
Abstract
OBJECTIVE: Main objective: to estimate the prevalence of post-concussion symptoms (PPCS) in patients aged ≥55 years. Secondary objective: to identify the predictive factors associated with PPCS in this age group. SETTING: Seven Canadian academic Level I and Level II trauma centers' emergency department (ED). PARTICIPANTS: 356 patients aged ≥55 years consulting in the ED within 24 hours of a mild traumatic brain injury (TBI) between July 2013 and October 2016 were included in this study. DESIGN: This is a planned sub-analysis of a prospective multicenter cohort study. Patients were identified in the ED by emergency physicians and research assistants. Participants were contacted via telephone for follow-up at 7, 30, and 90 days post-mild TBI. During these follow-ups, research assistants assessed PPCS using the Rivermead Post-Concussion Symptoms Questionnaire (RPQ). A modified Poisson regression assessed the association between PPCS and potential predictors. MAIN MEASURES: The main outcome of this study was the presence of PPCS at 90 days, defined as the presence of spontaneously described severe (RPQ ≥1 symptom of 4 points, or 2 symptoms of 3 points), persistent symptoms that affect the patients' life. RESULTS: PPCS at 90 days was observed in 16%, [95% CI 12.6-20.2] of our cohort, and most of those reporting PPCS were aged between 55 and 65 years (63.2%). We identified 4 variables associated with PPCS: cervical sprains (RR: 2.28, [95% CI 1.34-3.86], P < .01), female sex (RR: 3.12 [95% CI 1.90-5.12], P < .01), at least 3 different prescribed medications (RR: 1.68 [95% CI 1.02-2.76], P < .05) and age, which appeared to be protective (RR: 0.63 [95% CI 0.42-0.92], P < .01). CONCLUSION: Our results identified patient characteristics associated with PPCS that can be easily recognized in the ED, such as patient sex, the use of at least 3 different medications and the presence of cervical sprain. Early identification of older adults at higher risk of PPCS is important to optimize care and guide post-ED management.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| 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".