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Diagnostic nomogram for closed-loop small bowel obstruction requiring emergency surgery.

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Summary

This study developed a diagnostic model for closed-loop small bowel obstruction (CL-SBO) using clinical data, blood tests, and CT scans. The model accurately predicts CL-SBO, aiding surgical decisions for high-risk patients.

Keywords:
Bowel ischemiaComputed tomographyNomogramPredictive modelingSmall bowel obstruction

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Area of Science:

  • Gastroenterology
  • Radiology
  • Surgical Oncology

Background:

  • Small bowel obstruction (SBO) is a common surgical emergency.
  • Distinguishing closed-loop SBO (CL-SBO) from open-loop SBO (OL-SBO) is crucial for timely surgical intervention.
  • Accurate diagnostic tools for CL-SBO are needed to improve patient outcomes.

Purpose of the Study:

  • To develop and validate a diagnostic model for CL-SBO.
  • To integrate clinical, laboratory (D-dimers), and computed tomography (CT) findings.
  • To assess the predictive value of individual CT signs for CL-SBO.

Main Methods:

  • Retrospective review of 219 patients with SBO who underwent surgery.
  • Development of a diagnostic nomogram using univariate and stepwise regression analysis.
  • Internal validation (K-fold cross-validation, bootstrap) and external validation (Qingdao Central Hospital data).

Main Results:

  • The nomogram incorporated D-dimers, tenderness, beak sign, radial distribution, whirl sign, and ascites.
  • The model demonstrated good predictive performance with a Harrell's C statistic of 0.786 (internal) and 0.784 (external).
  • CT findings like radial distribution, U/C-shaped loop, and whirl sign showed high specificity but low sensitivity for CL-SBO.

Conclusions:

  • The developed nomogram is an effective tool for diagnosing CL-SBO.
  • High-risk patients identified by the model warrant consideration for surgery.
  • The study highlights the utility of combining clinical, laboratory, and imaging data for CL-SBO diagnosis.