Identifying Persistent Postconcussion Symptom Risk in a Pediatric Sports Medicine Clinic
Bibliographic record
Abstract
BACKGROUND: Although most children report symptom resolution within a month of a concussion, some patients experience persistent postconcussion symptoms (PPCS) that continues for more than 1 month. Identifying patients at risk for PPCS soon after an injury can provide useful clinical information. PURPOSE: To determine if the Predicting Persistent Post-concussive Problems in Pediatrics (5P) clinical risk score, an emergency department (ED)-derived and validated tool, is associated with developing PPCS when obtained in a primary care sports concussion setting. STUDY DESIGN: Cohort study; Level of evidence, 3. METHODS: We conducted a study of patients seen at a pediatric sports medicine concussion clinic between May 1, 2013, and October 1, 2017, who were <19 years of age and evaluated within 10 days of a concussion. The main outcome was PPCS, defined as symptoms lasting >28 days. Nine variables were used to calculate the 5P clinical risk score, and we assessed the association between the 5P clinical risk score and PPCS occurrence. The secondary outcome was total symptom duration. RESULTS: We examined data from 230 children (mean age, 14.8 ± 2.5 years; 50% female; mean time from injury to clinical assessment, 5.6 ± 2.7 days). In univariable analyses, a greater proportion of those who developed PPCS reported feeling slowed down (72% vs 44%, respectively; P < .001), headache (94% vs 72%, respectively; P < .001), sensitivity to noise (71% vs 43%, respectively; P < .001), and fatigue (82% vs 51%, respectively; P < .001) and committed ≥4 errors in tandem stance (33% vs 7%, respectively; P < .001) than those who did not. Higher 5P clinical risk scores were associated with increased odds of developing PPCS (adjusted odds ratio [OR], 1.62 [95% CI, 1.30-2.02]) and longer symptom resolution times (β = 8.40 [95% CI, 3.25-13.50]). Among the individual participants who received a high 5P clinical risk score (9-12), the majority (82%) went on to experience PPCS. The area under the curve for the 5P clinical risk score was 0.75 (95% CI, 0.66-0.84). After adjusting for the effect of covariates, fatigue (adjusted OR, 2.93) and ≥4 errors in tandem stance (adjusted OR, 7.40) were independently associated with PPCS. CONCLUSION: Our findings extend the potential use for an ED-derived clinical risk score for predicting the PPCS risk into the sports concussion clinic setting. While not all 9 predictor variables of the 5P clinical risk score were independently associated with the PPCS risk in univariable or multivariable analyses, the combination of factors used to calculate the 5P clinical risk score was significantly associated with the odds of developing PPCS. Thus, obtaining clinically pragmatic risk scores soon after a concussion may be useful for early treatments or interventions to mitigate the PPCS risk.
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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 | 0.005 |
| 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 | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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 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".