Predictors of serious bacterial infections using serum biomarkers in an infant population aged 0 to 90 days: a prospective cohort study

Chang, Serena Su Ying; Lim, Amanda Zhirui; Ong, Gene Yong-Kwang; Piragasam, Rupini; Allen, John C.; Ng, Kee Chong; Maconochie, Ian; Chong, Shu-Ling

doi:10.1136/bmjpo-2020-000861

Cited by 13 publications

(9 citation statements)

References 40 publications

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“…10,18,19 We found that CRP and PCT as single biomarkers were strong predictors of SBIs and IBIs. In line with the findings of previous studies, 6,20,21 CRP ≥20mg/L performed best in predicting SBIs with an AUC of 0.741.…”

Section: Discussionsupporting

confidence: 90%

Validation and comparison of the PECARN rule, Step-by-Step approach and Lab-score for predicting serious and invasive bacterial infections in young febrile infants

Sutiman

Khoo

Ong

et al. 2022

Ann Acad Med Singap

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Introduction: Differentiating infants with serious bacterial infections (SBIs) or invasive bacterial infections (IBIs) from those without remains a challenge. We sought to compare the diagnostic performances of single biomarkers (absolute neutrophil count [ANC], C-reactive protein [CRP] and procalcitonin [PCT]) and 4 diagnostic approaches comprising Lab-score, Step-by-Step approach (original and modified) and Pediatric Emergency Care Applied Research Network (PECARN) rule. Method: This is a prospective cohort study involving infants 0–90 days of age who presented to an emergency department from July 2020 to August 2021. SBIs were defined as bacterial meningitis, bacteraemia and/or urinary tract infections. IBIs were defined as bacteraemia and/or bacterial meningitis. We evaluated the performances of Lab-score, Step-by-Step (original and modified) and PECARN rule in predicting SBIs and IBIs. Results: We analysed a total of 258 infants, among whom 86 (33.3%) had SBIs and 9 (3.5%) had IBIs. In predicting SBIs, ANC ≥4.09 had the highest sensitivity and negative predictive value (NPV), while PCT ≥1.7 had the highest specificity and positive predictive value (PPV). CRP ≥20 achieved the highest area under receiver operating characteristic curve (AUC) of 0.741 (95% confidence interval [CI] 0.672–0.810). The Step-by-Step (original) approach had the highest sensitivity (97.7%). Lab-score had the highest AUC of 0.695 (95% CI 0.621–0.768), compared to PECARN rule at 0.625 (95% CI 0.556–0.694) and Step-by-Step (original) at 0.573 (95% CI 0.502–0.644). In predicting IBIs, PCT ≥1.7 had the highest sensitivity, specificity, PPV and NPV. The Step-by-Step (original and modified) approach had the highest sensitivity of 100%. Lab-score had the highest AUC of 0.854 (95% CI 0.731–0.977) compared to PECARN rule at 0.589 (95% CI 0.420–0.758) and Step-by-Step at 0.562 (95% CI 0.392–0.732). Conclusion: CRP strongly predicted SBIs, and PCT strongly predicted IBI. The Step-by-Step approach had the highest sensitivity and NPV, while Lab-score had the highest specificity and AUC in predicting SBIs and IBIs. Keywords: Biomarkers, diagnostic approaches, febrile infants, Lab-score, PECARN rule, Step-by-Step approach

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Section: Discussionsupporting

confidence: 90%

Validation and comparison of the PECARN rule, Step-by-Step approach and Lab-score for predicting serious and invasive bacterial infections in young febrile infants

Sutiman

Khoo

Ong

et al. 2022

Ann Acad Med Singap

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“…Its physiological levels have been widely studied, even within the initial hours of life [ 62 ]. Compared to white blood cell count (WBC), absolute neutrophil count (ANC), and neutrophil-to-lymphocyte ratio (NLR), CRP exhibits superior discriminatory performance for SBI in the context of young infants presenting with fever in the ED, as evidenced by an area under the receiver operator curve (ROC) of 0.815 (95% confidence interval (CI) 0.748 to 0.883) [ 63 ]. It is crucial to emphasize that none of these individual biomarkers achieve perfection, aligning with findings from prior studies.…”

Section: From Biomarkers To Safety Nets: An Exploration Of Potential ...mentioning

confidence: 99%

Antimicrobial Stewardship in Pediatric Emergency Medicine: A Narrative Exploration of Antibiotic Overprescribing, Stewardship Interventions, and Performance Metrics

Meesters,

Buonsenso

2024

Children

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Antibiotic overprescribing is prevalent in pediatric emergency medicine, influenced by clinician–caregiver dynamics and diagnostic uncertainties, and poses substantial risks such as increasing antibacterial resistance, adverse drug reactions, and increased healthcare expenditures. While antimicrobial stewardship programs have proven effective in optimizing antibiotic use within inpatient healthcare settings, their implementation in pediatric emergency medicine presents specific challenges. Existing biomarkers like white blood cell count, C-reactive protein, procalcitonin, and presepsin have limitations in their ability to distinguish (serious) bacterial infections from other etiologies of fever. Furthermore, rapid antigen detection tests and guidelines aimed at guiding antibiotic prescriptions for children have not consistently reduced unnecessary antibiotic use. To improve antibiotic prescribing practices, potential strategies include the utilization of decision support tools, audit and feedback, establishing follow-up procedures, implementing safety netting systems, and delivering comprehensive training and supervision. Notably, host genome signatures have also gained attention for their potential to facilitate rapid and precise diagnoses of inflammatory syndromes. Standardized metrics are crucial for evaluating antimicrobial use within pediatric healthcare settings, enabling the establishment of benchmarks for assessing antibiotic utilization, quality enhancement initiatives, and research endeavors.

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“…Organisms present in the mother can be passed to the fetus by blood, rectovaginal, amniotic fluid and placenta, causing neonate PM (9). Some hematology tests, such as white blood cell (WBC), C-reactive protein (CRP), and procalcitonin (PCT) tests, are of limited value individually due to their low sensitivity and cannot be used to predict PM (10).…”

Section: Introductionmentioning

confidence: 99%

Establishment of a predictive model for purulent meningitis in preterm infants

Cheng¹,

Zhang²,

Fu³

et al. 2022

Transl Pediatr

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Background: Purulent meningitis (PM) is an important cause of mortality and morbidity in the newborn population throughout the world. The subtle of specific clinical signs and low success rates of lumbar puncture make diagnosis of PM more difficult in preterm than in older children. The objective of this study was to establish a predict model for preterm PM in hopes of helping clinicians develop new diagnostic and treatment strategies.Methods: Premature infants who were admitted to The First Affiliated Hospital of Zhengzhou University from September 2017 to March 2020 were enrolled in this study. All the patients underwent lumbar puncture. We collected data encompassing maternal diseases and neonatal clinical features. Cerebrospinal fluid (CSF) culture is the gold standard for diagnosing meningitis. The PM was diagnosed according to the diagnostic criteria. All statistical analyses were performed using R 3.63 (https://www.r-project.org/). Logistic regression and least absolute shrinkage and selection operator (LASSO) regression analyses were used to establish a risk prediction model of PM. The Brier score, calibration slope, and concordance (C)-index were used to verify the accuracy of prediction model.Results: A total of 168 preterm infants were enrolled in this study, 80 boys and 88 girls, the gestational age (GA) was 26. 43-36.86 weeks (32.45±2.79 weeks), the birth weight (BW) was 700-3,400 g (1,814.05±568.84 g).There were 77 preterm infants with PM while 91 without. We identified seven variables as independent risk factors for PM in preterm infants by LASSO analysis [the optimal λ was 0.080960, and log(λ) = −2.5138],including procalcitonin (PCT) on the 1st day after birth, prenatal glucocorticoid use, albumin, the 1-minute Apgar score, the use of non-invasive biphasic positive airway pressure, hemoglobin, and sex. These were used to construct a risk prediction nomogram and verified its accuracy. The Brier score was 0.17, the calibration slope was 0.966, and the concordance index was 0.82018.Conclusions: Our prediction model could predict the risk of PM in preterm infants. Using this prediction model, it may be able to provide reference to determine whether lumbar puncture is performed and whether antibiotics are applied as soon as possible.

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Predictors of serious bacterial infections using serum biomarkers in an infant population aged 0 to 90 days: a prospective cohort study

Cited by 13 publications

References 40 publications

Validation and comparison of the PECARN rule, Step-by-Step approach and Lab-score for predicting serious and invasive bacterial infections in young febrile infants

Validation and comparison of the PECARN rule, Step-by-Step approach and Lab-score for predicting serious and invasive bacterial infections in young febrile infants

Antimicrobial Stewardship in Pediatric Emergency Medicine: A Narrative Exploration of Antibiotic Overprescribing, Stewardship Interventions, and Performance Metrics

Establishment of a predictive model for purulent meningitis in preterm infants

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