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Validation of the Hospital for Sick Children Algorithm for Discriminating Bacteremia From Contaminants in Children With a Preliminary Positive Blood Culture.
Gravel, Jocelyn; Grandjean-Blanchet, Charlotte; Demean-Loghin, Alino; Noyon, Brandon; Ostrow, Olivia; Vallières, Émilie.
Afiliación
  • Gravel J; Department of Pediatric Emergency Medicine, CHU Sainte-Justine, Université de Montréal, Montréal, QC, Canada. Electronic address: Graveljocelyn@hotmail.com.
  • Grandjean-Blanchet C; Department of Pediatric Emergency Medicine, CHU Sainte-Justine, Université de Montréal, Montréal, QC, Canada.
  • Demean-Loghin A; Faculté de Médecine, Université de Montréal, Montréal, QC, Canada.
  • Noyon B; Faculté de Médecine, Université de Montréal, Montréal, QC, Canada.
  • Ostrow O; Department of Pediatric Emergency Medicine, The Hospital for Sick Children, University of Toronto, Toronto, ON, Canada.
  • Vallières É; Division of Microbiology, Department of Clinical Laboratory Medicine, CHU Sainte-Justine, Université de Montréal, Montréal, QC, Canada.
Ann Emerg Med ; 84(5): 490-499, 2024 Nov.
Article en En | MEDLINE | ID: mdl-38888530
ABSTRACT
STUDY

OBJECTIVE:

Children with positive blood cultures obtained in the emergency department (ED) prompt urgent actions due to the risk of bacteremia. This study aimed to validate the Hospital for Sick Children algorithm used for discriminating bacteremia from contaminants and identified variables associated with bacteremia in children with positive blood cultures.

METHODS:

We conducted a retrospective cohort study of all children with positive blood cultures from a tertiary care, pediatric ED between 2018 and 2022. A 2-step standardized approach defined true bacteremia as the primary outcome based on 1) the bacteria involved and 2) the clinical outcome assessed by 2 reviewers. We evaluated multiple independent variables. We used multiple logistic regression to analyze the association between independent variables and outcome.

RESULTS:

Among the 375,428 ED visits, 574 participants were identified, including 286 (49.8%; 95% confidence interval [CI] 45.8% to 53.9%) with bacteremia and 288 (50.2%; 95% CI 46.1% to 54.3%) with contaminants. The algorithm identified 364 children (63.4%) at high risk of bacteremia, 178 (31.0%) at medium risk, and 32 (5.6%) at low risk. The corresponding bacteremia proportions were 62%, 34%, and 0%, respectively, for a sensitivity of 100% and a specificity of 11%. Suspicion of osteoarticular infection (aOR=43.6; 95% CI 16.2 to 118), presence of internal hardware (aOR=24.9; 95% CI 7.2 to 83.5), and presence of Gram-negative bacteria or Gram-positive cocci in chains/pairs (aOR=21.7; 95% CI 11.7 to 40.3) were the most significant predictors of true bacteremia.

CONCLUSION:

The Hospital for Sick Children algorithm exhibits 100% sensitivity to detect children with bacteremia but demonstrated low specificity at 11%. We identified predictors to discriminate contaminants from bacteremia.
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Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Bacteriemia / Servicio de Urgencia en Hospital / Cultivo de Sangre Límite: Adolescent / Child / Child, preschool / Female / Humans / Infant / Male Idioma: En Revista: Ann Emerg Med Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos
Texto completo
Añadir a Mi BVS
Imprimir
XML
PubMed Links
Buscar en Google

Texto completo: 1 Colección: 01-internacional Base de datos: MEDLINE Asunto principal: Algoritmos / Bacteriemia / Servicio de Urgencia en Hospital / Cultivo de Sangre Límite: Adolescent / Child / Child, preschool / Female / Humans / Infant / Male Idioma: En Revista: Ann Emerg Med Año: 2024 Tipo del documento: Article Pais de publicación: Estados Unidos