Antibiotics in critically ill children-a narrative review on different aspects of a rational approach

Retrospective analysis of 300 microbial cell-free DNA sequencing results in routine blood stream infection diagnostics

Introduction

Bloodstream infections are a critical challenge worldwide due to the slow turnaround time of conventional microbiological tests for detecting bacteremia in septic patients. Noscendo GmbH (Duisburg, Germany) has developed the CE/IVD pipeline DISQVER for clinical metagenomics testing based on cell-free DNA (cfDNA) from blood samples to address this issue.

Methods

We conducted a retrospective study to evaluate the diagnostic utility of this methodological setup in improving treatment decisions since it was introduced into our clinical setting. Between January 2021 and June 2022, the first 300 cases in which DISQVER was applied at our university hospital were collected and analyzed. The results were compared with routine microbiology test results, clinical picture, associated treatment decisions, and clinical course.

Results

Our findings demonstrate that DISQVER results where no pathogen was reported effectively ruled out bacterial bloodstream infections, whereas positive results varied in their usefulness. While the metagenomic approach proved highly valuable for detecting non-culturable and rare pathogens, its utility was limited in cases where detected microorganisms were commonly associated with the microbiota.

Discussion

Performing on-site analysis might mitigate delays resulting from logistical challenges and might help optimizing antibiotic stewardship. Once prompt results can be obtained, the relevance of incorporating molecular resistograms will become more pronounced. Further, the specific patient subgroups that most benefit from this analysis must be worked out. Guiding clinicians in identifying the infection focus based on the detected bacteria would significantly improve patient care. Lastly, evidence of filamentous fungi must be diligently followed up.

Thromboelastometry-Based Profiling of Haemostatic Alterations in Neonatal Sepsis by Causative Pathogens

Background: Neonatal sepsis is a serious condition with high mortality, especially in premature and low-birth-weight neonates. This study aims to examine whether the haemostatic profile of neonates with sepsis defers depending on the type of bacteria (Gram-positive or Gram-negative), by using the method of Rotational Thromboelastometry (ROTEM). Methods: This single-centre prospective cohort study was conducted on 128 neonates with sepsis, including 95 cases caused by Gram-negative pathogens and 33 cases caused by Gram-positive bacteria. All participants were hospitalised in the Neonatal Intensive Care Unit (NICU). ROTEM parameters were compared between neonates with Gram-positive and Gram-negative infections. Results: The ROTEM parameters were found to be significantly different between neonates suffering from Gram-positive versus Gram-negative infections, with Gram-positive pathogens associated with an increased clotting potential compared to Gram-negative pathogens. This is reflected in the higher ROTEM values such as A10, α-angle, and MCF in the EXTEM and INTEM assays. Multivariant analysis showed that Gram-positive infections were linked to increased clot thickness at 10 min (coefficient: 8.9, CI: 2.8-15.0, p = 0.004), higher maximum clot stability (coefficient: 10.4, CI: 4.3-16.6, p = 0.001), and a bigger α-angle (coefficient: 8.0, CI: 2.7-13.2, p = 0.003). Similar findings were observed in the INTEM assay parameters. Conclusions: Neonatal sepsis caused by Gram-positive bacteria leads to a hypercoagulable haemostatic state, whereas neonates with sepsis caused by Gram-negative bacteria exhibit a more hypocoagulable profile and a higher incidence of haemorrhagic episodes. These findings provide valuable insights into the haemostatic disorders associated with sepsis, and may aid in developing an individualised approach for the treatment of those disorders, dependent on and adapted for the specific type of causative organism.

The epidemiology of critical respiratory diseases in ex-premature infants in Vietnam: A prospective single-center study

INTRODUCTION

This study aimed to describe the epidemiology and etiologies of critical respiratory diseases of ex-premature infants (EPIs) admitted to the Pediatric Intensive Care unit (PICU).

METHODS

Infants ≤2 years old with acute respiratory illnesses admitted to PICU of Vietnam National Children's Hospital from November 2019 to April 2021 were enrolled and followed up to hospital discharge. We compared respiratory pathogens, outcomes, and PICU resources utilized between EPIs and term infants. Among EPIs, we described clinical characteristics and evaluated the association between associated factors and mortality.

RESULTS

Among 1183 patients, aged ≤2 years were admitted for critical respiratory illnesses, 202 (17.1%) were EPIs. Respiratory viruses were detected in 53.5% and 38.2% among EPIs and term infants, respectively. Compared to term infants, a higher proportion of EPIs required mechanical ventilation (MV) (85.6 vs. 66.5%, p < .005) and vasopressor support (37.6 vs. 10.7%%, p < .005). EPIs had a higher median PICU length of stay (11.0 [IQR: 7; 22] vs. 6.0 days [IQR: 3; 11], p = .09), hospital length of stay (21.5 [IQR: 13; 40] vs. 10.0 days [IQR: 5; 18], p < .005) and case fatality rate (31.3% vs. 22.6%) compared to term infants. Among EPIs, PIM-3 score (adjusted odds ratio [aOR]: 1.51; 95% confidence interval [CI]: 1.30-1.75) and PELOD-2 score at admission (aOR: 1.41; 95% CI: 1.08-1.85) were associated with mortality.

CONCLUSIONS

EPIs with critical respiratory illnesses constituted a significant population in the PICU, required more PICU support, and had worse clinical outcomes compared to term infants.

Intraduodenal fecal microbiota transplantation ameliorates gut atrophy and cholestasis in a novel parenteral nutrition piglet model

Total parenteral nutrition (TPN) provides lifesaving nutritional support intravenously; however, it is associated with significant side effects. Given gut microbial alterations noted with TPN, we hypothesized that transferring fecal microbiota from healthy controls would restore gut-systemic signaling in TPN and mitigate injury. Using our novel ambulatory model (US Patent: US 63/136,165), 31 piglets were randomly allocated to enteral nutrition (EN), TPN only, TPN + antibiotics (TPN-A), or TPN + intraduodenal fecal microbiota transplant (TPN + FMT) for 14 days. Gut, liver, and serum were assessed through histology, biochemistry, and qPCR. Stool samples underwent 16 s rRNA sequencing. Permutational multivariate analysis of variance, Jaccard, and Bray-Curtis metrics were performed. Significant bilirubin elevation in TPN and TPN-A versus EN (P < 0.0001) was prevented with FMT. IFN-G, TNF-α, IL-β, IL-8, and lipopolysaccharide (LPS) were significantly higher in TPN (P = 0.009, P = 0.001, P = 0.043, P = 0.011, P < 0.0001), with preservation upon FMT. Significant gut atrophy by villous-to-crypt ratio in TPN (P < 0.0001) and TPN-A (P = 0.0001) versus EN was prevented by FMT (P = 0.426 vs. EN). Microbiota profiles using principal coordinate analysis demonstrated significant FMT and EN overlap, with the largest separation in TPN-A followed by TPN, driven primarily by Firmicutes and Fusobacteria. TPN-altered gut barrier was preserved upon FMT; upregulated cholesterol 7 α-hydroxylase and bile salt export pump in TPN and TPN-A and downregulated fibroblast growth factor receptor 4, EGF, farnesoid X receptor, and Takeda G Protein-coupled Receptor 5 (TGR5) versus EN was prevented by FMT. This study provides novel evidence of prevention of gut atrophy, liver injury, and microbial dysbiosis with intraduodenal FMT, challenging current paradigms into TPN injury mechanisms and underscores the importance of gut microbes as prime targets for therapeutics and drug discovery.NEW & NOTEWORTHY Intraduodenal fecal microbiota transplantation presents a novel strategy to mitigate complications associated with total parenteral nutrition (TPN), highlighting gut microbiota as a prime target for therapeutic and diagnostic approaches. These results from a highly translatable model provide hope for TPN side effect mitigation for thousands of chronically TPN-dependent patients.

Interpretable machine learning for allergic rhinitis prediction among preschool children in Urumqi, China

This study aimed to investigate the advantages and applications of machine learning models in predicting the risk of allergic rhinitis (AR) in children aged 2-8, compared to traditional logistic regression. The study analyzed questionnaire data from 7131 children aged 2-8, which was randomly divided into training, validation, and testing sets in a ratio of 55:15:30, repeated 100 times. Predictor variables included parental allergy, medical history during the child's first year (cfy), and early life environmental factors. The time of first onset of AR was restricted to after the age of 1 year to establish a clear temporal relationship between the predictor variables and the outcome. Feature engineering utilized the chi-square test and the Boruta algorithm, refining the dataset for analysis. The construction utilized Logistic Regression (LR), Support Vector Machine (SVM), Random Forest (RF), and Extreme Gradient Boosting Tree (XGBoost) as the models. Model performance was evaluated using the area under the receiver operating characteristic curve (AUROC), and the optimal decision threshold was determined by weighing multiple metrics on the validation sets and reporting results on the testing set. Additionally, the strengths and limitations of the different models were comprehensively analyzed by stratifying gender, mode of birth, and age subgroups, as well as by varying the number of predictor variables. Furthermore, methods such as Shapley additive explanations (SHAP) and purity of node partition in Random Forest were employed to assess feature importance, along with exploring model stability through alterations in the number of features. In this study, 7131 children aged 2-8 were analyzed, with 524 (7.35%) diagnosed with AR, with an onset age ranging from 2 to 8 years. Optimal parameters were refined using the validation set, and a rigorous process of 100 random divisions and repeated training ensured robust evaluation of the models on the testing set. The model construction involved incorporating fourteen variables, including the history of allergy-related diseases during the child's first year, familial genetic factors, and early-life indoor environmental factors. The performance of LR, SVM, RF, and XGBoost on the unstratified data test set was 0.715 (standard deviation = 0.023), 0.723 (0.022), 0.747 (0.015), and 0.733 (0.019), respectively; the performance of each model was stable on the stratified data, and the RF performance was significantly better than that of LR (paired samples t-test: p < 0.001). Different techniques for evaluating the importance of features showed that the top5 variables were father or mother with AR, having older siblings, history of food allergy and father's educational level. Utilizing strategies like stratification and adjusting the number of features, this study constructed a random forest model that outperforms traditional logistic regression. Specifically designed to detect the occurrence of allergic rhinitis (AR) in children aged 2-8, the model incorporates parental allergic history and early life environmental factors. The selection of the optimal cut-off value was determined through a comprehensive evaluation strategy. Additionally, we identified the top 5 crucial features that greatly influence the model's performance. This study serves as a valuable reference for implementing machine learning-based AR prediction in pediatric populations.

Pharmacokinetics in Critically Ill Children with Acute Kidney Injury

Acute kidney injury (AKI) is a commonly encountered comorbidity in critically ill children. The coexistence of AKI disturbs drug pharmacokinetics and pharmacodynamics, leading to clinically significant consequences. This can complicate an already critical clinical scenario by causing potential underdosing or overdosing giving way to possible therapeutic failures and adverse reactions. Current available studies offer little guidance to help maneuver such complex dosing regimens and decision-making in pediatric patients as most of them are done on heterogeneous groups of adult populations. Though there are some studies on drug dosing during continuous renal replacement therapy (CRRT), their utility is in question because of the recent advances in CRRT technology. Our review aims to discuss the principles of pharmacokinetics pertinent for honing the existing practices of drug dosing in critically ill children with AKI, and the various complexities and intricate challenges involved. This in turn will provide a framework to help enable caretakers to tailor dosing regimens in complex clinical setups with further ease and precision.

Update on Therapeutic Drug Monitoring of Beta-Lactam Antibiotics in Critically Ill Patients—A Narrative Review

Beta-lactam antibiotics remain one of the most preferred groups of antibiotics in critical care due to their excellent safety profiles and their activity against a wide spectrum of pathogens. The cornerstone of appropriate therapy with beta-lactams is to achieve an adequate plasmatic concentration of a given antibiotic, which is derived primarily from the minimum inhibitory concentration (MIC) of the specific pathogen. In a critically ill patient, the plasmatic levels of drugs could be affected by many significant changes in the patient’s physiology, such as hypoalbuminemia, endothelial dysfunction with the leakage of intravascular fluid into interstitial space and acute kidney injury. Predicting antibiotic concentration from models based on non-critically ill populations may be misleading. Therapeutic drug monitoring (TDM) has been shown to be effective in achieving adequate concentrations of many drugs, including beta-lactam antibiotics. Reliable methods, such as high-performance liquid chromatography, provide the accurate testing of a wide range of beta-lactam antibiotics. Long turnaround times remain the main drawback limiting their widespread use, although progress has been made recently in the implementation of different novel methods of antibiotic testing. However, whether the TDM approach can effectively improve clinically relevant patient outcomes must be proved in future clinical trials.

A European International Multicentre Survey on the Current Practice of Perioperative Antibiotic Prophylaxis for Paediatric Liver Transplantations

(1) Background: Postoperative infections are major contributors of morbidity and mortality after paediatric liver transplantation (pLTX). Evidence and recommendations regarding the most effective antimicrobial strategy are lacking. (2) Results: Of 39 pLTX centres, 20 responded. Aminopenicillins plus ß-lactamase inhibitors were used by six (30%) and third generation cephalosporins by three (15%), with the remaining centres reporting heterogenous regimens. Broad-spectrum regimens were the standard in 10 (50%) of centres and less frequent in the 16 (80%) centres with an infectious disease specialist. The duration ranged mainly between 24-48 h and 3-5 days in the absence and 3-5 days or 6-10 days in the presence of risk factors. Strategies regarding antifungal, antiviral, adjunctive antimicrobial, and surveillance strategies varied widely. (3) Methods: This international multicentre survey endorsed by the European Liver Transplant Registry queried all European pLTX centres from the registry on their current practice of perioperative antibiotic prophylaxis and antimicrobial strategies via an online questionnaire. (4) Conclusions: This survey found great heterogeneity regarding all aspects of postoperative antimicrobial treatment, surveillance, and prevention of infections in European pLTX centres. Evidence-based recommendations are urgently needed to optimise antimicrobial strategies and reduce the spectrum and duration of antimicrobial exposure.

Impact of an electronic alert system for pediatric sepsis screening a tertiary hospital experience

This study aimed to assess the potential impact of implementing an electronic alert system (EAS) for systemic inflammatory syndrome (SIRS) and sepsis in pediatric patients mortality. This retrospective study had a pre and post design. We enrolled patients aged ≤ 14 years who were diagnosed with sepsis/severe sepsis upon admission to the pediatric intensive care unit (PICU) of our tertiary hospital from January 2014 to December 2018. We implemented an EAS for the patients with SIRS/sepsis. The patients who met the inclusion criteria pre-EAS implementation comprised the control group, and the group post-EAS implementation was the experimental group. Mortality was the primary outcome, while length of stay (LOS) and mechanical ventilation in the first hour were the secondary outcomes. Of the 308 enrolled patients, 147 were in the pre-EAS group and 161 in the post-EAS group. In terms of mortality, 44 patients in the pre-EAS group and 28 in the post-EAS group died (p 0.011). The average LOS in the PICU was 7.9 days for the pre-EAS group and 6.8 days for the post-EAS group (p 0.442). Considering the EAS initiation time as the "zero time", early recognition of SIRS and sepsis via the EAS led to faster treatment interventions in post-EAS group, which included fluid boluses with median (25th, 75th percentile) time of 107 (37, 218) min vs. 30 (11,112) min, p < 0.001) and time to initiate antimicrobial therapy median (25th, 75th percentile) of 170.5 (66,320) min vs. 131 (53,279) min, p 0.042). The difference in mechanical ventilation in the first hour of admission was not significant between the groups (25.17% vs. 24.22%, p 0.895). The implementation of the EAS resulted in a statistically significant reduction in the mortality rate among the patients admitted to the PICU in our study. An EAS can play an important role in saving lives and subsequent reduction in healthcare costs. Further enhancement of systematic screening is therefore highly recommended to improve the prognosis of pediatric SIRS and sepsis. The implementation of the EAS, warrants further validation in multicenter or national studies.

Paediatric and neonatal sepsis and inflammation

Sepsis has a huge impact on global mortality and has been declared as a priority by the World Health organisation the WHO.1 Children have a high incidence of sepsis especially in the neonatal with an estimated 3 million babies affected worldwide and mortality ranges from 11 to 19%.2 In addition, long-term neurodevelopmental outcomes are affected but this is largely unquantified. However, challenges remain in the early recognition, diagnosis and standardised management of sepsis. This series on Sepsis and inflammation in children reviews the conundrums of diagnostic criteria, biomarkers, management and future strategies to improve outcomes.