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Evaluation of a prognostic scoring system for dogs managed with hemodialysis.
- Source :
-
Journal of Veterinary Emergency & Critical Care . Jul2018, Vol. 28 Issue 4, p340-345. 6p. - Publication Year :
- 2018
-
Abstract
- Abstract: Objective: To investigate prognostic models in a cohort of dogs with acute kidney injury (AKI) and acute on chronic kidney disease (AKI/CKD) managed by hemodialysis. Design: Retrospective study from July 2011 to November 2014. Setting: University Veterinary Teaching Hospital. Animals: Forty dogs with historical, clinical, imaging, and laboratory findings consistent with AKI or AKI/CKD managed with intermittent hemodialysis were included. Interventions: Scoring system models previously established by Segev et al for outcome prediction in dogs with AKI were applied to all dogs. Results: Models A, B, and C correctly classified outcomes in 68%, 83%, and 85% of cases, respectively. In our cohort Model A showed sensitivity of 58% and specificity of 86%, Model B showed sensitivity of 79% and specificity of 87%, Model C showed sensitivity of 86% and specificity of 84%. The presence of anuria (P < 0.0002), respiratory complications (P < 0.0001), disseminated intravascular coagulation (DIC) (P = 0.0004), grade of AKI (P = 0.0023), pancreatitis (P = 0.0001), and systemic inflammatory response syndrome (SIRS) (P = 0.0001) was significantly higher in nonsurvivors compared with survivors. Conclusions: In our cohort of patients, Segev's model C showed the best sensitivity and specificity for predicting prognosis, while model A had lower sensitivity. In our cohort of dialysis patients, the presence of respiratory complications, DIC, SIRS, and pancreatitis at hospitalization, were correlated with a poor prognosis. [ABSTRACT FROM AUTHOR]
Details
- Language :
- English
- ISSN :
- 14793261
- Volume :
- 28
- Issue :
- 4
- Database :
- Academic Search Index
- Journal :
- Journal of Veterinary Emergency & Critical Care
- Publication Type :
- Academic Journal
- Accession number :
- 130628489
- Full Text :
- https://doi.org/10.1111/vec.12736