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Canadian journal of veterinary research = Revue canadienne de recherche veterinaire2003; 67(1); 20-29;

Diagnostic decision rule for support in clinical assessment of the need for surgical intervention in horses with acute abdominal pain.

Abstract: A prospective survey of horses with colic referred to a university hospital was undertaken to elaborate on a simple clinical decision support system capable of predicting whether or not horses require surgical intervention. Cases were classified as requiring surgical intervention or not on the basis of intraoperative findings or necropsy reports. Logistic regression analysis was applied to identify predictors with the strongest association with treatment needed. The classification and regression tree (CART) methodology was used to combine the variables in a simple classification system. The performance of the elaborated algorithms, as diagnostic instruments, was recorded as test sensitivity and specificity. The CART method generated 5 different classification trees with a similar basic structure consisting of: degree of pain, peritoneal fluid colour, and rectal temperature. The tree, constructed at a prevalence of 15% surgical cases, appeared to be the best proposal made by CART. In this classification tree, further discrimination of cases was obtained by including the findings of rectal examination and packed cell volume. When regarded as a test system, the sensitivity and specificity was 52% and 95%, respectively, corresponding to positive and negative predictive values of 68% and 91%. The variables examined in the present study did not provide a safe clinical decision rule. The classification tree constructed at 15% surgical cases was considered feasible, the proportion of horses incorrectly predicted to be without need of immediate surgery (false negatives) was small, whereas the proportion of horses incorrectly predicted to be in need of immediate surgery (false positives) was large. Some of the false positive horses were amenable to surgical treatment, although these cases did not conform to the strict definition of a surgical case. A less rigorous definition of a surgical case than that used in the present study would lower the percentage of false positives.
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Publication Date: 2003-01-17 PubMed ID: 12528825PubMed Central: PMC227023
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  • Journal Article

Summary

This research summary has been generated with artificial intelligence and may contain errors and omissions. Refer to the original study to confirm details provided. Submit correction.

The research article discusses a study that aimed to develop a simple clinical decision support system to predict whether horses suffering from acute abdominal pain, or colic, require surgical intervention. It centered on analysis of intraoperative findings, necropsy reports and logistic regression to identify predictors for surgical need. The best results were achieved at a 15% prevalence of surgical cases, but some false positives and negatives were observed.

Objective and Methodology

  • The objective of the research was to create a practical, easy-to-use clinical decision support system for predicting the necessity of surgical intervention in cases of horses with acute abdominal pain.
  • A prospective survey of horses suffering from colic referred to a university hospital was conducted for this research.
  • The cases were categorized into two groups based on their requirement for surgical intervention. This categorization was determined through intraoperative findings or necropsy reports.
  • Logistic regression analysis was used to identify the predictors with the strongest association with the need for treatment. These predictors were then combined using the Classification and Regression Tree (CART) methodology to create a simple classification system.

Results and Analysis

  • The CART methodology helped establish five different classification trees, all with a similar underlying structure that included factors like degree of pain, the colour of peritoneal fluid, and rectal temperature.
  • Among these, the tree constructed at a prevalence of 15% surgical cases was found to be the most effective.
  • This most effective tree further improved upon classification accuracy by considering additional factors such as findings of rectal examination and packed cell volume.
  • As a test system, the sensitivity was 52% and the specificity was 95%, corresponding to positive and negative predictive values of 68% and 91% respectively.

Limitations and Conclusions

  • Despite the promising results, the variables tested in this study failed to produce a completely reliable clinical decision rule.
  • The proportion of horses incorrectly predicted as not needing immediate surgery (false negatives) was small, while the number of horses incorrectly predicted as needing immediate surgery (false positives) was large.
  • However, it is worth noting that some of the false positive horses were still responsive to surgical treatment, even though they didn’t strictly fall under the definition of a surgical case.
  • The strict definition of a surgical case used in this study could be a factor contributing to the high number of false positives and a less rigorous definition might decrease this percentage.

Cite This Article

APA
Thoefner MB, Ersbøll BK, Jansson N, Hesselholt M. (2003). Diagnostic decision rule for support in clinical assessment of the need for surgical intervention in horses with acute abdominal pain. Can J Vet Res, 67(1), 20-29.

Publication

Canadian journal of veterinary research = Revue canadienne de recherche veterinaire
ISSN: 0830-9000
NlmUniqueID: 8607793
Country: Canada
Language: English
Volume: 67
Issue: 1
Pages: 20-29

Researcher Affiliations

Thoefner, Martin B
  • Department of Large Animal Surgery, Royal Veterinary and Agricultural University of Copenhagen, Bülowsvej 17, DK-1870 Frederiksberg C, Denmark. thoefner@post10.tele.dk
Ersbøll, Bjarne K
    Jansson, Nicolai
      Hesselholt, Michael

        MeSH Terms

        • Abdomen, Acute / diagnosis
        • Abdomen, Acute / pathology
        • Abdomen, Acute / surgery
        • Abdomen, Acute / veterinary
        • Acute Disease
        • Age Factors
        • Animals
        • Colic / diagnosis
        • Colic / surgery
        • Colic / veterinary
        • Decision Making
        • Decision Trees
        • Diagnosis, Differential
        • False Negative Reactions
        • False Positive Reactions
        • Female
        • Horse Diseases / diagnosis
        • Horse Diseases / pathology
        • Horse Diseases / surgery
        • Horses
        • Male
        • Predictive Value of Tests
        • Prospective Studies
        • Sensitivity and Specificity
        • Sex Factors

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        Citations

        This article has been cited 3 times.
        1. Cummings CO, Krucik DDR, Price E. Clinical predictive models in equine medicine: A systematic review. Equine Vet J 2023 Jul;55(4):573-583.
          doi: 10.1111/evj.13880pubmed: 36199162google scholar: lookup
        2. Kos VK, Kramaric P, Brloznik M. Packed cell volume and heart rate to predict medical and surgical cases and their short-term survival in horses with gastrointestinal-induced colic. Can Vet J 2022 Apr;63(4):365-372.
          pubmed: 35368402
        3. Hernández-Avalos I, Mota-Rojas D, Mendoza-Flores JE, Casas-Alvarado A, Flores-Padilla K, Miranda-Cortes AE, Torres-Bernal F, Gómez-Prado J, Mora-Medina P. Nociceptive pain and anxiety in equines: Physiological and behavioral alterations. Vet World 2021 Nov;14(11):2984-2995.
          doi: 10.14202/vetworld.2021.2984-2995pubmed: 35017848google scholar: lookup
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