Spinal Cord Injury in the Pediatric Population: A Systematic Review of the Literature
Bibliographic record
Abstract
Spinal Cord Injury (SCI) in the pediatric population is relatively rare but carries significant psychological and physiological consequences. An interdisciplinary group of experts composed of medical and surgical specialists treating patients with SCI formulated the following questions: 1) What is the epidemiology of pediatric spinal cord injury and fractures?; 2) Are there unique features of pediatric SCI which distinguish the pediatric SCI population from adult SCI?; 3) Is there evidence to support the use of neuroprotective approaches, including hypothermia and steroids, in the treatment of pediatric SCI? A systematic review of the literature using multiple databases was undertaken to evaluate these three specific questions. A search strategy composed of specific search terms (Spinal Cord Injury, Paraplegia, Quadriplegia, tetraplegia, lapbelt injuries, seatbelt injuries, cervical spine injuries and Pediatrics) returned over 220 abstracts that were evaluated and by two observers. Relevant abstracts were then evaluated and papers were graded using the Downs and Black method. A table of evidence was then presented to a panel of experts using a modified Delphi approach and the following recommendation was then formulated using a consensus approach: Pediatric patients with traumatic SCI have different mechanisms of injury and have a better neurological recovery potential when compared to adults. Patients with SCI before their adolescent growth spurt have a high likelihood of developing scoliosis. Because of these differences, traumatic SCI should be highly suspected in the presence of abnormal neck or neurological exam, a high-risk mechanism of injury or a distracting injury even in the absence of radiological anomaly.
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 | 0.006 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.004 |
| Bibliometrics | 0.016 | 0.020 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".