Association Between Preinjury Symptoms and Postconcussion Symptoms at 4 Weeks in Youth
Bibliographic record
Abstract
OBJECTIVE: To investigate whether preinjury physical, emotional, cognitive, and sleep symptoms on the Post-Concussion Symptoms Inventory (PCSI) are associated with persistent postconcussion symptoms (PPCS) at 4 weeks and whether any associations are moderated by sex or age. STUDY SETTING AND PARTICIPANTS: A total of 3063 participants with acute concussion, presenting to 9 Canadian pediatric emergency departments, were enrolled from August 2013 to June 2015. DESIGN: A planned secondary analysis of a prospective, multicenter cohort study (Predicting Persistent Post-concussive Problems in Pediatrics or 5P). Primary outcome was PPCS at 4 weeks, defined as 3 or more new or worsening individual symptoms compared with the preinjury score at 28 days on the PCSI. The association between preinjury scores and PPCS was analyzed with a multivariable logistic regression analysis that included preinjury, sex, age, sex × preinjury, and age × preinjury interactions as predictors. Missing baseline covariates were imputed. RESULTS: A total of 2123 (n = 844 [39.8%] girls; median [IQR] age = 12.9 [10.7, 15.0] participants were included in the analysis. Preinjury physical symptom score was associated with PPCS at 4 weeks (χ2 = 13.87, df = 6, P = .031). The preinjury emotional score also contributed to the variability in PPCS (χ2 = 11.79, df = 6, P = .067). While girls reported higher preinjury physical, emotional, and cognitive scores than boys, neither sex nor age interacted with preinjury to predict PPCS at 4 weeks. Independent of age and sex, preinjury physical symptoms were associated with PPCS at 4 weeks (OR = 1.40; 95% CI, 1.15-1.70). CONCLUSION: Preinjury physical symptoms are associated with the probability of having PPCS at 4 weeks postconcussion independent of age and sex. Providers should consider preinjury symptoms to inform prognosis and recovery management.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".