Computed tomography features associated with operative management for nonstrangulating small bowel obstruction
Bibliographic record
Abstract
BACKGROUND: The management of nonstrangulating small bowel obstruction (SBO) may require surgery, but the need for and timing of surgical intervention isn't always apparent. We sought to determine whether specific features on computed tomography (CT) can predict the necessity for operative management. METHODS: Two radiologists independently reviewed CT scans from all patients admitted to hospital with SBO between 2004 and 2006. We examined the association between radiographic features and operative management by univariate analysis using the χ(2) or Fisher exact test. Significant factors with high concordance between radiologists were entered into a multivariable stepwise logistic regression model. RESULTS: There were 228 patients with SBO, 63 of whom met our inclusion criteria and had CT scans available for review. Three CT features were frequently associated with operative management and had good concordance between radiologists: complete bowel obstruction, small bowel dilation greater than 4 cm and transition point. Transition point was the only significant factor predictive of operative management for SBO on multivariable logistic regression analysis (OR 19, 95% confidence interval 1.8-201, p = 0.014). CONCLUSION: In patients with nonstrangulating SBO, the presence of a transition point on CT scan should alert the surgeon to the increased likelihood that operative management may be required.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".