Neonatal sepsis: a systematic review of core outcomes from randomised clinical trials

Identifying outcomes and outcome measures in neonatal family-centered care trials: a systematic review

BACKGROUND

A wide range of outcomes for infants and parents has been reported in clinical trials testing FCC interventions. This systematic review aimed to identify outcomes, outcome measures, and time-points reported in experimental studies testing FCC interventions in neonatal care units.

METHODS

This review included experimental studies investigating FCC interventions in neonatal settings. Database searches were conducted in MEDLINE, EMBASE, CINAHL, Cochrane, PsycINFO, Scopus, JBI, Lilacs, and SciELO, completed in December 2022 and updated in November 2023. Critical appraisal was performed using the JBI checklist for randomized controlled trials, and a narrative synthesis process was used. Outcomes were categorized into the Comet Taxonomy core areas.

RESULTS

The search identified 8787 papers; 42 studies were included in the analysis. Totally, 60 outcomes were identified: 42 infant and 18 parents' outcomes. Outcomes were clustered into 12 domains for infants and five domains for parents and measured by 97 outcome measures. The included studies reported 25 and 27 different time-points for infants and parents, respectively.

CONCLUSION

This review of studies testing FCC interventions identified heterogeneity and inconsistency of outcomes, outcome measures, and time-points measuring the outcomes. Developing a core outcome set for FCC studies is warranted to benchmark the evidence and identify best-practices.

IMPACT

This systematic review identified inconsistency of outcomes, outcome measures, and time-points reported in quantitative studies testing family-centered care interventions in neonatal care settings. The lack of standardized outcomes and outcome measures reported in clinical trials makes it difficult to synthesize data to provide conclusive recommendations. This systematic review will contribute to the development of a core outcome set for research testing family-centered care interventions in neonatal care settings.

Outcomes of interventions in neonatal sepsis: A systematic review of qualitative research

BACKGROUND

While a systematic review exists detailing neonatal sepsis outcomes from clinical trials, there remains an absence of a qualitative systematic review capturing the perspectives of key stakeholders.

OBJECTIVES

Our aim is to identify outcomes from qualitative research on any intervention to prevent or improve the outcomes of neonatal sepsis that are important to parents, other family members, healthcare providers, policymakers, and researchers as a part of the development of a core outcome set (COS) for neonatal sepsis.

SEARCH STRATEGY

A literature search was carried out using MEDLINE, EMBASE, CINAHL, and PsycInfo databases.

SELECTION CRITERIA

Publications describing qualitative data relating to neonatal sepsis outcomes were included.

DATA COLLECTION AND ANALYSIS

Drawing on the concepts of thematic synthesis, texts related to outcomes were coded and grouped. These outcomes were then mapped to the domain headings of an existing model.

MAIN RESULTS

Out of 6777 records screened, six studies were included. Overall, 19 outcomes were extracted from the included studies. The most frequently reported outcomes were those in the domains related to parents, healthcare workers and individual organ systemas such as gastrointestinal system. The remaining outcomes were classified under the headings of general outcomes, miscellaneous outcomes, survival, and infection.

CONCLUSIONS

The outcomes identified in this review are different from those reported in neonatal sepsis clinical trials, thus highlighting the importance of incorporating qualitative studies into COS development to encapsulate all relevant stakeholders' perspectives.

Neonatal sepsis and cardiovascular dysfunction I: mechanisms and pathophysiology

The highest incidence of sepsis across all age groups occurs in neonates leading to substantial mortality and morbidity. Cardiovascular dysfunction frequently complicates neonatal sepsis including biventricular systolic and/or diastolic dysfunction, vasoregulatory failure, and pulmonary arterial hypertension. The haemodynamic response in neonatal sepsis can be hyperdynamic or hypodynamic and the underlying pathophysiological mechanisms are heterogeneous. The diagnosis and definition of both neonatal sepsis and cardiovascular dysfunction complicating neonatal sepsis are challenging and not consensus-based. Future developments in neonatal sepsis management will be facilitated by common definitions and datasets especially in neonatal cardiovascular optimisation. IMPACT: Cardiovascular dysfunction is common in neonatal sepsis but there is no consensus-based definition, making calculating the incidence and designing clinical trials challenging. Neonatal cardiovascular dysfunction is related to the inflammatory response, which can directly target myocyte function and systemic haemodynamics.

Protocol for the development of a core outcome set for neonatal sepsis (NESCOS)

Neonatal sepsis is a serious public health problem; however, there is substantial heterogeneity in the outcomes measured and reported in research evaluating the effectiveness of the treatments. Therefore, we aim to develop a Core Outcome Set (COS) for studies evaluating the effectiveness of treatments for neonatal sepsis. Since a systematic review of key outcomes from randomised trials of therapeutic interventions in neonatal sepsis was published recently, we will complement this with a qualitative systematic review of the key outcomes of neonatal sepsis identified by parents, other family members, parent representatives, healthcare providers, policymakers, and researchers. We will interpret the outcomes of both studies using a previously established framework. Stakeholders across three different groups i.e., (1) researchers, (2) healthcare providers, and (3) patients' parents/family members and parent representatives will rate the importance of the outcomes in an online Real-Time Delphi Survey. Afterwards, consensus meetings will be held to agree on the final COS through online discussions with key stakeholders. This COS is expected to minimize outcome heterogeneity in measurements and publications, improve comparability and synthesis, and decrease research waste.

Developmental Pharmacokinetics of Antibiotics Used in Neonatal ICU: Focus on Preterm Infants

Neonatal Infections are among the most common reasons for admission to the intensive care unit. Neonatal sepsis (NS) significantly contributes to mortality rates. Empiric antibiotic therapy of NS recommended by current international guidelines includes benzylpenicillin, ampicillin/amoxicillin, and aminoglycosides (gentamicin). The rise of antibacterial resistance precipitates the growth of the use of antibiotics of the Watch (second, third, and fourth generations of cephalosporines, carbapenems, macrolides, glycopeptides, rifamycins, fluoroquinolones) and Reserve groups (fifth generation of cephalosporines, oxazolidinones, lipoglycopeptides, fosfomycin), which are associated with a less clinical experience and higher risks of toxic reactions. A proper dosing regimen is essential for effective and safe antibiotic therapy, but its choice in neonates is complicated with high variability in the maturation of organ systems affecting drug absorption, distribution, metabolism, and excretion. Changes in antibiotic pharmacokinetic parameters result in altered efficacy and safety. Population pharmacokinetics can help to prognosis outcomes of antibiotic therapy, but it should be considered that the neonatal population is heterogeneous, and this heterogeneity is mainly determined by gestational and postnatal age. Preterm neonates are common in clinical practice, and due to the different physiology compared to the full terms, constitute a specific neonatal subpopulation. The objective of this review is to summarize the evidence about the developmental changes (specific for preterm and full-term infants, separately) of pharmacokinetic parameters of antibiotics used in neonatal intensive care units.

Cardiorespiratory signature of neonatal sepsis: development and validation of prediction models in 3 NICUs

BACKGROUND

Heart rate characteristics aid early detection of late-onset sepsis (LOS), but respiratory data contain additional signatures of illness due to infection. Predictive models using cardiorespiratory data may improve early sepsis detection. We hypothesized that heart rate (HR) and oxygenation (SpO₂) data contain signatures that improve sepsis risk prediction over HR or demographics alone.

METHODS

We analyzed cardiorespiratory data from very low birth weight (VLBW, <1500 g) infants admitted to three NICUs. We developed and externally validated four machine learning models to predict LOS using features calculated every 10 m: mean, standard deviation, skewness, kurtosis of HR and SpO₂, and cross-correlation. We compared feature importance, discrimination, calibration, and dynamic prediction across models and cohorts. We built models of demographics and HR or SpO₂ features alone for comparison with HR-SpO₂ models.

RESULTS

Performance, feature importance, and calibration were similar among modeling methods. All models had favorable external validation performance. The HR-SpO₂ model performed better than models using either HR or SpO₂ alone. Demographics improved the discrimination of all physiologic data models but dampened dynamic performance.

CONCLUSIONS

Cardiorespiratory signatures detect LOS in VLBW infants at 3 NICUs. Demographics risk-stratify, but predictive modeling with both HR and SpO₂ features provides the best dynamic risk prediction.

IMPACT

Heart rate characteristics aid early detection of late-onset sepsis, but respiratory data contain signatures of illness due to infection. Predictive models using both heart rate and respiratory data may improve early sepsis detection. A cardiorespiratory early warning score, analyzing heart rate from electrocardiogram or pulse oximetry with SpO₂, predicts late-onset sepsis within 24 h across multiple NICUs and detects sepsis better than heart rate characteristics or demographics alone. Demographics risk-stratify, but predictive modeling with both HR and SpO₂ features provides the best dynamic risk prediction. The results increase understanding of physiologic signatures of neonatal sepsis.

Artificial and human intelligence for early identification of neonatal sepsis

Artificial intelligence may have a role in the early detection of sepsis in neonates. Machine learning can identify patterns that predict high or increasing risk for clinical deterioration from a sepsis-like illness. In developing this potential addition to NICU care, careful consideration should be given to the data and methods used to develop, validate, and evaluate prediction models. When an AI system alerts clinicians to a change in a patient's condition that warrants a bedside evaluation, human intelligence and experience come into play to determine an appropriate course of action: evaluate and treat or wait and watch closely. With intelligently developed, validated, and implemented AI sepsis systems, both clinicians and patients stand to benefit. IMPACT: This narrative review highlights the application of AI in neonatal sepsis prediction. It describes issues in clinical prediction model development specific to this population. This article reviews the methods, considerations, and literature on neonatal sepsis model development and validation. Challenges of AI technology and potential barriers to using sepsis AI systems in the NICU are discussed.