Which pediatric blunt trauma patients do not require pelvic imaging?
Bibliographic record
Abstract
BACKGROUND: This study aimed to develop a tool in identifying traumatized children at low risk of pelvic fracture and to determine the sensitivity of this low-risk model for pelvic fractures. We hypothesized that the proportion of children without predictors with pelvic fracture is less than 1%. METHODS: This is a retrospective trauma registry analysis of previously healthy children 1 year to 17 years old presenting to the pediatric emergency department with blunt trauma. Postulated predictors of pelvic fracture on radiograph or computed tomography included pain/abnormal examination result of the pelvis/hip, femur deformity, hematuria, abdominal pain/tenderness, Glasgow Coma Scale (GCS) score of 13 or lower, and hemodynamic instability. We used multivariable logistic regression to identify independent predictors of fracture. RESULTS: Of 1,121 eligible patients (mean [SD] age, 8.5 [4.6] years), 87 (7.8%) had pelvic fracture. Independent predictors included pain/abnormal examination result of the pelvis/hip (odds ratio [OR], 16.7; 95% confidence interval [CI], 9.6-29.1), hematuria (OR, 6.6; 95% CI, 3.0-14.6), femoral deformity (OR, 5.9; 95% CI, 3.1-11.3), GCS score of 13 or lower (OR, 2.4; 95% CI, 1.3-4.3), and hemodynamic instability (OR, 3.4; 95% CI, 1.7-6.9). One of 590 children (0.2%; 95% CI, 0-0.5%) without predictors had pelvic fractures versus 86 (16.2%) of 531 in those with one or more predictors (OR, 119; 95% CI, 16.6-833). One of 87 children with pelvic fractures had no predictors (1.1%; 95% CI, 0-3%). When assuming a 100% radiography rate, this tool saves 53% pelvic radiographs. CONCLUSION: Children with multiple blunt trauma without pain/abnormal examination result of the pelvis/hip, femur deformity, hematuria, abdominal pain/tenderness, GCS score of 13 or lower, or hemodynamic instability constitute a low-risk population for pelvic fracture, with less than 0.5% risk rate. This population does not require routine pelvic imaging. LEVEL OF EVIDENCE: Therapeutic study, level IV.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".