Predictors of Septic Shock or Bacteremia in Children Experiencing Febrile Neutropenia Post-Chemotherapy

Author:

Avilés-Robles Martha1,Schnur Jennifer J23,Dorantes-Acosta Elisa4,Márquez-González Horacio5,Ocampo-Ramírez Luis A1,Chawla Nitesh V23

Affiliation:

1. Department of Infectious Diseases, Hospital Infantil de México Federico Gómez , Mexico City , Mexico

2. Lucy Family Institute for Data and Society, University of Notre Dame , Notre Dame, Indiana , USA

3. Department of Computer Science and Engineering, University of Notre Dame , Notre Dame, Indiana , USA

4. Department of Oncology and Leukemia Cell Research Biobank, Hospital Infantil de México Federico Gómez , Mexico City , Mexico

5. Department of Clinical Research, Hospital Infantil de México Federico Gómez , Mexico City , Mexico

Abstract

Abstract Background Febrile neutropenia (FN) is an early indicator of infection in oncology patients post-chemotherapy. We aimed to determine clinical predictors of septic shock and/or bacteremia in pediatric cancer patients experiencing FN and to create a model that classifies patients as low-risk for these outcomes. Methods This is a retrospective analysis with clinical data of a cohort of pediatric oncology patients admitted during July 2015 to September 2017 with FN. One FN episode per patient was randomly selected. Statistical analyses include distribution analysis, hypothesis testing, and multivariate logistic regression to determine clinical feature association with outcomes. Results A total of 865 episodes of FN occurred in 429 subjects. In the 404 sampled episodes that were analyzed, 20.8% experienced outcomes of septic shock and/or bacteremia. Gram-negative bacteria count for 70% of bacteremias. Features with statistically significant influence in predicting these outcomes were hematological malignancy (P < .001), cancer relapse (P = .011), platelet count (P = .004), and age (P = .023). The multivariate logistic regression model achieves AUROC = 0.66 (95% CI 0.56–0.76). The optimal classification threshold achieves sensitivity = 0.96, specificity = 0.33, PPV = 0.40, and NPV = 0.95. Conclusions This model, based on simple clinical variables, can be used to identify patients at low-risk of septic shock and/or bacteremia. The model’s NPV of 95% satisfies the priority to avoid discharging patients at high-risk for adverse infection outcomes. The model will require further validation on a prospective population.

Funder

National Council of Science and Technology of Mexico

Consejo Nacional de Ciencia y Tecnología

Publisher

Oxford University Press (OUP)

Subject

Infectious Diseases,General Medicine,Pediatrics, Perinatology and Child Health

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