Office management of mild head injury in children and adolescents.
Bibliographic record
Abstract
OBJECTIVE: To provide family physicians with updated, practical, evidence-based information about mild head injury (MHI) and concussion in the pediatric population. SOURCES OF INFORMATION: MEDLINE (1950 to February 2013), the Cochrane Database of Systematic Reviews (2005 to 2013), the Cochrane Central Register of Controlled Trials (2005 to 2013), and DARE (2005 to 2013) were searched using terms relevant to concussion and head trauma. Guidelines, position statements, articles, and original research relevant to MHI were selected. MAIN MESSAGE: Trauma is the main cause of death in children older than 1 year of age, and within this group head trauma is the leading cause of disability and death. Nine percent of reported athletic injuries in high school students involve MHI. Family physicians need to take a focused history, perform physical and neurologic examinations, use standardized evaluation instruments (Glasgow Coma Scale; the Sport Concussion Assessment Tool, version 3; the child version of the Sport Concussion Assessment Tool; and the Balance Error Scoring System), instruct parents how to monitor their children, decide when caregivers are not an appropriately responsible resource, follow up with patients promptly, guide a safe return to play and to learning, and decide when neuropsychological testing for longer-term follow-up is required. CONCLUSION: A thorough history, physical and neurologic assessment, the use of validated tools to provide an objective framework, and periodic follow-up are the basis of family physician management of pediatric MHI.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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".