Intra-abdominal Free Fluid without Solid Organ Injury in Blunt Abdominal Trauma: An Indication for Laparotomy
Bibliographic record
Abstract
BACKGROUND: The optimal management of patients sustaining blunt abdominal trauma (BAT), in whom intra-abdominal free fluid but no solid organ injury is found on imaging, remains unclear. The purpose of this study was to determine the incidence and significance of this finding. METHODS: All patients presenting with suspected BAT to a provincial trauma center over a 30-month period were reviewed. A screening focused abdominal sonogram for trauma scan was obtained in every case. Stable patients with positive or indeterminate scans underwent computed tomographic scanning. Those with free fluid but without visible solid organ injury were studied. Radiologic interpretation, clinical management, and operative findings were analyzed. RESULTS: Twenty-eight of 1,367 patients (2%) met inclusion criteria. Twenty-one patients (75%) underwent exploratory laparotomy, which for 16 (76%) was therapeutic: bowel injuries were found in 10 patients, mesentery injuries in 6, and injuries to solid organs in 3. In five patients, laparotomy was nontherapeutic. Those with more than a trace of free fluid were significantly more likely to have a therapeutic procedure. Seven patients (25%) were observed, of whom two failed nonoperative management and underwent therapeutic laparotomies within 24 hours of admission for missed colon, splenic, and hepatic injuries. The presence of abdominal seat belt bruising or a Chance-type fracture in the study patients was associated with a 90% and 100% therapeutic laparotomy rate, respectively. Computed tomographic scan findings were variable and were not able to predict injury severity or need for surgery. CONCLUSION: The finding of more than trace amounts of free fluid in the absence of solid organ injury in BAT is often associated with clinically significant visceral injury. Early laparotomy is recommended for these patients.
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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 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 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".