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The DOI matches its Crossref record; 21 of the 21 references it cites were found in a registry or an index.

A Prediction Model for Recognizing Strangulated Small Bowel Obstruction

Open access
Huang, Xiaming, Fang, Guan, Lin, Jie, Xu, Keyu, Shi, Hongqi, Zhuang, Lei·2018·Gastroenterology Research and Practice

Abstract

Introduction. Early and accurate diagnosis of strangulated small bowel obstruction (SSBO) is difficult. This study aimed to devise a prediction model for predicting the risk of SSBO.Materials and Methods.A database of 417 patients who had clinical symptoms of intestinal obstruction confirmed by computed tomography (CT) were evaluated for inclusion in this study. Symptoms and laboratory and radiologic findings of these patients were collected after admission. These clinical factors were analyzed using logistic regression. A logistic regression model was applied to identify determinant variables and construct a clinical score that would predict SSBO.Results. Seventy-six patients were confirmed to have SSBO, 169 patients required surgery but had no evidence of intestinal ischemia, and 172 patients were successfully managed conservatively. In multivariate logistic regression analysis, body temperature ≥ 38.0°C, positive peritoneal irritation sign, white blood cell (WBC) count > 10.0 × 10^9/L, thick-walled small bowel ≥3 mm, and ascites were significantly associated with SSBO. A new prediction model with total scores ranging from 0 to 481 was developed with these five variables. The area under the curve (AUC) of the new prediction model was 0.935.Conclusions. Our prediction model is a good predictive model to evaluate the severity of SBO.

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Figures

Figure 1 Computed tomography scan of the abdomen showing a large quantity of ascites (black arrow) around the liver.
Figure 1 Computed tomography scan of the abdomen showing a large quantity of ascites (black arrow) around the liver.CC BY · PubMed Central
Figure 2 Receiver operating characteristic (ROC) curve for the prediction model. The area under the curve was 0.935 (95% CI, 0.900–0.969).
Figure 2 Receiver operating characteristic (ROC) curve for the prediction model. The area under the curve was 0.935 (95% CI, 0.900–0.969).CC BY · PubMed Central

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  1. 1988, The American Surgeon, 54, 565

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Metadata

Authors
Huang, X., Fang, G., Lin, J., Xu, K., Shi, H., & Zhuang, L.
Affiliations
  • First Affiliated Hospital of Wenzhou Medical University (CN)
  • Department of General Surgery, The First affiliated Hospital of Wenzhou Medical University, Wenzhou, China
Corresponding author
  • Shi, Hongqi
  • Zhuang, Lei
Venue
Gastroenterology Research and Practice
Publisher
Wiley
Published
2018
Volume
2018
Pages
1-7
ISSN
  • 1687-6121 (ISSN-L)
  • 1687-630X
OpenAlex
W2789980118
Cited by
45
References
21
Citations by year
2026: 4 · 2025: 4 · 2024: 8 · 2023: 6 · 2022: 8 · 2021: 10 · 2020: 5
FWCI
3.90
Type
journal article
Language
en
Open access
Locations
  • Gastroenterology Research and Practice (publishedVersion, cc-by)
  • Europe PMC (PubMed Central) (publishedVersion, cc-by)
  • PubMed Central (publishedVersion, cc-by)
  • PubMed (publishedVersion)
  • DOAJ (DOAJ: Directory of Open Access Journals) (submittedVersion, cc-by-sa)
Funders
Science and Technology Planning Project of Wenzhou (Y20160046)
Topics
  • Health Sciences › Medicine › Surgery › Intestinal and Peritoneal Adhesions
  • Health Sciences › Medicine › Surgery › Gastrointestinal disorders and treatments
  • Health Sciences › Medicine › Surgery › Intestinal Malrotation and Obstruction Disorders
Keywords
strangulated small bowel obstruction, prediction model, clinical risk score, intestinal obstruction, peritoneal irritation, ascites, fever, leukocytosis, intestinal ischemia, conservative treatment, surgical management

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CoChat. (2026). Citation check: A Prediction Model for Recognizing Strangulated Small Bowel Obstruction. https://app.cochat.ai/papers/10.1155/2018/7164648
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Huang, X., Fang, G., Lin, J., Xu, K., Shi, H., & Zhuang, L. (2018). A Prediction Model for Recognizing Strangulated Small Bowel Obstruction. Gastroenterology Research and Practice. https://doi.org/10.1155/2018/7164648

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