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Development, evaluation and validation of a screening tool for late onset bacteremia in neonates – a pilot study

BACKGROUND: Clinical and laboratory parameters can aid in the early identification of neonates at risk for bacteremia before clinical deterioration occurs. However, current prediction models have poor diagnostic capabilities. The objective of this study was to develop, evaluate and validate a screen...

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Autores principales: Walker, Sandra A. N., Cormier, Melanie, Elligsen, Marion, Choudhury, Julie, Rolnitsky, Asaph, Findlater, Carla, Iaboni, Dolores
Formato: Online Artículo Texto
Lenguaje:English
Publicado: BioMed Central 2019
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651932/
https://www.ncbi.nlm.nih.gov/pubmed/31340780
http://dx.doi.org/10.1186/s12887-019-1633-1
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author Walker, Sandra A. N.
Cormier, Melanie
Elligsen, Marion
Choudhury, Julie
Rolnitsky, Asaph
Findlater, Carla
Iaboni, Dolores
author_facet Walker, Sandra A. N.
Cormier, Melanie
Elligsen, Marion
Choudhury, Julie
Rolnitsky, Asaph
Findlater, Carla
Iaboni, Dolores
author_sort Walker, Sandra A. N.
collection PubMed
description BACKGROUND: Clinical and laboratory parameters can aid in the early identification of neonates at risk for bacteremia before clinical deterioration occurs. However, current prediction models have poor diagnostic capabilities. The objective of this study was to develop, evaluate and validate a screening tool for late onset (> 72 h post admission) neonatal bacteremia using common laboratory and clinical parameters; and determine its predictive value in the identification of bacteremia. METHODS: A retrospective chart review of neonates admitted to a neonatal intensive care unit (NICU) between March 1, 2012 and January 14, 2015 and a prospective evaluation of all neonates admitted between January 15, 2015 and March 30, 2015 were completed. Neonates with late-onset bacteremia (> 72 h after NICU admission) were eligible for inclusion in the bacteremic cohort. Bacteremic patients were matched to non-infected controls on several demographic parameters. A Pearson’s Correlation matrix was completed to identify independent variables significantly associated with infection (p < 0.05, univariate analysis). Significant parameters were analyzed using iterative binary logistic regression to identify the simplest significant model (p < 0.05). The predictive value of the model was assessed and the optimal probability cut-off for bacteremia was determined using a Receiver Operating Characteristic curve. RESULTS: Maximum blood glucose, heart rate, neutrophils and bands were identified as the best predictors of bacteremia in a significant binary logistic regression model. The model’s sensitivity, specificity and accuracy were 90, 80 and 85%, respectively, with a false positive rate of 20% and a false negative rate of 9.7%. At the study bacteremia prevalence rate of 51%, the positive predictive value, negative predictive value and negative post-test probability were 82, 89 and 11%, respectively. CONCLUSION: The model developed in the current study is superior to currently published neonatal bacteremia screening tools. Validation of the tool in a historic data set of neonates from our institution will be completed. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12887-019-1633-1) contains supplementary material, which is available to authorized users.
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spelling pubmed-66519322019-07-31 Development, evaluation and validation of a screening tool for late onset bacteremia in neonates – a pilot study Walker, Sandra A. N. Cormier, Melanie Elligsen, Marion Choudhury, Julie Rolnitsky, Asaph Findlater, Carla Iaboni, Dolores BMC Pediatr Research Article BACKGROUND: Clinical and laboratory parameters can aid in the early identification of neonates at risk for bacteremia before clinical deterioration occurs. However, current prediction models have poor diagnostic capabilities. The objective of this study was to develop, evaluate and validate a screening tool for late onset (> 72 h post admission) neonatal bacteremia using common laboratory and clinical parameters; and determine its predictive value in the identification of bacteremia. METHODS: A retrospective chart review of neonates admitted to a neonatal intensive care unit (NICU) between March 1, 2012 and January 14, 2015 and a prospective evaluation of all neonates admitted between January 15, 2015 and March 30, 2015 were completed. Neonates with late-onset bacteremia (> 72 h after NICU admission) were eligible for inclusion in the bacteremic cohort. Bacteremic patients were matched to non-infected controls on several demographic parameters. A Pearson’s Correlation matrix was completed to identify independent variables significantly associated with infection (p < 0.05, univariate analysis). Significant parameters were analyzed using iterative binary logistic regression to identify the simplest significant model (p < 0.05). The predictive value of the model was assessed and the optimal probability cut-off for bacteremia was determined using a Receiver Operating Characteristic curve. RESULTS: Maximum blood glucose, heart rate, neutrophils and bands were identified as the best predictors of bacteremia in a significant binary logistic regression model. The model’s sensitivity, specificity and accuracy were 90, 80 and 85%, respectively, with a false positive rate of 20% and a false negative rate of 9.7%. At the study bacteremia prevalence rate of 51%, the positive predictive value, negative predictive value and negative post-test probability were 82, 89 and 11%, respectively. CONCLUSION: The model developed in the current study is superior to currently published neonatal bacteremia screening tools. Validation of the tool in a historic data set of neonates from our institution will be completed. ELECTRONIC SUPPLEMENTARY MATERIAL: The online version of this article (10.1186/s12887-019-1633-1) contains supplementary material, which is available to authorized users. BioMed Central 2019-07-24 /pmc/articles/PMC6651932/ /pubmed/31340780 http://dx.doi.org/10.1186/s12887-019-1633-1 Text en © The Author(s). 2019 Open AccessThis article is distributed under the terms of the Creative Commons Attribution 4.0 International License (http://creativecommons.org/licenses/by/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The Creative Commons Public Domain Dedication waiver (http://creativecommons.org/publicdomain/zero/1.0/) applies to the data made available in this article, unless otherwise stated.
spellingShingle Research Article
Walker, Sandra A. N.
Cormier, Melanie
Elligsen, Marion
Choudhury, Julie
Rolnitsky, Asaph
Findlater, Carla
Iaboni, Dolores
Development, evaluation and validation of a screening tool for late onset bacteremia in neonates – a pilot study
title Development, evaluation and validation of a screening tool for late onset bacteremia in neonates – a pilot study
title_full Development, evaluation and validation of a screening tool for late onset bacteremia in neonates – a pilot study
title_fullStr Development, evaluation and validation of a screening tool for late onset bacteremia in neonates – a pilot study
title_full_unstemmed Development, evaluation and validation of a screening tool for late onset bacteremia in neonates – a pilot study
title_short Development, evaluation and validation of a screening tool for late onset bacteremia in neonates – a pilot study
title_sort development, evaluation and validation of a screening tool for late onset bacteremia in neonates – a pilot study
topic Research Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC6651932/
https://www.ncbi.nlm.nih.gov/pubmed/31340780
http://dx.doi.org/10.1186/s12887-019-1633-1
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