FREE SHIPPING over $40
OVER 10000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Canadian journal of veterinary research = Revue canadienne de recherche veterinaire1989; 53(1); 87-94;

Prognosis in equine colic patients using multivariable analysis.

Abstract: Multiple logistic regression was used to investigate prognosis in 308 horses referred to the University of Minnesota veterinary teaching hospital with colic. Bivariate results identified the following significant individual parameters: absent or hypomotile abdominal sounds, medical or surgical classification, peritoneal fluid total protein, anion gap, serum glucose, capillary refill time, blood pH, heart rate, packed cell volume, base excess, serum chloride, plasma bicarbonate, serum urinary nitrogen and age. Two multivariable prognostic models were developed using logistic regression. Model I (based on 257 cases with a mortality rate of 39%) included age, sex, medical or surgical classification, capillary refill time, packed cell volume and heart rate. Model II (based on 138 cases with a mortality rate of 48%) included age, sex, medical or surgical classification, capillary refill time, serum bicarbonate, serum chloride and respiratory rate. Predictive performance of the models was evaluated by treating the calculated probability of death for each horse as a continuous test result. The influence of varying the probability cutoff point for death on test characteristics (sensitivity, specificity and positive and negative predictive values) was determined. These models have not been validated and thus their performance in a different population is uncertain.
Get Full Text
Publication Date: 1989-01-01 PubMed ID: 2914230PubMed Central: PMC1255520
The Equine Research Bank provides access to a large database of publicly available scientific literature. Inclusion in the Research Bank does not imply endorsement of study methods or findings by Mad Barn.
LinkedInCopy
  • 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.

This research sought to determine the prognosis of equine colic in horses referred to the University of Minnesota veterinary teaching hospital and developed two prognostic models based on a multiple of factors, though the overall effectiveness of these models is yet to be fully validated.

Study Methodology

  • The research used multiple logistic regression to analyze the prognosis of 308 horses with colic.
  • Several parameters were identified as significant in determining prognosis, including absent or hypomotile abdominal sounds, medical or surgical classification, peritoneal fluid total protein, anion gap, serum glucose, capillary refill time, blood pH, heart rate, packed cell volume, base excess, serum chloride, plasma bicarbonate, serum urinary nitrogen and age.
  • Two multivariable prognostic models were developed using logistic regression. The models relied on different parameters – age, sex, medical or surgical classification, capillary refill time, packed cell volume and heart rate for Model I; and age, sex, medical or surgical classification, capillary refill time, serum bicarbonate, serum chloride and respiratory rate for Model II.

Model Evaluation and Performance

  • The models’ performance was assessed by treating the calculated probability of death for each horse as a continuous test result. This allowed for continuous adjustment and refinement of the model.
  • The investigators also examined the influence of varying the probability cut off point for death on the test characteristics (sensitivity, specificity and positive and negative predictive values).
  • Model I was based on 257 cases with a mortality rate of 39%, while Model II was based on 138 cases with a higher mortality rate of 48%.

Limits of the Study and Future Considerations

  • The researchers note that these models have not been validated in other populations, and their performance remains uncertain when applied to different groups of horses.
  • It’s also important to mention that although these models included a broad range of parameters, not all possible factors influencing prognosis might have been considered. Future research is suggested to further refine these models and validate their efficacy across diverse settings.

Cite This Article

APA
Reeves MJ, Curtis CR, Salman MD, Hilbert BJ. (1989). Prognosis in equine colic patients using multivariable analysis. Can J Vet Res, 53(1), 87-94.

Publication

Canadian journal of veterinary research = Revue canadienne de recherche veterinaire
ISSN: 0830-9000
NlmUniqueID: 8607793
Country: Canada
Language: English
Volume: 53
Issue: 1
Pages: 87-94

Researcher Affiliations

Reeves, M J
  • Department of Clinical Sciences, College of Veterinary Medicine and Biomedical Sciences, Colorado State University, Fort Collins 80523.
Curtis, C R
    Salman, M D
      Hilbert, B J

        MeSH Terms

        • Animals
        • Colic / pathology
        • Colic / veterinary
        • Female
        • Horse Diseases / pathology
        • Horses
        • Male
        • Minnesota
        • Prognosis
        • Retrospective Studies

        References

        This article includes 22 references
        1. J S Afr Vet Assoc. 1975 Mar;46(1):127
          pubmed: 1177237
        2. J Am Vet Med Assoc. 1982 Jul 1;181(1):63-5
          pubmed: 7107490
        3. Equine Vet J. 1987 Jan;19(1):29-30
          pubmed: 3691457
        4. Aust Vet J. 1976 Mar;52(3):109-17
          pubmed: 985238
        5. Equine Vet J. 1986 Jul;18(4):271-4
          pubmed: 3758003
        6. Equine Vet J. 1986 Jul;18(4):275-7
          pubmed: 3758004
        7. J Am Vet Med Assoc. 1986 Feb 1;188(3):248-51
          pubmed: 3005202
        8. Am J Epidemiol. 1982 Jan;115(1):92-106
          pubmed: 7055134
        9. Vet Clin North Am Large Anim Pract. 1979 Nov;1(2):275-87
          pubmed: 552689
        10. Cornell Vet. 1980 Jul;70(3):232-46
          pubmed: 7428373
        11. Equine Vet J. 1986 Jul;18(4):264-70
          pubmed: 3758002
        12. J Am Vet Med Assoc. 1986 Oct 1;189(7):777-80
          pubmed: 3771338
        13. J Am Vet Med Assoc. 1981 Feb 15;178(4):396-8
          pubmed: 7240001
        14. J Am Vet Med Assoc. 1972 Dec 1;161(11):1195-8
          pubmed: 4565055
        15. J S Afr Vet Assoc. 1975 Mar;46(1):101-5
          pubmed: 240937
        16. Equine Vet J. 1976 Apr;8(2):49-54
          pubmed: 4300
        17. Equine Vet J. 1983 Jul;15(3):211-5
          pubmed: 6884310
        18. Equine Vet J. 1977 Oct;9(4):202-4
          pubmed: 923554
        19. Vet Med Small Anim Clin. 1970 Jul;65(7):669-73
          pubmed: 5200322
        20. Am J Epidemiol. 1986 Feb;123(2):203-8
          pubmed: 3946370
        21. Equine Vet J. 1983 Oct;15(4):337-44
          pubmed: 6641680
        22. Can Vet J. 1983 Mar;24(3):76-85
          pubmed: 17422234

        Citations

        This article has been cited 16 times.
        1. Macleod BM, Wilkins PA, McCoy AM, Bishop RC. Integration of machine learning and viscoelastic testing to improve survival prediction in horses experiencing acute abdominal pain at a veterinary teaching hospital. Equine Vet J 2026 Jan;58(1):105-114.
          doi: 10.1111/evj.14517pubmed: 40275538google scholar: lookup
        2. Milner PI, Bardell D. Can Arterial Blood Gas, Electrolyte and Acid-Base Analysis at Admission be Used to Predict Survival to Hospital Discharge for Different Causes of Colic?. Vet Med Sci 2025 Mar;11(2):e70210.
          doi: 10.1002/vms3.70210pubmed: 39912702google scholar: lookup
        3. Giraldo AF, Carballo R, Serrenho RC, Tran V, Valverde A, Renaud DL, Gomez DE. Association of the type of metabolic acidosis and non-survival of horses with colitis. Can Vet J 2023 Nov;64(11):1044-1050.
          pubmed: 37915775
        4. Ruff J, Zetterstrom S, Boone L, Hofmeister E, Smith C, Epstein K, Blikslager A, Fogle C, Burke M. Retrospective analysis of postoperative complications following surgical treatment of ileal impaction in horses managed with manual decompression compared to jejunal enterotomy. Front Vet Sci 2023;10:1156678.
          doi: 10.3389/fvets.2023.1156678pubmed: 37180077google scholar: lookup
        5. Straticò P, Varasano V, Palozzo A, Guerri G, Celani G, Revelant O, Petrizzi L. Retrospective Study on Risk Factors and Short-Term Outcome of Horses Referred for Colic from 2016 to 2022. Vet Sci 2022 Oct 3;9(10).
          doi: 10.3390/vetsci9100545pubmed: 36288158google scholar: lookup
        6. 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
        7. 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.
          doi: 10.1111/vsu.13839pubmed: 35674231google scholar: lookup
        8. 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
        9. Farrell A, Kersh K, Liepman R, Dembek KA. Development of a Colic Scoring System to Predict Outcome in Horses. Front Vet Sci 2021;8:697589.
          doi: 10.3389/fvets.2021.697589pubmed: 34692803google scholar: lookup
        10. Salem SE, Proudman CJ, Archer DC. Has intravenous lidocaine improved the outcome in horses following surgical management of small intestinal lesions in a UK hospital population?. BMC Vet Res 2016 Jul 27;12(1):157.
          doi: 10.1186/s12917-016-0784-7pubmed: 27459996google scholar: lookup
        11. Curtis L, Burford JH, Thomas JS, Curran ML, Bayes TC, England GC, Freeman SL. Prospective study of the primary evaluation of 1016 horses with clinical signs of abdominal pain by veterinary practitioners, and the differentiation of critical and non-critical cases. Acta Vet Scand 2015 Oct 6;57:69.
          doi: 10.1186/s13028-015-0160-9pubmed: 26444675google scholar: lookup
        12. Edner AH, Nyman GC, Essén-Gustavsson B. Metabolism before, during and after anaesthesia in colic and healthy horses. Acta Vet Scand 2007 Nov 15;49(1):34.
          doi: 10.1186/1751-0147-49-34pubmed: 18001483google scholar: lookup
        13. Staempfli HR, Townsend HG, Prescott JF. Prognostic features and clinical presentation of acute idiopathic enterocolitis in horses. Can Vet J 1991 Apr;32(4):232-7.
          pubmed: 17423769
        14. 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.
          doi: 10.1186/1751-0147-45-109pubmed: 15535091google scholar: lookup
        15. Nappert G, Johnson PJ. Determination of the acid-base status in 50 horses admitted with colic between December 1998 and May 1999. Can Vet J 2001 Sep;42(9):703-7.
          pubmed: 11565369
        16. Pascoe PJ, Ducharme NG, Ducharme GR, Lumsden JH. A computer-derived protocol using recursive partitioning to aid in estimating prognosis of horses with abdominal pain in referral hospitals. Can J Vet Res 1990 Jun;54(3):373-8.
          pubmed: 2199007
        Subscribe to our newsletter
        Join 99,727 horse owners like you who receive our email updates on horse health and nutrition.