Home Print this page Email this page Small font sizeDefault font sizeIncrease font size
Users Online: 178
 
About us Editorial board Search Ahead of print Current issue Archives Submit article Instructions Subscribe Contacts Advertise Login 
     


 
 Table of Contents  
ORIGINAL ARTICLE
Year : 2017  |  Volume : 6  |  Issue : 3  |  Page : 159-162

Association between sepsis calculator and infection parameters for newborns with suspected early onset sepsis


1 Department of Pediatrics, Tergooi Hospital, Blaricum, The Netherlands
2 Department of Pediatrics, Tergooi Hospital, Blaricum; Department of Pathology and Medical Biology, University Medical Center Groningen, Groningen, The Netherlands
3 Department of Epidemiology and Statistics, St. Antonius Hospital, Nieuwegein, The Netherlands

Date of Web Publication11-Jul-2017

Correspondence Address:
Niek B Achten
Rijksstraatweg 1, 1261 AN Blaricum
The Netherlands
Login to access the Email id

Source of Support: None, Conflict of Interest: None


DOI: 10.4103/jcn.JCN_110_16

Rights and Permissions
  Abstract 

Context: Early-onset sepsis remains an important clinical problem with significant antibiotic overtreatment as a result of poor specificity of clinical and infection parameters. Quantitative risk stratification models such as the early-onset neonatal sepsis (EOS) calculator are promising, but it is unclear how these models relate to infection parameters in the first 72 h of life. Aim: The aim of this study is to evaluate the hypothesis that higher EOS calculator results are associated with (serial) laboratory infection parameters, in particular an increase in C-reactive protein (CRP) within 24–48 h and low leukocyte counts. Subjects and Methods: EOS risk estimates were determined for infants born ≥34 weeks of gestation who were started on antibiotic treatment for suspected EOS within 72 h after birth. EOS risk estimates were retrospectively compared to (changes in) available laboratory infection parameters, including CRP, leukocyte, and thrombocyte count. Statistical Analysis Used: Spearman's rho rank correlations coefficient was used when testing for correlations between continuous parameters. Kruskal–Wallis and Mann–Whitney U-tests were applied to differences between stratified risk groups. Results: EOS risk was not correlated with changes in infection parameters. We found negative correlations between both EOS risk and CRP level and leukocyte count within 6 h of the start of antibiotics, as well as CRP level between 6 and 24 h after start of treatment.
Conclusions: In contrast to our hypothesis, high EOS risk at birth was consistently correlated with lower CRP and leukocyte counts within 24 h after the start of antibiotics, but not with infection parameters after 24 h. Further interpretation of infection parameters during sepsis calculator use needs to be elucidated.

Keywords: Antibiotics, early-onset sepsis, infection, newborns, sepsis calculator


How to cite this article:
Achten NB, Zonneveld R, Tromp E, Plötz FB. Association between sepsis calculator and infection parameters for newborns with suspected early onset sepsis. J Clin Neonatol 2017;6:159-62

How to cite this URL:
Achten NB, Zonneveld R, Tromp E, Plötz FB. Association between sepsis calculator and infection parameters for newborns with suspected early onset sepsis. J Clin Neonatol [serial online] 2017 [cited 2017 Aug 23];6:159-62. Available from: http://www.jcnonweb.com/text.asp?2017/6/3/159/210130


  Introduction Top


Early-onset neonatal sepsis (EOS) remains an important clinical problem in neonatal care. Due to poor specificity of clinical findings and limited usability of available infection biomarkers, there is significant over-treatment with antibiotics in the first 72 h of life of newborns with suspected EOS.[1] In an attempt to overcome this problem, a quantitative risk stratification strategy based on objective maternal risk factors and neonatal clinical findings has been developed.[2] This model, hereafter referred to as the EOS calculator, provides a quantitative estimation of EOS risk along with a recommendation on the use of antibiotics and is available online. Two retrospective studies revealed that the application of the EOS calculator may significantly reduce antibiotic therapy and thus use of the calculator may become more common in clinical practice.[3],[4]

Despite this promising potential, it is currently unclear how the EOS calculator estimated risk and recommendations relate to infection parameters in the first 72 h of life. Serial values in C-reactive protein (CRP) and leukocyte count are still commonly used as arguments for the start and duration of antibiotic therapy.[1],[5] For this study, our aim was to evaluate the hypothesis that higher EOS calculator results are associated with (serial) laboratory infection parameters. As EOS is associated with elevated CRP and a lower leukocyte count,[5],[6] we particularly hypothesized high EOS risk estimate to be associated with an increase in CRP within 24–48 h, and low leukocyte counts.


  Subjects and Methods Top


Study design

Data from a previously established retrospective birth cohort were used for analysis.[4] The study included all newborns born ≥34 weeks of gestation, who were started on antibiotic treatment for suspected EOS within 72 h after birth, in Tergooi Hospital, Blaricum, The Netherlands, during 2014. Exclusion criteria were major congenital anomalies, including chromosomal and prophylactic treatment with antibiotics. The study was approved by the Scientific Review Committee of Tergooi Hospital.

Data collection

Maternal and neonatal clinical data were derived from hospital records. Local protocol required routine infection parameter testing in newborns treated for clinically suspected EOS at start of antibiotic therapy and follow-up testing at 12–24 h and/or 24–72 h after the start of antibiotic treatment. Infection parameter results were derived from electronic laboratory records.

Early-onset neonatal sepsis calculator risk estimates and stratification

EOS risk estimates were determined using the online calculator as provided by Escobar et al., through http://newbornsepsiscalculator.org.[2],[7] These estimates represent the estimated incidence of EOS per 1000 live births and were calculated individually for each newborn in the study. The resultant sepsis risk was categorized into three levels; <0.65 (low risk), 0.65–1.54 (intermediate risk), and >1.54 (high risk) per 1000 live births. In addition to using EOS calculator risk estimate as a continuous variable, we used these groups for stratified analysis.

Delta variables

Since specifically serial values in infection parameters are used to guide clinical decisions,[8] we calculated delta variables when serial values were available. For delta variables, we calculated absolute differences between values derived from initial blood draw (0–6 h after start of treatment) and follow-up values 24 h after start of treatment. Values derived between 6 and 24 h were used as follow-up values if values >24 h were unavailable.

Statistical analysis

All data were statistically analyzed using R (version 3.2.1) (http://www.r-project.org). Distributions of continuous variables were visualized using kernel density plots. Spearman's rho rank correlations coefficient was used when testing for correlations between EOS risk estimates and infection parameters (continuous variables not normally distributed). Kruskal–Wallis and Mann–Whitney U-tests were applied to determine the significance of differences between EOS stratified risk groups.


  Results Top


After exclusion of three newborns with insufficient clinical information to estimate EOS risk, data from 108 newborns were used for analysis [Table 1].
Table 1: Infection parameters and correlation results among total and stratified risk group analysis

Click here to view


C-reactive protein

We found negative correlations between EOS risk estimations and CRP levels within 6 h and between 6 and 24 h after the start of antibiotics (Spearman's rho −0.45 and −0.24, respectively). This was confirmed by EOS stratified group analysis, where the high EOS risk group was associated with lower CRP levels [<1 vs. 11.5 mg/L, P < 0.05, [Table 1]. EOS risk estimate was not correlated with change in CRP as determined by the delta CRP variable based on serial CRP values.

Leukocytes and thrombocytes

EOS risk estimate was not correlated with changes in serial leukocytes count. Lower leukocyte counts within 6 h after the start of antibiotics were associated with higher EOS risk estimations (Spearman's rho −0.30). Leukocyte count within 6 h after start of antibiotics was lower in the high-risk group compared to the intermediate/low-risk group (P < 0.05) [Table 1]. There were no correlations between EOS risk and (serial) thrombocyte counts.


  Discussion Top


In contrast to our hypothesis, we did not find any correlations between EOS risk and changes in serial CRP or serial leukocyte or thrombocyte counts. We observed negative correlations between EOS risk estimate and CRP level and leukocyte count within 6 h of start of antibiotics, as well as CRP level between 6 and 24 h after start of treatment. Analyzing differences between EOS stratified risk groups comparable results within 6 h of start of treatment were found.

In the high-risk group, single point measurement CRP levels were in the normal range at start of antibiotic therapy, which was started shortly after birth. This can be explained by the fact that CRP levels represent endogenous neonatal synthesis, rise above 5 mg/L by 6–8 h, and peak around 24–48 h.[9],[10] Negative correlation between high EOS risk and CRP levels at the start of antibiotic treatment may be explained by the fact that high-risk newborns started with antibiotic treatment shortly after birth, before endogenous synthesis of CRP occurred. Furthermore, this may also explain the significant differences of CRP levels of <1 mg/L in high-risk group versus 11.5 mg/L in the low-risk group at the start of antibiotics (P < 0.05). In contrast to the high-risk group, antibiotic therapy was mostly started 12 h after birth in the low-risk group of our population.[4]

Remarkably, CRP levels did not clearly increase in the high-risk group as CPR level after 24–48 h was not significantly raised compared to low and intermediate risk groups. This appears to contrast with studies confirming that the sensitivity of CRP increases substantially with serial determinations of CRP 24–48 h after the onset of symptoms.[9] However, although EOS-risk is correlated with infection, still the majority of the newborns in this group had negative blood cultures, corresponding with persistent low CRP levels. In addition, given the half-life of CRP (19 h) and clinical studies showing CRP levels decreasing after 16 h in response to successful antibiotic therapy, it is well possible that CRP-levels have returned to normal range within 24–48 h in infected children in the high-risk group, as this group was generally started on antibiotics within shortly after birth.[9],[11]

From a clinical point of view, these findings underline the puzzling nature of EOS clinical management, with high EOS risk associated with low CRP levels. In the high-risk group, based on objective maternal factors and newborn clinical evaluation, antibiotic therapy is started and continued for 7 days. In this group, (serial) CRP measurement is not of additional value to discontinue antibiotic therapy in case of negative blood cultures. In the low EOS risk group, however, serial CRP may serve to discontinue antibiotic treatment after 3 days, given the negative predictive value of serial low CRP levels.[10]

The correlation between higher EOS risk estimates and lower leukocyte counts within 6 h after start of antibiotics corresponds with published findings showing lower leukocyte counts being associated with EOS.[6] It should be noted, however, that low leukocyte counts are rare – reflected in a modest difference in absolute leukocyte count between the high-risk group and overall median (15.3 vs. 16.4 × 10^9/L). Therefore, leukocyte counts are likely to be of limited clinical value in EOS diagnostics. Finally, (changes) in thrombocyte counts were, in line with published literature, not related to EOS risk. Thus, we do not recommend the use of thrombocyte counts to guide clinical decisions regarding antibiotics for EOS, regardless of estimated EOS risk.

Limitations of this study include its retrospective nature and selection bias for determination of infection parameters. However, given the high percentage of available results within 6 h of start of antibiotics, we think this bias is limited for the correlations we found. Our sample size is limited, but given the consistent results among correlation and stratified group level analysis, we do not expect different results with a larger sample size.


  Conclusions Top


EOS remains an important clinical problem with significant antibiotic overtreatment as a result of poor clinical and infection parameters. In newborns treated for EOS, risk estimates are neither associated with changes in CRP level nor leukocyte or thrombocyte count. If more widespread use of the sepsis calculator is expected, the interpretation of common infection parameters in the context of EOS risk needs to be further elucidated.

Financial support and sponsorship

Nil.

Conflicts of interest

There are no conflicts of interest.

 
  References Top

1.
van Herk W, Stocker M, van Rossum AM. Recognising early onset neonatal sepsis: An essential step in appropriate antimicrobial use. J Infect 2016;72:S77-82.  Back to cited text no. 1
[PUBMED]    
2.
Escobar GJ, Puopolo KM, Wi S, Turk BJ, Kuzniewicz MW, Walsh EM, et al. Stratification of risk of early-onset sepsis in newborns ≥ 34 weeks' gestation. Pediatrics 2014;133:30-6.  Back to cited text no. 2
[PUBMED]    
3.
Shakib J, Buchi K, Smith E, Young PC. Management of newborns born to mothers with chorioamnionitis: Is it time for a kinder, gentler approach? Acad Pediatr 2015;15:340-4.  Back to cited text no. 3
    
4.
Kerste M, Corver J, Sonnevelt MC, van Brakel M, van der Linden PD, M Braams-Lisman BA, et al. Application of sepsis calculator in newborns with suspected infection. J Matern Fetal Neonatal Med 2016;29:3860-5.  Back to cited text no. 4
    
5.
Chirico G, Loda C. Laboratory aid to the diagnosis and therapy of infection in the neonate. Pediatr Rep 2011;3:e1.  Back to cited text no. 5
    
6.
Newman TB, Puopolo KM, Wi S, Draper D, Escobar GJ. Interpreting complete blood counts soon after birth in newborns at risk for sepsis. Pediatrics 2010;126:903-9.  Back to cited text no. 6
    
7.
Puopolo KM, Draper D, Wi S, Newman TB, Zupancic J, Lieberman E, et al. Estimating the probability of neonatal early-onset infection on the basis of maternal risk factors. Pediatrics 2011;128:e1155-63.  Back to cited text no. 7
    
8.
van Herk W, el Helou S, Janota J, Hagmann C, Klingenberg C, Staub E, et al. Variation in current management of term and late-preterm neonates at risk for early-onset sepsis: An international survey and review of guidelines. Pediatr Infect Dis J 2016;35:494-500.  Back to cited text no. 8
    
9.
Hofer N, Zacharias E, Müller W, Resch B. An update on the use of C-reactive protein in early-onset neonatal sepsis: Current insights and new tasks. Neonatology 2012;102:25-36.  Back to cited text no. 9
    
10.
Simonsen KA, Anderson-Berry AL, Delair SF, Davies HD. Early-onset neonatal sepsis. Clin Microbiol Rev 2014;27:21-47.  Back to cited text no. 10
    
11.
Ehl S, Gehring B, Pohlandt F. A detailed analysis of changes in serum C-reactive protein levels in neonates treated for bacterial infection. Eur J Pediatr 1999;158:238-42.  Back to cited text no. 11
    



 
 
    Tables

  [Table 1]



 

Top
 
 
  Search
 
Similar in PUBMED
  Search Pubmed for
  Search in Google Scholar for
Related articles
Access Statistics
Email Alert *
Add to My List *
* Registration required (free)

 
  In this article
Abstract
Introduction
Subjects and Methods
Results
Discussion
Conclusions
References
Article Tables

 Article Access Statistics
    Viewed282    
    Printed4    
    Emailed0    
    PDF Downloaded92    
    Comments [Add]    

Recommend this journal