Less is more: Antibiotics at the beginning of life.

Antibiotic exposure at the beginning of life can lead to increased antimicrobial resistance and perturbations of the developing microbiome. Early-life microbiome disruption increases the risks of developing chronic diseases later in life. Fear of missing evolving neonatal sepsis is the key driver for antibiotic overtreatment early in life. Bias (a systemic deviation towards overtreatment) and noise (a random scatter) affect the decision-making process. In this perspective, we advocate for a factual approach quantifying the burden of treatment in relation to the burden of disease balancing antimicrobial stewardship and effective sepsis management

Analysis of Antibiotic Exposure and Early-Onset Neonatal Sepsis in Europe, North America, and Australia.

IMPORTANCE Appropriate use of antibiotics is life-saving in neonatal early-onset sepsis (EOS), but overuse of antibiotics is associated with antimicrobial resistance and long-term adverse outcomes. Large international studies quantifying early-life antibiotic exposure along with EOS incidence are needed to provide a basis for future interventions aimed at safely reducing neonatal antibiotic exposure. OBJECTIVE To compare early postnatal exposure to antibiotics, incidence of EOS, and mortality among different networks in high-income countries. DESIGN, SETTING, AND PARTICIPANTS This is a retrospective, cross-sectional study of late-preterm and full-term neonates born between January 1, 2014, and December 31, 2018, in 13 hospital-based or population-based networks from 11 countries in Europe and North America and Australia. The study included all infants born alive at a gestational age greater than or equal to 34 weeks in the participating networks. Data were analyzed from October 2021 to March 2022. EXPOSURES Exposure to antibiotics started in the first postnatal week. MAIN OUTCOMES AND MEASURES The main outcomes were the proportion of late-preterm and full-term neonates receiving intravenous antibiotics, the duration of antibiotic treatment, the incidence of culture-proven EOS, and all-cause and EOS-associated mortality. RESULTS A total of 757 979 late-preterm and full-term neonates were born in the participating networks during the study period; 21 703 neonates (2.86%; 95% CI, 2.83%-2.90%), including 12 886 boys (59.4%) with a median (IQR) gestational age of 39 (36-40) weeks and median (IQR) birth weight of 3250 (2750-3750) g, received intravenous antibiotics during the first postnatal week. The proportion of neonates started on antibiotics ranged from 1.18% to 12.45% among networks. The median (IQR) duration of treatment was 9 (7-14) days for neonates with EOS and 4 (3-6) days for those without EOS. This led to an antibiotic exposure of 135 days per 1000 live births (range across networks, 54-491 days per 1000 live births). The incidence of EOS was 0.49 cases per 1000 live births (range, 0.18-1.45 cases per 1000 live births). EOS-associated mortality was 3.20% (12 of 375 neonates; range, 0.00%-12.00%). For each case of EOS, 58 neonates were started on antibiotics and 273 antibiotic days were administered. CONCLUSIONS AND RELEVANCE The findings of this study suggest that antibiotic exposure during the first postnatal week is disproportionate compared with the burden of EOS and that there are wide (up to 9-fold) variations internationally. This study defined a set of indicators reporting on both dimensions to facilitate benchmarking and future interventions aimed at safely reducing antibiotic exposure in early life

Cost impact of procalcitonin-guided decision making on duration of antibiotic therapy for suspected early-onset sepsis in neonates

Abstract Backgrounds The large, international, randomized controlled NeoPInS trial showed that procalcitonin (PCT)-guided decision making was superior to standard care in reducing the duration of antibiotic therapy and hospitalization in neonates suspected of early-onset sepsis (EOS), without increased adverse events. This study aimed to perform a cost-minimization study of the NeoPInS trial, comparing health care costs of standard care and PCT-guided decision making based on the NeoPInS algorithm, and to analyze subgroups based on country, risk category and gestational age. Methods Data from the NeoPInS trial in neonates born after 34 weeks of gestational age with suspected EOS in the first 72 h of life requiring antibiotic therapy were used. We performed a cost-minimization study of health care costs, comparing standard care to PCT-guided decision making. Results In total, 1489 neonates were included in the study, of which 754 were treated according to PCT-guided decision making and 735 received standard care. Mean health care costs of PCT-guided decision making were not significantly different from costs of standard care (€3649 vs. €3616). Considering subgroups, we found a significant reduction in health care costs of PCT-guided decision making for risk category ‘infection unlikely’ and for gestational age ≥ 37 weeks in the Netherlands, Switzerland and the Czech Republic, and for gestational age < 37 weeks in the Czech Republic. Conclusions Health care costs of PCT-guided decision making of term and late-preterm neonates with suspected EOS are not significantly different from costs of standard care. Significant cost reduction was found for risk category ‘infection unlikely,’ and is affected by both the price of PCT-testing and (prolonged) hospitalization due to SAEs

Machine learning used to compare the diagnostic accuracy of risk factors, clinical signs and biomarkers and to develop a new prediction model for neonatal early-onset sepsis

Background: Current strategies for risk stratification and prediction of neonatal early-onset sepsis (EOS) are inefficient and lack diagnostic performance. The aim of this study was to use machine learning to analyze the diagnostic accuracy of risk factors (RFs), clinical signs and biomarkers and to develop a prediction model for culture-proven EOS. We hypothesized that the contribution to diagnostic accuracy of biomarkers is higher than of RFs or clinical signs. Study Design: Secondary analysis of the prospective international multicenter NeoPInS study. Neonates born after completed 34 weeks of gestation with antibiotic therapy due to suspected EOS within the first 72 hours of life participated. Primary outcome was defined as predictive performance for culture-proven EOS with variables known at the start of antibiotic therapy. Machine learning was used in form of a random forest classifier. Results: One thousand six hundred eighty-five neonates treated for suspected infection were analyzed. Biomarkers were superior to clinical signs and RFs for prediction of culture-proven EOS. C-reactive protein and white blood cells were most important for the prediction of the culture result. Our full model achieved an area-under-the-receiver-operating-characteristic-curve of 83.41% (±8.8%) and an area-under-the-precision-recall-curve of 28.42% (±11.5%). The predictive performance of the model with RFs alone was comparable with random. Conclusions: Biomarkers have to be considered in algorithms for the management of neonates suspected of EOS. A 2-step approach with a screening tool for all neonates in combination with our model in the preselected population with an increased risk for EOS may have the potential to reduce the start of unnecessary antibiotics

C-Reactive Protein, Procalcitonin, and White Blood Count to Rule Out Neonatal Early-onset Sepsis Within 36 Hours: A Secondary Analysis of the Neonatal Procalcitonin Intervention Study.

BACKGROUND: Neonatal early-onset sepsis (EOS) is one of the main causes of global neonatal mortality and morbidity, and initiation of early antibiotic treatment is key. However, antibiotics may be harmful. METHODS: We performed a secondary analysis of results from the Neonatal Procalcitonin Intervention Study, a prospective, multicenter, randomized, controlled intervention study. The primary outcome was the diagnostic accuracy of serial measurements of C-reactive protein (CRP), procalcitonin (PCT), and white blood count (WBC) within different time windows to rule out culture-positive EOS (proven sepsis). RESULTS: We analyzed 1678 neonates with 10 899 biomarker measurements (4654 CRP, 2047 PCT, and 4198 WBC) obtained within the first 48 hours after the start of antibiotic therapy due to suspected EOS. The areas under the curve (AUC) comparing no sepsis vs proven sepsis for maximum values of CRP, PCT, and WBC within 36 hours were 0.986, 0.921, and 0.360, respectively. The AUCs for CRP and PCT increased with extended time frames up to 36 hours, but there was no further difference between start to 36 hours vs start to 48 hours. Cutoff values at 16 mg/L for CRP and 2.8 ng/L for PCT provided a sensitivity of 100% for discriminating no sepsis vs proven sepsis. CONCLUSIONS: Normal serial CRP and PCT measurements within 36 hours after the start of empiric antibiotic therapy can exclude the presence of neonatal EOS with a high probability. The negative predictive values of CRP and PCT do not increase after 36 hours

Completeness of reporting of quality improvement studies in neonatology is inadequate: a systematic literature survey

Introduction Quality improvement (QI) is a growing field of inquiry in healthcare, but the reporting quality of QI studies in neonatology remains unclear. We conducted a systematic survey of the literature to assess the reporting quality of QI studies and factors associated with reporting quality.Methods We searched Medline for publications of QI studies from 2016 to 16 April 2020. Pairs of reviewers independently screened citations and assessed reporting quality using a 31-item modified Standards for Quality Improvement Reporting Excellence, 2nd edition (SQUIRE 2.0) checklist. We reported the number (percentage) of studies that reported each item and their corresponding 95% CIs. We used Poisson regression to explore factors associated with reporting quality, namely, journal endorsement of SQUIRE 2.0, declaration of funding sources, year of publication and number of authors. The results were reported as incidence rate ratio (IRR) and 95% CI.Results Of 1921 citations, 336 were eligible; among them, we randomly selected 100 articles to assess reporting quality. The mean (standard deviation) number of SQUIRE 2.0 items adhered to was 22.0 (4.5). Percentage of articles reporting each item varied from 26% to 100%. Journal endorsement of SQUIRE 2.0 (IRR=1.11, 95% CI 1.02 to 1.21, p=0.015), declaration of funding sources and increasing number of authors were significantly associated with better reporting.Conclusions Reporting quality of QI studies in neonatology is inadequate. Endorsing the SQUIRE 2.0 guideline is a step that journals can implement to enhance the completeness of reporting

Cost impact of procalcitonin-guided decision making on duration of antibiotic therapy for suspected early-onset sepsis in neonates

BACKGROUNDS The large, international, randomized controlled NeoPInS trial showed that procalcitonin (PCT)-guided decision making was superior to standard care in reducing the duration of antibiotic therapy and hospitalization in neonates suspected of early-onset sepsis (EOS), without increased adverse events. This study aimed to perform a cost-minimization study of the NeoPInS trial, comparing health care costs of standard care and PCT-guided decision making based on the NeoPInS algorithm, and to analyze subgroups based on country, risk category and gestational age. METHODS Data from the NeoPInS trial in neonates born after 34 weeks of gestational age with suspected EOS in the first 72 h of life requiring antibiotic therapy were used. We performed a cost-minimization study of health care costs, comparing standard care to PCT-guided decision making. RESULTS In total, 1489 neonates were included in the study, of which 754 were treated according to PCT-guided decision making and 735 received standard care. Mean health care costs of PCT-guided decision making were not significantly different from costs of standard care (€3649 vs. €3616). Considering subgroups, we found a significant reduction in health care costs of PCT-guided decision making for risk category 'infection unlikely' and for gestational age ≥ 37 weeks in the Netherlands, Switzerland and the Czech Republic, and for gestational age < 37 weeks in the Czech Republic. CONCLUSIONS Health care costs of PCT-guided decision making of term and late-preterm neonates with suspected EOS are not significantly different from costs of standard care. Significant cost reduction was found for risk category 'infection unlikely,' and is affected by both the price of PCT-testing and (prolonged) hospitalization due to SAEs

Variation in Current Management of Term and Late-preterm Neonates at Risk for Early-onset Sepsis: An International Survey and Review of Guidelines.

Uncertainty about the presence of infection results in unnecessary and prolonged empiric antibiotic treatment of newborns at risk for early-onset sepsis (EOS). This study evaluates the impact of this uncertainty on the diversity in management. A web-based survey with questions addressing management of infection risk-adjusted scenarios was performed in Europe, North America, and Australia. Published national guidelines (n = 5) were reviewed and compared with the results of the survey. 439 Clinicians (68% were neonatologists) from 16 countries completed the survey. In the low-risk scenario, 29% would start antibiotic therapy and 26% would not, both groups without laboratory investigations; 45% would start if laboratory markers were abnormal. In the high-risk scenario, 99% would start antibiotic therapy. In the low-risk scenario, 89% would discontinue antibiotic therapy before 72 hours. In the high-risk scenario, 35% would discontinue therapy before 72 hours, 56% would continue therapy for 5-7 days, and 9% for more than 7 days. Laboratory investigations were used in 31% of scenarios for the decision to start, and in 72% for the decision to discontinue antibiotic treatment. National guidelines differ considerably regarding the decision to start in low-risk and regarding the decision to continue therapy in higher risk situations. There is a broad diversity of clinical practice in management of EOS and a lack of agreement between current guidelines. The results of the survey reflect the diversity of national guidelines. Prospective studies regarding management of neonates at risk of EOS with safety endpoints are needed

Machine Learning Used to Compare the Diagnostic Accuracy of Risk Factors, Clinical Signs and Biomarkers and to Develop a New Prediction Model for Neonatal Early-onset Sepsis

BACKGROUND Current strategies for risk stratification and prediction of neonatal early-onset sepsis (EOS) are inefficient and lack diagnostic performance. The aim of this study was to use machine learning to analyze the diagnostic accuracy of risk factors (RFs), clinical signs and biomarkers and to develop a prediction model for culture-proven EOS. We hypothesized that the contribution to diagnostic accuracy of biomarkers is higher than of RFs or clinical signs. STUDY DESIGN Secondary analysis of the prospective international multicenter NeoPInS study. Neonates born after completed 34 weeks of gestation with antibiotic therapy due to suspected EOS within the first 72 hours of life participated. Primary outcome was defined as predictive performance for culture-proven EOS with variables known at the start of antibiotic therapy. Machine learning was used in form of a random forest classifier. RESULTS One thousand six hundred eighty-five neonates treated for suspected infection were analyzed. Biomarkers were superior to clinical signs and RFs for prediction of culture-proven EOS. C-reactive protein and white blood cells were most important for the prediction of the culture result. Our full model achieved an area-under-the-receiver-operating-characteristic-curve of 83.41% (±8.8%) and an area-under-the-precision-recall-curve of 28.42% (±11.5%). The predictive performance of the model with RFs alone was comparable with random. CONCLUSIONS Biomarkers have to be considered in algorithms for the management of neonates suspected of EOS. A 2-step approach with a screening tool for all neonates in combination with our model in the preselected population with an increased risk for EOS may have the potential to reduce the start of unnecessary antibiotics

Remote ischemic conditioning in necrotizing enterocolitis: study protocol of a multi-center phase II feasibility randomized controlled trial

PURPOSE: Remote ischemic conditioning (RIC) is a maneuver involving brief cycles of ischemia reperfusion in an individual's limb. In the early stage of experimental NEC, RIC decreased intestinal injury and prolonged survival by counteracting the derangements in intestinal microcirculation. A single-center phase I study demonstrated that the performance of RIC was safe in neonates with NEC. The aim of this phase II RCT was to evaluate the safety and feasibility of RIC, to identify challenges in recruitment, retainment, and to inform a phase III RCT to evaluate efficacy. METHODS: RIC will be performed by trained research personnel and will consist of four cycles of limb ischemia (4-min via cuff inflation) followed by reperfusion (4-min via cuff deflation), repeated on two consecutive days post randomization. The primary endpoint of this RCT is feasibility and acceptability of recruiting and randomizing neonates within 24 h from NEC diagnosis as well as masking and completing the RIC intervention. RESULTS: We created a novel international consortium for this trial and created a consensus on the diagnostic criteria for NEC and protocol for the trial. The phase II multicenter-masked feasibility RCT will be conducted at 12 centers in Canada, USA, Sweden, The Netherlands, UK, and Spain. The inclusion criteria are: gestational age < 33 weeks, weight ≥ 750 g, NEC receiving medical treatment, and diagnosis established within previous 24 h. Neonates will be randomized to RIC (intervention) or no-RIC (control) and will continue to receive standard management of NEC. We expect to recruit and randomize 40% of eligible patients in the collaborating centers (78 patients; 39/arm) in 30 months. Bayesian methods will be used to combine uninformative prior distributions with the corresponding observed proportions from this trial to determine posterior distributions for parameters of feasibility. CONCLUSIONS: The newly established NEC consortium has generated novel data on NEC diagnosis and defined the feasibility parameters for the introduction of a novel treatment in NEC. This phase II RCT will inform a future phase III RCT to evaluate the efficacy and safety of RIC in early-stage NEC