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Published in: BMC Pediatrics 1/2019

Open Access 01-12-2019 | Research article

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

Authors: Sandra A. N. Walker, Melanie Cormier, Marion Elligsen, Julie Choudhury, Asaph Rolnitsky, Carla Findlater, Dolores Iaboni

Published in: BMC Pediatrics | Issue 1/2019

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Abstract

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.
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Literature
1.
go back to reference Plano LRW. The changing spectrum of neonatal infectious disease. J Perinatol. 2010;30:S16–20.CrossRef Plano LRW. The changing spectrum of neonatal infectious disease. J Perinatol. 2010;30:S16–20.CrossRef
2.
go back to reference Stoll BJ, Hansen N, Fanaroff AA, Wright LL, Carlo WA, Ehrenkranz RA, et al. Late-onset Sepsis in very low birth weight neonates: the experience of the NICHD neonatal research network. Pediatr. 2002;110(2):285–91.CrossRef Stoll BJ, Hansen N, Fanaroff AA, Wright LL, Carlo WA, Ehrenkranz RA, et al. Late-onset Sepsis in very low birth weight neonates: the experience of the NICHD neonatal research network. Pediatr. 2002;110(2):285–91.CrossRef
3.
go back to reference Wirtschafter DD, Padilla G, Wan K, Trupp D, Fayard EES. Antibiotic use for presumed neonatally acquired infections far exceeds that for central line-associated blood stream infections: an exploratory critique. J Perinatol. 2011;31:514–8.CrossRef Wirtschafter DD, Padilla G, Wan K, Trupp D, Fayard EES. Antibiotic use for presumed neonatally acquired infections far exceeds that for central line-associated blood stream infections: an exploratory critique. J Perinatol. 2011;31:514–8.CrossRef
4.
go back to reference Schelonka RL, Chai MK, Yoder BA, Hensley D, Brockett RM, Ascher DP. Volume of blood required to detect common neonatal pathogens. J Pediatr. 1996;129(2):275–8.CrossRef Schelonka RL, Chai MK, Yoder BA, Hensley D, Brockett RM, Ascher DP. Volume of blood required to detect common neonatal pathogens. J Pediatr. 1996;129(2):275–8.CrossRef
5.
go back to reference Mahieu LM, De Dooy JJ, Cossey VR, Goosens LL, Vrancken SL, Jespers AY, et al. Internal and external validation of the NOSEP prediction score for nosocomial sepsis in neonates. Crit Care Med. 2002;30(7):1459–66.CrossRef Mahieu LM, De Dooy JJ, Cossey VR, Goosens LL, Vrancken SL, Jespers AY, et al. Internal and external validation of the NOSEP prediction score for nosocomial sepsis in neonates. Crit Care Med. 2002;30(7):1459–66.CrossRef
6.
go back to reference Okascharoen C, Hui C, Cairnie J, Morris AM, Kirpalani H. External validation of bed side prediction score for diagnosis of late-onset neonatal sepsis. J Perinatol. 2007;27:496–501.CrossRef Okascharoen C, Hui C, Cairnie J, Morris AM, Kirpalani H. External validation of bed side prediction score for diagnosis of late-onset neonatal sepsis. J Perinatol. 2007;27:496–501.CrossRef
7.
go back to reference Mahieu LM, De Muynck AO, De Dooy JJ, Laroche SM, Van Acker KJ. Prediction of nosocomial sepsis in neonates by means of a computer-weighted bedside scoring system (NOSEP score). Crit Care Med. 2000;28(6):2026–33.CrossRef Mahieu LM, De Muynck AO, De Dooy JJ, Laroche SM, Van Acker KJ. Prediction of nosocomial sepsis in neonates by means of a computer-weighted bedside scoring system (NOSEP score). Crit Care Med. 2000;28(6):2026–33.CrossRef
8.
go back to reference Singh SA, Dutta S, Narang A. Predictive clinical scores for diagnosis of late onset neonatal septicemia. J Trop Pediatr. 2003;49(4):235–9.CrossRef Singh SA, Dutta S, Narang A. Predictive clinical scores for diagnosis of late onset neonatal septicemia. J Trop Pediatr. 2003;49(4):235–9.CrossRef
9.
go back to reference Okascharoen C, Sirinavin S, Thakkinstian A, Kitayaporn D, Supapanachart S. A bedside prediction-scoring model for late onset neonatal Sepsis. J Perinatol. 2005;25(12):778–83.CrossRef Okascharoen C, Sirinavin S, Thakkinstian A, Kitayaporn D, Supapanachart S. A bedside prediction-scoring model for late onset neonatal Sepsis. J Perinatol. 2005;25(12):778–83.CrossRef
10.
go back to reference Dalgic N, Ergenekon E, Koc E, Atalay Y. NOSEP and clinical scores for nosocomial sepsis in a neonatal intensive care unit (letter). J Trop Pediatr. 2006;52(3):226–7.CrossRef Dalgic N, Ergenekon E, Koc E, Atalay Y. NOSEP and clinical scores for nosocomial sepsis in a neonatal intensive care unit (letter). J Trop Pediatr. 2006;52(3):226–7.CrossRef
11.
go back to reference Kudawla M, Dutta S, Narang A. Validation of a clinical score for the diagnosis of late onset neonatal septicemia in babies weighing 1000-2500 g. J Trop Pediatr. 2008;54(1):66–9.CrossRef Kudawla M, Dutta S, Narang A. Validation of a clinical score for the diagnosis of late onset neonatal septicemia in babies weighing 1000-2500 g. J Trop Pediatr. 2008;54(1):66–9.CrossRef
12.
go back to reference Rosenberg RE, Ahmed ASMNU, Saha SK, Chowdhury MAKA, Ahmed S, Law PA, et al. Nosocomial sepsis risk score for preterm infants in low resource settings. J Trop Pediatr. 2010;56(2):82–9.CrossRef Rosenberg RE, Ahmed ASMNU, Saha SK, Chowdhury MAKA, Ahmed S, Law PA, et al. Nosocomial sepsis risk score for preterm infants in low resource settings. J Trop Pediatr. 2010;56(2):82–9.CrossRef
13.
go back to reference Bekhof J, Reitsma JB, Kok JH, Van Straaten IHLM. Clinical signs to identify late-onset sepsis in preterm infants. Eur J Pediatr. 2013;172(4):501–8.CrossRef Bekhof J, Reitsma JB, Kok JH, Van Straaten IHLM. Clinical signs to identify late-onset sepsis in preterm infants. Eur J Pediatr. 2013;172(4):501–8.CrossRef
14.
go back to reference Verstraete EH, Blot K, Mahieu L, Vogelaers D, Blot S. Prediction models for neonatal health care-associated sepsis: a meta-analysis. Pediatrics. 2015;135(4):e1002–14.CrossRef Verstraete EH, Blot K, Mahieu L, Vogelaers D, Blot S. Prediction models for neonatal health care-associated sepsis: a meta-analysis. Pediatrics. 2015;135(4):e1002–14.CrossRef
15.
go back to reference Yapicioglu H, Ozlu F, Sertdemir Y. Are vital signs indicative for bacteremia in newborns? J Matern Fetal Neonatal Med. 2015;28(18):2244–9.CrossRef Yapicioglu H, Ozlu F, Sertdemir Y. Are vital signs indicative for bacteremia in newborns? J Matern Fetal Neonatal Med. 2015;28(18):2244–9.CrossRef
16.
go back to reference Oeser C, Lutsar I, Metsvaht T, Turner MA, Heath PT, Sharland M. Clinical trials in neonatal sepsis. J Antimicrob Chemother. 2013;68:2733–45.CrossRef Oeser C, Lutsar I, Metsvaht T, Turner MA, Heath PT, Sharland M. Clinical trials in neonatal sepsis. J Antimicrob Chemother. 2013;68:2733–45.CrossRef
17.
go back to reference Ng PC. Diagnostic markers of infection in neonates. Arch Dis Child Fetal Neonatal Ed. 2003;89:F229–F35.CrossRef Ng PC. Diagnostic markers of infection in neonates. Arch Dis Child Fetal Neonatal Ed. 2003;89:F229–F35.CrossRef
18.
go back to reference Streimish I, Bizzarro M, Northrup V, Wang C, Renna S, Koval N, et al. Neutrophil CD64 with hematologic criteria for diagnosis of neonatal Sepsis. Am J Perinatol. 2014;31:21–30.CrossRef Streimish I, Bizzarro M, Northrup V, Wang C, Renna S, Koval N, et al. Neutrophil CD64 with hematologic criteria for diagnosis of neonatal Sepsis. Am J Perinatol. 2014;31:21–30.CrossRef
19.
go back to reference Adly AAM, Ismail EA, Andrawes NG, El-Saadany MA. Circulating soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) as diagnostic and prognostic marker in neonatal sepsis. Cytokine. 2014;65:184–91.CrossRef Adly AAM, Ismail EA, Andrawes NG, El-Saadany MA. Circulating soluble triggering receptor expressed on myeloid cells-1 (sTREM-1) as diagnostic and prognostic marker in neonatal sepsis. Cytokine. 2014;65:184–91.CrossRef
20.
go back to reference Sarafidis K, Soubasi-Griva V, Piretzi K, Thomaidou A, Agakidou E, Taparkou A, et al. Diagnostic utility of elevated serum soluble triggering receptor expressed on myeloid cells (sTREM)-1 in infected neonates. Intensive Care Med. 2010;36:864–8.CrossRef Sarafidis K, Soubasi-Griva V, Piretzi K, Thomaidou A, Agakidou E, Taparkou A, et al. Diagnostic utility of elevated serum soluble triggering receptor expressed on myeloid cells (sTREM)-1 in infected neonates. Intensive Care Med. 2010;36:864–8.CrossRef
22.
go back to reference Gokmen Z, Ozkiraz S, Kulaksizoglu S, Kilicdag H, Ozel D, Ecevit A, Tarcan A. Resistin-a novel feature in the diagnosis of sepsis in premature neonates. Am J Perinatol. 2013;30(6):513–8.CrossRef Gokmen Z, Ozkiraz S, Kulaksizoglu S, Kilicdag H, Ozel D, Ecevit A, Tarcan A. Resistin-a novel feature in the diagnosis of sepsis in premature neonates. Am J Perinatol. 2013;30(6):513–8.CrossRef
23.
go back to reference Suguna Narasimhulu S, Hendricks-Munoz KD, Borkowsky W, Mally P. Usefulness of urinary immune biomarkers in the evaluation of neonatal sepsis: a pilot project. Clin Pediatr. 2013;52(6):520–6.CrossRef Suguna Narasimhulu S, Hendricks-Munoz KD, Borkowsky W, Mally P. Usefulness of urinary immune biomarkers in the evaluation of neonatal sepsis: a pilot project. Clin Pediatr. 2013;52(6):520–6.CrossRef
24.
go back to reference Weinstein MP. Blood culture contamination: persisting problems and partial Progress. J Clin Microbiol. 2003;41(6):2275–8.CrossRef Weinstein MP. Blood culture contamination: persisting problems and partial Progress. J Clin Microbiol. 2003;41(6):2275–8.CrossRef
25.
go back to reference Venkatesh MP, Placencia F, Weisman LE. Coagulase-negative staphylococcal infections in the neonate and child: an update. Semin Pediatr Infect Dis. 2006;17:120–7.CrossRef Venkatesh MP, Placencia F, Weisman LE. Coagulase-negative staphylococcal infections in the neonate and child: an update. Semin Pediatr Infect Dis. 2006;17:120–7.CrossRef
26.
go back to reference Isaacs D. A ten year, multicentre study of coagulase negative staphylococcal infections in Australasian neonatal units. Arch Dis Child Fetal Neonatal Ed. 2003;88:F89–93.CrossRef Isaacs D. A ten year, multicentre study of coagulase negative staphylococcal infections in Australasian neonatal units. Arch Dis Child Fetal Neonatal Ed. 2003;88:F89–93.CrossRef
27.
go back to reference Anderson T, Rubin H. Statistical inference in factor analysis. Berkeley: University of California Press; 1956. Anderson T, Rubin H. Statistical inference in factor analysis. Berkeley: University of California Press; 1956.
28.
go back to reference Everitt BS. Multivariate analysis: the need for data, and other problems. Br J Psychiatry. 1975;126:237–40.CrossRef Everitt BS. Multivariate analysis: the need for data, and other problems. Br J Psychiatry. 1975;126:237–40.CrossRef
29.
go back to reference Gorsuch R. Factor analysis. Second ed. Hillsdale: Lawrence Erlbaum Associates; 1983. Gorsuch R. Factor analysis. Second ed. Hillsdale: Lawrence Erlbaum Associates; 1983.
30.
go back to reference Kline P. A handbook of test construction: introduction to psychometric design. London: Methuen and Co; 1986. Kline P. A handbook of test construction: introduction to psychometric design. London: Methuen and Co; 1986.
31.
go back to reference Nunnally J. Psychometric theory. Second ed. New York: McGraw-Hill; 1978. Nunnally J. Psychometric theory. Second ed. New York: McGraw-Hill; 1978.
32.
go back to reference Velicer W, Fava J. Effects of variable and subject sampling on factor pattern recovery. Psychol Methods. 1998;3:231–51.CrossRef Velicer W, Fava J. Effects of variable and subject sampling on factor pattern recovery. Psychol Methods. 1998;3:231–51.CrossRef
Metadata
Title
Development, evaluation and validation of a screening tool for late onset bacteremia in neonates – a pilot study
Authors
Sandra A. N. Walker
Melanie Cormier
Marion Elligsen
Julie Choudhury
Asaph Rolnitsky
Carla Findlater
Dolores Iaboni
Publication date
01-12-2019
Publisher
BioMed Central
Published in
BMC Pediatrics / Issue 1/2019
Electronic ISSN: 1471-2431
DOI
https://doi.org/10.1186/s12887-019-1633-1

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