FREE SHIPPING over $40
OVER 10000 FIVE-STAR REVIEWS
5% OFF ALL SUBSCRIPTIONS
100% HAPPINESS GUARANTEE
Analyze Diet
0
Veterinary research communications2017; 42(1); 19-27; doi: 10.1007/s11259-017-9704-y

Development of a clinical prediction score for detection of suspected cases of equine grass sickness (dysautonomia) in France.

Abstract: Equine grass sickness (EGS) (equine dysautonomia) is a neurodegenerative condition of grazing equines. Pre-mortem diagnosis of EGS is a challenge for practitioners as definitive diagnosis requires ileal/myenteric lymph node biopsies. This study aimed to develop a clinical score that could be used by practitioners to improve the detection of acute or subacute EGS cases in the field. Suspected EGS cases were declared by veterinary practitioners. A case was classified as confirmed positive if ileal or rectal biopsy samples showed neuronal degeneration typical of EGS. A semi-quantitative scoring system, including epidemiological and clinical data, was created to attempt to classify suspected EGS horses into confirmed positive or negative cases. Each variable was weighted based on a boosted regression trees model, while taking into account its clinical relevance. Twenty-eight EGS cases were confirmed by biopsy during the entire study period. The best cut-off value for the score to have a high sensitivity while maximizing specificity was 8, with a sensitivity of 100% and a specificity of 53%. In our dataset, 77% of animals would be correctly classified with this cut-off value of 8. Highest sensitivity was chosen in order to detect the highest number of potential cases. Our score represents an inexpensive and useful tool to aid in the identification of suspected EGS cases in the field and selection for further diagnostics procedures to confirm or rule out the disease. Application of the score to larger populations of animals would be required to further adapt and refine the score.
Get Full Text
Publication Date: 2017-12-04 PubMed ID: 29204821DOI: 10.1007/s11259-017-9704-yGoogle Scholar: Lookup
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.

The research aims at developing a scoring system to detect cases of Equine Grass Sickness (EGS) minimizing the need for invasive diagnostic procedures like biopsies. The scoring system uses factors like epidemiological and clinical data, and it has proven effective with a 100% sensitivity and a specificity of 53%.

Background on Equine Grass Sickness (EGS)

  • This study focuses on a condition known as Equine Grass Sickness (EGS), also referred to as equine dysautonomia, which is a degenerative disease that affects the nervous system of horses that graze.
  • Diagnosing EGS pre-mortem typically requires invasive procedures like ileal or rectal biopsies, making it challenging for practitioners to confirm the disease.

Methodology

  • The researchers sought to develop a semi-quantitative scoring system to classify suspected EGS horses into confirmed cases (positive or negative).
  • A case was considered confirmed if ileal or rectal biopsies showed signs of the neurodegeneration typical of EGS.
  • The score considered epidemiological factors and clinical data and each variable was weighted according to a boosted regression trees model while considering its clinical relevance.

Results

  • The score was tested on suspected EGS cases; a total of 28 cases were confirmed to be EGS during the study period.
  • Researchers found that a cut-off value of 8 for the score provided the best balance between sensitivity (100%) and specificity (53%).
  • With this cut-off value, 77% of the animals in the dataset were correctly classified.

Implications and Future Research

  • The developed score is seen as a valuable tool to aid in identifying suspected EGS cases in the field, therefore minimizing the need for invasive diagnostic procedures.
  • However, the researchers note that further study would need to be done using larger animal populations to fine-tune the scoring system.
  • The researchers also note that this scoring approach prioritizes sensitivity (identifying as many potential positive cases as possible) over specificity (accurately identifying negative cases).

Cite This Article

APA
Randleff-Rasmussen PK, Leblond A, Cappelle J, Bontemps J, Belluco S, Popoff MR, Marcillaud-Pitel C, Tapprest J, Tritz P, Desjardins I. (2017). Development of a clinical prediction score for detection of suspected cases of equine grass sickness (dysautonomia) in France. Vet Res Commun, 42(1), 19-27. https://doi.org/10.1007/s11259-017-9704-y

Publication

Veterinary research communications
ISSN: 1573-7446
NlmUniqueID: 8100520
Country: Switzerland
Language: English
Volume: 42
Issue: 1
Pages: 19-27

Researcher Affiliations

Randleff-Rasmussen, P K
  • Equine Clinic, University of Lyon, VetAgroSup, Marcy L'Etoile, France. pia.randleff-rasmussen@vetagro-sup.fr.
Leblond, A
  • Equine Clinic, University of Lyon, VetAgroSup, Marcy L'Etoile, France.
  • UMR EPIA, INRA, VetAgro Sup, 69280, Marcy l'étoile, France.
  • Réseau d'Epidémio-Surveillance en Pathologie Equine (RESPE), Saint-Contest, France.
Cappelle, J
  • UMR EPIA, INRA, VetAgro Sup, 69280, Marcy l'étoile, France.
  • UMR ASTRE, CIRAD, INRA, 34398, Montpellier, France.
Bontemps, J
  • Equine Clinic, University of Lyon, VetAgroSup, Marcy L'Etoile, France.
Belluco, S
  • Laboratoire d'Histopathologie, University of Lyon, VetAgroSup, Marcy L'Etoile, France.
Popoff, M R
  • Anaerobic Bacteria and Toxins, Pasteur Institute, Paris, France.
Marcillaud-Pitel, C
  • Réseau d'Epidémio-Surveillance en Pathologie Equine (RESPE), Saint-Contest, France.
Tapprest, J
  • Laboratory for Equine Diseases, French Agency for Food, Environmental and Occupational Health & Safety (Anses), Goustranville, France.
Tritz, P
  • Réseau d'Epidémio-Surveillance en Pathologie Equine (RESPE), Saint-Contest, France.
  • Commission Maladies Infectieuses et Epidémiologie AVEF, Paris, France.
  • Clinique Vétérinaire, Faulquemont, France.
Desjardins, I
  • Equine Clinic, University of Lyon, VetAgroSup, Marcy L'Etoile, France.

MeSH Terms

  • Animals
  • Horse Diseases / diagnosis
  • Horses
  • Primary Dysautonomias / diagnosis
  • Primary Dysautonomias / veterinary
  • Sensitivity and Specificity
  • Veterinary Medicine / methods

References

This article includes 25 references
  1. Mair TS, Kelley AM, Pearson GR. Comparison of ileal and rectal biopsies in the diagnosis of equine grass sickness.. Vet Rec 2011 Mar 12;168(10):266.
    pubmed: 21498179doi: 10.1136/vr.c6349google scholar: lookup
  2. Hahn CN, Mayhew IG. Phenylephrine eyedrops as a diagnostic test in equine grass sickness.. Vet Rec 2000 Nov 18;147(21):603-6.
    pubmed: 11110481doi: 10.1136/vr.147.21.603google scholar: lookup
  3. McCarthy HE, Proudman CJ, French NP. Epidemiology of equine grass sickness: a literature review (1909-1999).. Vet Rec 2001 Sep 8;149(10):293-300.
    pubmed: 11570789doi: 10.1136/vr.149.10.293google scholar: lookup
  4. Wylie CE, Proudman CJ, McGorum BC, Newton JR. A nationwide surveillance scheme for equine grass sickness in Great Britain: results for the period 2000-2009.. Equine Vet J 2011 Sep;43(5):571-9.
    pubmed: 21649713doi: 10.1111/j.2042-3306.2011.00364.xgoogle scholar: lookup
  5. Hedderson EJ, Newton JR. Prospects for vaccination against equine grass sickness.. Equine Vet J 2004 Mar;36(2):186-91.
    pubmed: 15038444doi: 10.2746/0425164044868710google scholar: lookup
  6. Bracamonte JL, Bouré LP, Geor RJ, Runciman JR, Nykamp SG, Cruz AM, Teeter MG, Waterfall HL. Evaluation of a laparoscopic technique for collection of serial full-thickness small intestinal biopsy specimens in standing sedated horses.. Am J Vet Res 2008 Mar;69(3):431-9.
    pubmed: 18312145doi: 10.2460/ajvr.69.3.431google scholar: lookup
  7. Doxey DL, Gilmour JS, Milne EM. A comparative study of normal equine populations and those with grass sickness (dysautonomia) in eastern Scotland.. Equine Vet J 1991 Sep;23(5):365-9.
    pubmed: 1959528doi: 10.1111/j.2042-3306.1991.tb03739.xgoogle scholar: lookup
  8. Wales AD, Whitwell KE. Potential role of multiple rectal biopsies in the diagnosis of equine grass sickness.. Vet Rec 2006 Mar 18;158(11):372-7.
    pubmed: 16547184doi: 10.1136/vr.158.11.372google scholar: lookup
  9. Laupacis A, Sekar N, Stiell IG. Clinical prediction rules. A review and suggested modifications of methodological standards.. JAMA 1997 Feb 12;277(6):488-94.
    pubmed: 9020274
  10. Gilmour JS, Jolly GM. Some aspects of the epidemiology of equine grass sickness.. Vet Rec 1974 Jul 27;95(4):77-81.
    pubmed: 4439627doi: 10.1136/vr.95.4.77google scholar: lookup
  11. Milne EM, Pirie RS, McGorum BC, Shaw DJ. Evaluation of formalin-fixed ileum as the optimum method to diagnose equine dysautonomia (grass sickness) in simulated intestinal biopsies.. J Vet Diagn Invest 2010 Mar;22(2):248-52.
    pubmed: 20224086doi: 10.1177/104063871002200214google scholar: lookup
  12. Elith J, Leathwick JR, Hastie T. A working guide to boosted regression trees.. J Anim Ecol 2008 Jul;77(4):802-13.
    pubmed: 18397250doi: 10.1111/j.1365-2656.2008.01390.xgoogle scholar: lookup
  13. Scholes SF, Vaillant C, Peacock P, Edwards GB, Kelly DF. Diagnosis of grass sickness by ileal biopsy.. Vet Rec 1993 Jul 3;133(1):7-10.
    pubmed: 8362491doi: 10.1136/vr.133.1.7google scholar: lookup
  14. Hunter LC, Miller JK, Poxton IR. The association of Clostridium botulinum type C with equine grass sickness: a toxicoinfection?. Equine Vet J 1999 Nov;31(6):492-9.
    pubmed: 10596931doi: 10.1111/j.2042-3306.1999.tb03857.xgoogle scholar: lookup
  15. Newton JR, Hedderson EJ, Adams VJ, McGorum BC, Proudman CJ, Wood JL. An epidemiological study of risk factors associated with the recurrence of equine grass sickness (dysautonomia) on previously affected premises.. Equine Vet J 2004 Mar;36(2):105-12.
    pubmed: 15038431doi: 10.2746/0425164044868639google scholar: lookup
  16. Jago RC, Handel I, Hahn CN, Pirie RS, Keen JA, Waggett BE, McGorum BC. Bodyweight change aids prediction of survival in chronic equine grass sickness.. Equine Vet J 2016 Nov;48(6):792-797.
    pubmed: 26701780doi: 10.1111/evj.12551google scholar: lookup
  17. McGorum BC, Pirie RS, Shaw D, Macintyre N, Cox A. Neuronal chromatolysis in the subgemmal plexus of gustatory papillae in horses with grass sickness.. Equine Vet J 2016 Nov;48(6):773-778.
    pubmed: 26518231doi: 10.1111/evj.12530google scholar: lookup
  18. Pirie RS, McGorum BC. Equine grass sickness: Benefits of a multifaceted research approach.. Equine Vet J 2016 Nov;48(6):770-772.
    pubmed: 27723120doi: 10.1111/evj.12628google scholar: lookup
  19. Wood JL, Milne EM, Doxey DL. A case-control study of grass sickness (equine dysautonomia) in the United Kingdom.. Vet J 1998 Jul;156(1):7-14.
    pubmed: 9691846doi: 10.1016/s1090-0233(98)80055-5google scholar: lookup
  20. Pirie RS, Jago RC, Hudson NP. Equine grass sickness.. Equine Vet J 2014 Sep;46(5):545-53.
    pubmed: 24580639doi: 10.1111/evj.12254google scholar: lookup
  21. Ireland JL, McGorum BC, Proudman CJ, Newton JR. Designing a field trial of an equine grass sickness vaccine: A questionnaire-based feasibility study.. Vet J 2016 Jul;213:64-71.
    pubmed: 27240918doi: 10.1016/j.tvjl.2016.05.001google scholar: lookup
  22. Wylie CE, Proudman CJ. Equine grass sickness: epidemiology, diagnosis, and global distribution.. Vet Clin North Am Equine Pract 2009 Aug;25(2):381-99.
    pubmed: 19580947doi: 10.1016/j.cveq.2009.04.006google scholar: lookup
  23. Gilmour JS, Brown R, Johnson P. A negative serological relationship between cases of grass sickness in Scotland and Clostridium perfringens type A enterotoxin.. Equine Vet J 1981 Jan;13(1):56-8.
    pubmed: 6263613doi: 10.1111/j.2042-3306.1981.tb03453.xgoogle scholar: lookup
  24. Doxey DL, Milne EM, Ellison J, Curry PJ. Long-term prospects for horses with grass sickness (dysautonomia).. Vet Rec 1998 Feb 28;142(9):207-9.
    pubmed: 9533290doi: 10.1136/vr.142.9.207google scholar: lookup
  25. McCarthy HE, French NP, Edwards GB, Miller K, Proudman CJ. Why are certain premises at increased risk of equine grass sickness? A matched case-control study.. Equine Vet J 2004 Mar;36(2):130-4.
    pubmed: 15038435doi: 10.2746/0425164044868594google scholar: lookup

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. Laus F, Corsalini J, Mandara MT, Bazzano M, Bertoletti A, Gialletti R. Equine grass sickness in italy: a case series study. BMC Vet Res 2021 Aug 6;17(1):264.
    doi: 10.1186/s12917-021-02966-ypubmed: 34362361google scholar: lookup
  3. Harte T, Smith D, Moore J, Wells B. Review of published research on primary dysautonomia of domestic animals. Vet Rec 2026 Jan 3;198(1):e30-e40.
    doi: 10.1002/vetr.5499pubmed: 40482055google scholar: lookup
Subscribe to our newsletter
Join 99,780 horse owners like you who receive our email updates on horse health and nutrition.