Pediatric TBI: Direct admissions vs. secondary referrals to a hospital: A single‑center, retrospective study
Bibliographic record
Abstract
The present retrospective study was conducted in an aim to examine the differences between pediatric traumatic brain injury (TBI) cases referred to and those admitted directly to the hospital. For this purpose, pediatric patients who presented to a main trauma center with TBI between January, 2015 and December, 2019 were reviewed retrospectively, emphasizing whether they were admitted directly or referred from another center. Data collected included the demographic characteristics of the patients, as well as their presenting complaints and the cause of TBI. A total of 981 cases of pediatric TBI were admitted over the 5-year period. The average age of the patients was 58.1 months for the referred cases and almost 50 months for the patients directly admitted. The male sex accounted for 63.6% of all cases. The most common cause of injury was falling (63.5%). Nausea and vomiting were the most typical presenting symptoms, occurring more among the directly admitted cases (P-value ≤0.05). Mild TBI accounted for 85.3% of the cases, and the most common radiological diagnosis was skull fracture (37.4%) (P-value ≤0.004). The referred patients had a more extended hospital stay (P-value ≤0.001). On the whole, the present study identified 981 cases; the majority of these were direct admissions, and the majority of the severe cases were referred from other healthcare facilities. Further research is required on this topic as only a single hospital was covered herein, and patients were not followed-up after discharge. A multi-center analysis would cover a greater number of patients and would thus provide more substantial data on the topic.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".