Clinical and laboratory predictors for bacteremia in critically ill calves.
antimicrobial stewardship
biomarkers
blood culture
prediction model
sepsis
Journal
Journal of veterinary internal medicine
ISSN: 1939-1676
Titre abrégé: J Vet Intern Med
Pays: United States
ID NLM: 8708660
Informations de publication
Date de publication:
21 Oct 2024
21 Oct 2024
Historique:
received:
22
05
2024
accepted:
02
10
2024
medline:
21
10
2024
pubmed:
21
10
2024
entrez:
21
10
2024
Statut:
aheadofprint
Résumé
Sepsis is a main contributor to calf mortality, but diagnosis is difficult. Develop and validate a predictive model for bacteremia in critically ill calves (CIC). A total of 334 CIC, sampled for blood culture. Cross-sectional study. Multivariable logistic regression and classification tree analysis on clinical, ultrasonographic, and laboratory variables were performed on a dataset including all animals. Model validation was done on 30% of the dataset. Similar statistics (except validation) were performed on a subset of the database (n = 143), in which presumed contaminants were excluded. The best performing model to predict bacteremia, taking all detected bacteria into account, included tachypnea, tachycardia, acidemia, hypoglycemia, venous hypoxemia, and hypoproteinemia. Sensitivity and specificity of this model were 70.6% and 98.0%, respectively, but decreased to 61.5% and 91.7% during model validation. The best-performing model, excluding presumed contaminants, included abnormal temperature, heart rate, absence of enteritis, hypocalcemia, and hyperlactatemia as risk factors for bacteremia. Sensitivity and specificity of this model were 71.4% and 93.9%, respectively. Both classification trees performed less well in comparison to logistic regression. The classification tree excluding presumed contaminants, featured hypoglycemia, absence of diarrhea, and hyperlactatemia as risk factors for bacteremia. Sensitivity and specificity were 39.4% and 92.7%, respectively. Hypoglycemia, hyperlactatemia, and hypoproteinemia seem relevant in assessing bacteremia in CIC. The performance of these models based on basic clinical and blood variables remains insufficient to predict bacteremia.
Sections du résumé
BACKGROUND
BACKGROUND
Sepsis is a main contributor to calf mortality, but diagnosis is difficult.
OBJECTIVES
OBJECTIVE
Develop and validate a predictive model for bacteremia in critically ill calves (CIC).
ANIMALS
METHODS
A total of 334 CIC, sampled for blood culture.
METHODS
METHODS
Cross-sectional study. Multivariable logistic regression and classification tree analysis on clinical, ultrasonographic, and laboratory variables were performed on a dataset including all animals. Model validation was done on 30% of the dataset. Similar statistics (except validation) were performed on a subset of the database (n = 143), in which presumed contaminants were excluded.
RESULTS
RESULTS
The best performing model to predict bacteremia, taking all detected bacteria into account, included tachypnea, tachycardia, acidemia, hypoglycemia, venous hypoxemia, and hypoproteinemia. Sensitivity and specificity of this model were 70.6% and 98.0%, respectively, but decreased to 61.5% and 91.7% during model validation. The best-performing model, excluding presumed contaminants, included abnormal temperature, heart rate, absence of enteritis, hypocalcemia, and hyperlactatemia as risk factors for bacteremia. Sensitivity and specificity of this model were 71.4% and 93.9%, respectively. Both classification trees performed less well in comparison to logistic regression. The classification tree excluding presumed contaminants, featured hypoglycemia, absence of diarrhea, and hyperlactatemia as risk factors for bacteremia. Sensitivity and specificity were 39.4% and 92.7%, respectively.
CONCLUSIONS AND CLINICAL IMPORTANCE
CONCLUSIONS
Hypoglycemia, hyperlactatemia, and hypoproteinemia seem relevant in assessing bacteremia in CIC. The performance of these models based on basic clinical and blood variables remains insufficient to predict bacteremia.
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Subventions
Organisme : FOD Volksgezondheid, Veiligheid van de Voedselketen en Leefmilieu
ID : RF 21/6351 RATIOSEP
Informations de copyright
© 2024 The Author(s). Journal of Veterinary Internal Medicine published by Wiley Periodicals LLC on behalf of American College of Veterinary Internal Medicine.
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