Evolution of dizziness-related disability in children following concussion: a group-based trajectory analysis
Bibliographic record
Abstract
OBJECTIVE: This study aimed to identify Dizziness-Related Disability (DRD) recovery trajectories in pediatric concussion and assess clinical predictors of disability groups. MATERIALS AND METHODS: In this prospective cohort study, 81 children (8-17 years) diagnosed with an acute concussion took part in 3 evaluation sessions (baseline, 3-month, and 6-month). All sessions included the primary disability outcome, the Dizziness Handicap Inventory (DHI) to create the DRD recovery trajectories using group-based multi-trajectory modeling analysis. Each independent variable included general patients' characteristics, premorbid conditions, function and symptoms questionnaires, and clinical physical measures; and were compared between the trajectories with logistic regression models. RESULTS: = 17, 21%) were identified. The Predicting and Preventing Postconcussive Problems in Pediatrics (5P) total score (Odds Ratio (OR):1.50, 95% Confidence Interval (CI): 1.01-2.22), self-reported neck pain (OR:7.25, 95%CI: 1.24-42.36), and premorbid anxiety (OR:7.25, 95%CI: 1.24-42.36) were the strongest predictors of belonging to HD group. CONCLUSIONS: Neck pain, premorbid anxiety, and the 5P score should be considered initially in clinical practice as to predict DRD at 3 and 6-month. Further research is needed to refine predictions and enhance personalized treatment strategies for pediatric concussion.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.004 |
| 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) | 0.001 | 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 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".