What's the Incidence of Delayed Splenic Bleeding in Children After Blunt Trauma? An Institutional Experience and Review of the Literature
Bibliographic record
Abstract
BACKGROUND: The existence and incidence of delayed splenic bleeding (DSB) in children are controversial but the implications are significant. We sought to determine the incidence of DSB in children and to look for similarities between reported cases. METHODS: A retrospective cohort study of all children admitted from 1992 to 2006 to our level 1 pediatric trauma center with blunt splenic injuries to calculate the incidence of DSB. In addition, a systematic review of the literature was performed, looking for similarities between reported cases of DSB in children since 1980. RESULTS: Three hundred three children were admitted with blunt splenic injuries (mean age, 10 years +/- 4.5 years; boys 212 [70%]). Two hundred ninety-three (96%) were successfully managed nonoperatively. All-cause mortality was 20 of 303 (6.6%). We identified 1 of 303 (0.33%) children with DSB. The patient was a boy, aged 15 years. He presented 23 days after initial injury with DSB causing death. He had an uncomplicated admission after his initial grade IV injury. There have been 14 cases of DSB reported in the literature since 1980. Twelve (88%) were boys, with a mean age of 14 years +/- 4 years (with 11 of 14 (79%) being adolescent). The mean time to DSB was 10 days +/- 7 days. There were no similarities in mechanism, imaging characteristics, or presence of pseudoaneurysm between cases. CONCLUSION: DSB is exceedingly rare. Our institutional incidence is 1 of 303 (0.33%). The number and quality of reported cases is insufficient to draw conclusions on predisposing factors for DSB, however, most cases occur in adolescents.
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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 | 0.002 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 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".