Early cognitive impairment is common in pediatric patients following mild traumatic brain injury
Bibliographic record
Abstract
INTRODUCTION: The incidence and factors related to early cognitive impairment (ECI) after mild traumatic brain injury (mTBI) in pediatric trauma patients (PTPs) are unknown. Prior data in the adult population demonstrated an ECI incidence of 51% after mTBI and strong correlation with initial Glasgow Coma Scale (GCS) and Brain Injury Guidelines (BIG) category. Therefore, we hypothesized that ECI is common after mTBI in PTPs and associated with initial GCS and BIG category. METHODS: A single-center, retrospective review of PTPs (age, 8-17 years) from 2015 to 2019 with intracranial hemorrhage and mTBI (GCS score, 13-15) was performed. Primary outcome was ECI, defined as Ranchos Los Amigos score less than 8. Comparisons between ECI and non-ECI groups regarding Injury Severity Score (ISS), demographics, and cognitive and clinical outcomes were evaluated using χ2 statistics and Wilcoxon rank sum tests. Odds of ECI were evaluated using multivariable logistic regression. RESULTS: From 47 PTPs with mTBI, 18 (38.3%) had ECI. Early cognitive impairment patients had a higher ISS than non-ECI patients (19.7 vs. 12.6, p = 0.003). Injuries involving motor vehicles were more often related to ECI than non-auto-involved mechanisms (55% vs. 15%, p = 0.005). Lower GCS score (odds ratio [OR], 6.60; 95% confidence interval [CI], 1.34-32.51, p = 0.02), higher ISS (OR, 1.12; 95% CI, 1.01-1.24; p = 0.030), and auto-involved injuries (OR, 6.06; 95% CI, 1.15-31.94; p = 0.030) were all associated with increased risk of ECI. There was no association between BIG category and risk of ECI (p > 0.05). CONCLUSION: Nearly 40% of PTPs with mTBI suffer from ECI. Lower initial GCS score, higher ISS, and autoinvolved mechanism of injury were associated with increased risk of ECI. Brain Injury Guidelines category was not associated with ECI in pediatric patients. LEVEL OF EVIDENCE: Prognostic study, Level III.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".