The characteristics, management and outcomes of high- and low-grade renal injuries in paediatric trauma patients at a major trauma centre
Bibliographic record
Abstract
Introduction Children, given anatomical variations, are at increased risk of renal injury following trauma. The management of paediatric renal injuries has, similar to other solid organ injuries, largely shifted towards conservative management; however, hemodynamically unstable patients may still warrant surgical exploration or interventional techniques. The aim of this study is to describe the local incidence, demographics, morbidity and outcomes associated with high- and low-grade renal injury in a paediatric major trauma population. Method This was a 5-year retrospective review of trauma registry data and chart analysis of all paediatric renal injuries from major trauma at a North American level 1 paediatric trauma centre between January 2016–31 December 2020. Data was analysed using SPSS v27 with p < 0.05 considered significant. Results Of 1334 major trauma patients, 45 suffered a kidney injury (20 high-grade and 25 low-grade injuries), of which 93.3% underwent conservative management with no difference in outcomes between groups. 80% of patients had concurrent injuries (a quarter requiring surgery for these), with a trend towards higher rates of chest injuries in high-grade renal injury patients ( p = 0.08). Bicycle injuries were statistically more likely to cause high-grade renal injury ( p = 0.02). Angiography was utilized infrequently (3/45 patients, 6.6%), and no patients underwent embolization in our study population. Overall mortality (4.4%) and length of stay were unaffected by grade of injury. Conclusion Paediatric renal injury is an uncommon injury in major trauma patients (3.4%). Most cases can be managed conservatively regardless of the grade of injury. Renal injury patients are likely to have concurrent injuries, often requiring surgery. Further studies are needed to measure the success and utilization of interventional radiology techniques for management in children.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 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".