The role of serotonin receptor alleles and environmental stressors in the development of post‐concussive symptoms after pediatric mild traumatic brain injury
Bibliographic record
Abstract
AIM: To determine whether post-injury depressive symptoms, and pre-injury major life stressors and genetic factors (HTR1A C(-1019)G alleles; rs6295) are more common in children with mild traumatic brain injury (mTBI) who develop postconcussion syndrome (PCS) symptoms compared with children with asymptomatic mTBI. METHOD: This was a cross-sectional study of 47 symptomatic children (32 males, 15 females; mean age 14y [SD 3y 3mo]) who experienced post-concussive symptoms for 7 or more days and 42 asymptomatic children (26 males 16 females; mean age 13y 6mo [SD 3y 1mo]) after mTBI. Outcome measures were the Postconcussion Symptoms Inventory (PCSI), the Children's Depression Inventory (CDI), standard questionnaire of previous life events, and buccal DNA analysis to determine genotype and allele frequencies for the HTR1A C(-1019)G polymorphism. RESULTS: Depressive symptoms were uncommon. CDI scores did not differ between groups. Allelic and genotypic frequencies for HTR1A C(-1019)G were similar in both groups. Symptomatic children continued to have elevated PCS scores compared with asymptomatic children 1.72 (SD 0.69) years later and had experienced significantly more life stressors (Wald (1)=8.51, p=0.004). INTERPRETATION: HTR1A polymorphisms do not differ in children with PCS. Children who have experienced more significant life stresses are more likely to develop PCS symptoms after mTBI.
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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 | 0.000 | 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 | 0.000 |
| 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".