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Record W4407894973 · doi:10.1542/peds.2024-069575

Tackling Antibiotic Stewardship Challenges in the Neonatal Intensive Care Unit Through Rigorous Quality Improvement

2025· article· en· W4407894973 on OpenAlexaboutno aff
Jeffrey Meyers

Bibliographic record

VenuePEDIATRICS · 2025
Typearticle
Languageen
FieldMedicine
TopicNeonatal and Maternal Infections
Canadian institutionsnot available
Fundersnot available
KeywordsMedicineIntensive care medicineNeonatal intensive care unitSepsisAntibioticsAntibiotic StewardshipRetinopathy of prematurityAntimicrobial stewardshipNeonatal sepsisNecrotizing enterocolitisIntensive careIntensive care unitPediatricsAntibiotic resistanceInternal medicinePregnancyGestational ageMicrobiology

Abstract

fetched live from OpenAlex

Antibiotic stewardship in the neonatal intensive care unit (NICU) has drawn much attention over the last decade following reports of antibiotic overuse and unexplained prescribing variation1,2 and reports showing association between antibiotic use and multiple adverse outcomes, including necrotizing enterocolitis, late-onset sepsis, retinopathy of prematurity, and bronchopulmonary dysplasia.3–6 Antibiotic use has also been linked with emergence of fungal infections, multidrug-resistant bacteria, and disturbances in the developing microbiome.7–9 In response, emphasis has been placed on quality improvement (QI) to drive antibiotic stewardship, with many local unit-based initiatives as well as larger-scale collaboratives reporting important efforts safely reducing antibiotic use in the NICU and neonatal care.10–12 In this issue of Pediatrics, the articles by Juliano et al13 and Paul et al14 offer valuable contributions to this growing literature, describing use of QI for antibiotic stewardship in level 4 NICUs with a specific focus on reducing antibiotic use for culture-negative sepsis.The authors should be applauded for addressing a challenging area of antibiotic use in the NICU. Culture-negative sepsis is clinical illness presumed to represent bacterial infection despite lack of definitive evidence, such as a positive culture. The diagnosis of culture-negative sepsis is uncertain, and treatment at best is a “gray” area. Previous studies suggest that antibiotic use in the NICU for culture-negative sepsis is substantially more than for culture-positive sepsis. For example, a recent study involving more than 100 000 births from 15 Dutch hospitals found that for every 1 case of early-onset culture-positive sepsis, 20 additional newborns received prolonged empirical antibiotics.15 Likewise, a single-center study from a level 3 NICU in the US reported that 26% of all antibiotic use was due to antibiotic use for 5 days or more in the setting of sterile cultures, whereas only 5% was for culture-positive sepsis.16 This discrepancy is likely driven by multiple factors, such as nonspecific clinical manifestations of sepsis, limitations in predictive abilities of biomarkers and other diagnostic tests, and the risks of missing sepsis, the most concerning of which is death.17 However, these 2 reports highlight that not only is improvement work needed in gray areas of antibiotic stewardship, but it is entirely possible. By using evidence to support the safety of a 5-day antibiotic course for culture-negative sepsis18 and through application of rigorous QI methodology, both Juliano et al and Paul et al have observed significant and sustained improvements in antibiotic use for culture-negative sepsis.Both teams described well-designed initiatives with multidisciplinary involvement and clearly defined aims. The authors developed an understanding of their current state and used a driver diagram to display their team’s theory for improvement. Interestingly, these 2 initiatives tested similar interventions: development of written guidelines to standardize practice, a formal process to document and/or discuss antibiotic indication through use of an antibiotic necessity statement (Paul et al) or antibiotic stewardship rounds (Juliano et al), and use of frequent audits and feedback for prescribing providers. Both initiatives used clearly defined outcome, process, and balancing measures and tracked outcome and process measures over time using statistical process control charts. The conclusions regarding reduction in antibiotic use in both articles were based on well-accepted rules for detecting special cause variation. The reductions in antibiotic use for culture-negative sepsis in both units have been sustained for more than 18 months, further strengthening the belief that both QI initiatives have resulted in meaningful and lasting improvement—the ultimate goal of all improvement work.The interventions described by Juliano et al and Paul et al are strategies known to enhance system reliability in health care, such as those proposed by the Institute for Healthcare Improvement (IHI).19 In the IHI’s model, reliability is enhanced using a 3-step model: (1) prevent failure, (2) identify and mitigate failure, and (3) redesign the process after identifying critical failures. In these articles, at least 2 of these steps can be identified. First, developing written guidelines for culture-negative sepsis works to prevent failures by promoting a standardized or uniform approach, such as through defining an expected duration of antibiotic treatment of 5 days. Second, use of antibiotic necessity statements, antibiotic stewardship rounds, and frequent audits/feedback are all strategies these teams used to identify and mitigate deviations from the desired or standard approach, which in these units might be antibiotic duration longer than 5 days when cultures remain sterile. Importantly, the interventions described in both manuscripts seem feasible and if implemented together may yield comparable results in most NICUs.Given the increasing frequency with which QI manuscripts are being published, critical evaluation tools for QI are needed. Ideally, these tools should prompt evaluation of the report’s adherence to the stated QI methodology being employed and encourage the reader to consider if and how they might apply aspects of the published report in their own setting. Discerning rigorous from nonrigorous QI is important because poorly done QI carries risks. Examples of such risks include: Failing to understand the current state, resulting in tests of change that do not adequately address the root cause(s) of the outcome of interest;Solely using education and/or other tests of change that focus on the lowest level of reliability, which decreases the likelihood of sustained improvements;Inability to link changes/improvements in process measures with the outcome measure, limiting the ability to conclude that changes in the process led to improvement;Inappropriate/misapplication of rules for detecting special cause variation, resulting in erroneous conclusions as to whether improvement in the outcome has occurred; andInability for readers to learn from and potentially apply lessons learned, limiting generalizability.The Quality Improvement Minimum Quality Criteria Set was the first proposed framework for critical appraisal of QI and suggests that minimum standards be present for the QI report to be considered high quality.20 The Quality Improvement Critical Knowledge (QUICK) Tool was recently developed to assist health care providers in evaluating the rigor, validity, and generalizability of improvement work and ultimately facilitate the application of QI manuscripts to clinical practice and/or local QI efforts.21 This tool prompts readers with questions across 3 sections that assess for robust methodology, presence or absence of improvement, and applicability of the results to the reader’s own setting. Evaluating the reports by Juliano et al and Paul et al using the QUICK Tool is a useful exercise. Both reports described a QI project that was well designed (clear scope of problem, well-described context and setting, interdisciplinary team involvement, clear aim statement), used a theory for improvement (driver diagram) and tested changes that enhanced the reliability of the system, described outcome and process measures that were tracked over time using control charts, appropriately applied rules for detecting special cause variation, and observed sustained improvements. Both reports also confirmed safety of their interventions through a similar balancing measure: antibiotic reinitiation.Some limitations are also noted. Paul et al relied heavily on education as a test of change, which is necessary but often not sufficient for sustained improvements. This likely explains the increase in the antibiotic utilization rate for culture-negative sepsis observed in July 2023, which represented undesired special cause variation. In the report by Juliano et al, some interventions were not described as an iterative process of testing and lack sufficient detail from which to learn, such as antibiotic stewardship rounds. In addition, it is not clear what changes the authors believed were most important in decreasing the number of treatment courses for culture-negative sepsis and days of therapy for early-onset culture-negative sepsis, especially since special cause variation occurred at different times for these outcomes. These limitations do not seem to substantially detract from the value of the manuscripts but should be considered as providers explore similar initiatives in their units. Importantly, while both teams worked in level 4 NICUs caring for infants needing the most advanced care,22 every NICU regardless of size or designated level provides care to babies being evaluated for possible infection, making these manuscripts broadly relevant and applicable.Other gray areas exist when it comes to antibiotic stewardship in the NICU, and the neonatal community should consider ways to address these equally challenging conditions. Congenital pneumonia and ventilator-associated pneumonia (VAP), for example, lack clear, well-accepted definitions for diagnosis and have similar presentations to other noninfectious respiratory conditions for which antibiotics are not indicated.23 These respiratory infections often lack an identifiable infecting organism, and tracheal aspirates have demonstrated poor sensitivity and specificity for diagnosing true disease.24,25 As a result of this diagnostic uncertainty, significant variability in practice has followed. For instance, 52% of Canadian Neonatal Network NICUs surveyed in 2019 indicated that the diagnosis of VAP is made entirely at physician discretion, with variable diagnostic criteria applied in diagnosing VAP among 37% of centers.26 Despite diagnostic uncertainty, congenital pneumonia and VAP remain common diagnoses for which antibiotics are prescribed in the NICU. One concept that may prove useful in these gray areas is diagnostic stewardship. Strategies used in diagnostic stewardship have traditionally promoted accurate, timely diagnosis to foster appropriate antimicrobial administration.27 In addition, diagnostic stewardship efforts may also serve to promote a standard approach to evaluation and management of infectious conditions, limit unnecessary use of poorly performing diagnostic tests, and decrease unwanted variability.Moving forward, it is likely that both ongoing research and QI efforts will be required to drive additional antibiotic stewardship efforts in these challenging, gray areas of neonatal care. At the very least, these 2 reports should challenge all of us to continually improve the care we provide the babies and families we serve, even when there is diagnostic uncertainty.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.427
Threshold uncertainty score0.395

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.063
GPT teacher head0.352
Teacher spread0.289 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations1
Published2025
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