Objectives:
1. Identify the core clinical and CT predictors of operative need in SBO including mesenteric edema, free fluid, closed-loop obstruction, lack of enhancement, and feces sign absence — and understand how these features have remained consistent across 15 years of research.
2. Compare major international SBO predictive models (Zielinski, Geneva Severity Score, STRISK, and NOFA) and describe how they inform real-time decision-making in North American acute care surgery.
3. Apply evidence-based algorithms, including the 2025 JTACS EGS pathway to structure SBO evaluation, integrate Water-Soluble Contrast studies, and avoid delayed surgery in high-risk patients.
4. Evaluate the long-term impact of operative vs. non-operative management with emphasis on recurrence risk, timing between episodes, and how to incorporate recurrence data into patient counseling.
5. Synthesize 15 years of evolving SBO literature into practical bedside strategies by balancing red-flag findings, risk-model guidance, and individualized clinical judgment to optimize outcomes.
STRISK and NOFA Calculator:
Prediction Models | Clinical Abdominal Surgery Helsinki
References
1. Geneva Clinical Severity Score
Wassmer, C. H., Guber, J., Zeindler, J., Meier, R. P. H., Ouaïssi, M., Ris, F., Morel, P., Didier, C., & Gkikas, I. (2023).
A new clinical severity score for the management of adhesive small bowel obstruction: A cohort study. International Journal of Surgery, 109, 262–270.
https://pubmed.ncbi.nlm.nih.gov/37026805/
2. STRISK & NOFA Predictive Models
Räty, S., Rinta-Kilpinen, E., Eklund, M., Turunen, N., Koskinen, I., Rasilainen, S., Korhonen, T., & Paajanen, H. (2025).
Development and external validation of prediction risk models for strangulation or non-operative treatment failure in small bowel obstruction: A multicenter prospective study. Surgery, 178(1), 45–56.
Prediction Models | Clinical Abdominal Surgery Helsinki
3. JTACS EGS Algorithm – Evidence-Based, Cost-Effective Management
Livingston, D. H., Wolfson, D., Cogbill, T. H., Rice, T. W., Patel, N.,
et al. (2025).
Evidence-based, cost-effe
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