A computer-derived protocol using recursive partitioning to aid in estimating prognosis of horses with abdominal pain in referral hospitals.
Abstract: In order to determine which variables are useful and accurate in estimating prognosis in horses with abdominal pain, data were analyzed from 231 horses presented at a veterinary teaching hospital. Using multiple stepwise discriminant analysis in a recursive partition model, we obtained a decision protocol that identified survivors and nonsurvivors. The prevalence of survivors was 61% in this population. The sensitivity, specificity, and positive and negative predictive values of this model were 71, 83, 87 and 65%, respectively. This decision protocol was validated by Jackknife classification and also by evaluation with a referral population of 100 horses in which the prevalence of survivors was 83%. This led to sensitivity, specificity, and positive and negative predictive values of 83, 78, 94 and 50%, respectively.
Publication Date: 1990-06-01 PubMed ID: 2199007PubMed Central: PMC1255672
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- Journal Article
- Research Support
- Non-U.S. Gov't
- Abdominal
- Clinical Pathology
- Clinical Study
- Colic
- Diagnosis
- Disease Diagnosis
- Disease Management
- Disease Treatment
- Emergency Care
- Equine Health
- Horses
- Hospitalization
- Pain Management
- Predictive Model
- Prognosis
- Regression Analysis
- Statistical Analysis
- Veterinary Care
- Veterinary Medicine
- Veterinary Practice
- Veterinary Research
Summary
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This research article focuses on developing a computer-derived protocol to predict the prognosis of horses suffering from abdominal pain using a statistical method called recursive partitioning.
Overview of the Study
- The study involved collecting data from 231 horses that were presented with abdominal pain at a veterinary teaching hospital.
- The main goal was to identify variables that are accurate and useful in estimating the prognosis of these horses.
- The method used for data analysis was multiple stepwise discriminant analysis in a recursive partition model.
Creation of the Decision Protocol
- Through the analysis, a decision protocol was developed that could distinguish between surviving and non-surviving horses.
- In this given population, 61% were survivors.
- The level of accuracy of this model was calculated using statistical measures such as sensitivity, specificity, and positive and negative predictive values, which were found to be 71%, 83%, 87%, and 65% respectively.
Validation of the Decision Protocol
- The decision protocol was validated using two different methods. The first was Jackknife classification, a method that tests the robustness of the model by leaving out one observation at a time and determining the effect on the overall model.
- The second validation method involved testing the decision protocol on a referral population of 100 horses. Here, the prevalence of survivors was higher, at 83%.
- Using this population, the sensitivity, specificity, and positive and negative predictive values of the model were determined to be 83%, 78%, 94%, and 50% respectively.
Conclusion
- The article concludes with the successful development and validation of a decision protocol based on recursive partitioning.
- This model can be used to predict the prognosis of horses presented with abdominal pain in veterinary hospitals, contributing to effective decision-making and management of these cases.
Cite This Article
APA
Pascoe PJ, Ducharme NG, Ducharme GR, Lumsden JH.
(1990).
A computer-derived protocol using recursive partitioning to aid in estimating prognosis of horses with abdominal pain in referral hospitals.
Can J Vet Res, 54(3), 373-378.
Publication
Researcher Affiliations
- Department of Clinical Studies, Ontario Veterinary College, University of Guelph.
MeSH Terms
- Abdominal Pain / diagnosis
- Abdominal Pain / mortality
- Abdominal Pain / veterinary
- Algorithms
- Animals
- Diagnosis, Computer-Assisted / veterinary
- Discriminant Analysis
- Hematocrit / veterinary
- Horse Diseases / diagnosis
- Horse Diseases / mortality
- Horses
- Predictive Value of Tests
- Prognosis
References
This article includes 21 references
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Citations
This article has been cited 3 times.- Cummings CO, Krucik DDR, Price E. Clinical predictive models in equine medicine: A systematic review.. Equine Vet J 2023 Jul;55(4):573-583.
- Bishop RC, Gutierrez-Nibeyro SD, Stewart MC, McCoy AM. Performance of predictive models of survival in horses undergoing emergency exploratory laparotomy for colic.. Vet Surg 2022 Aug;51(6):891-902.
- Ihler CF, Venger JL, Skjerve E. Evaluation of clinical and laboratory variables as prognostic indicators in hospitalised gastrointestinal colic horses.. Acta Vet Scand 2004;45(1-2):109-18.
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