Diagnostic Peritoneal Lavage – A Lost Art? A Retrospective Observational Study at a Canadian Tertiary Trauma Centre
Bibliographic record
Abstract
INTRODUCTION: Abdominal trauma is a leading cause of morbidity and mortality in the young, adult patient in North America. The standard tools to assess the severity of abdominal trauma have been evolving. The continuing role of diagnostic peritoneal lavage (DPL) as a clinical tool to evaluate intra-abdominal injury today remains controversial. This study investigated trends in the use of DPL, CT (computerized tomography) and FAST (Focused Assessment with Sonography for Trauma) in trauma patients in the province of Nova Scotia’s single adult tertiary trauma centre. METHODS: We conducted a retrospective analysis of all patients over the age of 15 with severe blunt and/or penetrating abdominal trauma from 1996 to 2001 who presented to a tertiary care hospital in Nova Scotia. Patients included in this study were those with an injury severity score (ISS) of ≥9 for penetrating trauma and ≥12 for blunt trauma and were derived from the Nova Scotia Trauma Registry. Descriptive statistics were utilized to determine trends over the six year period. RESULTS: Of 172 patients included in the final cohort, the majority were male and under the age of 50. Blunt abdominal injury was far more common than penetrating abdominal injury in this cohort. Abdominal CT, FAST, and DPL were performed in 43.6%, 19.8% and 0.6% of the patients respectively. Absolute numbers of CTs and ultrasounds performed for abdominal trauma increased; however, the percentage of patients receiving those investigations remained constant. DISCUSSION: Despite having excellent published test characteristics and extensive literature supporting its use, DPL is not commonly used today to assess blunt/penetrating abdominal injury in major trauma patients in Nova Scotia’s tertiary trauma centre. These trends may have implications for guideline formulation for care of the major trauma patient with suspected intra-abdominal injuries.
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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 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 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".