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There is limited data on antibiotic treatment in hospitalized neonates in low- and middle-income countries (LMICs). We aimed to describe patterns of antibiotic use, pathogens, and clinical outcomes, and to develop a severity score predicting mortality in neonatal sepsis to inform future clinical trial design. Hospitalized infants <60 days with clinical sepsis were enrolled during 2018 to 2020 by 19 sites in 11 countries (mainly Asia and Africa). Prospective daily observational data was collected on clinical signs, supportive care, antibiotic treatment, microbiology, and 28-day mortality. Two prediction models were developed for (1) 28-day mortality from baseline variables (baseline NeoSep Severity Score); and (2) daily risk of death on IV antibiotics from daily updated assessments (NeoSep Recovery Score). Multivariable Cox regression models included a randomly selected 85% of infants, with 15% for validation. A total of 3,204 infants were enrolled, with median birth weight of 2,500 g (IQR 1,400 to 3,000) and postnatal age of 5 days (IQR 1 to 15). 206 different empiric antibiotic combinations were started in 3,141 infants, which were structured into 5 groups based on the World Health Organization (WHO) AWaRe classification. Approximately 25.9% (n = 814) of infants started WHO first line regimens (Group 1-Access) and 13.8% (n = 432) started WHO second-line cephalosporins (cefotaxime/ceftriaxone) (Group 2-\"Low\" Watch). The largest group (34.0%, n = 1,068) started a regimen providing partial extended-spectrum beta-lactamase (ESBL)/pseudomonal coverage (piperacillin-tazobactam, ceftazidime, or fluoroquinolone-based) (Group 3-\"Medium\" Watch), 18.0% (n = 566) started a carbapenem (Group 4-\"High\" Watch), and 1.8% (n = 57) a Reserve antibiotic (Group 5, largely colistin-based), and 728/2,880 (25.3%) of initial regimens in Groups 1 to 4 were escalated, mainly to carbapenems, usually for clinical deterioration (n = 480; 65.9%). A total of 564/3,195 infants (17.7%) were blood culture pathogen positive, of whom 62.9% (n = 355) had a gram-negative organism, predominantly Klebsiella pneumoniae (n = 132) or Acinetobacter spp. (n = 72). Both were commonly resistant to WHO-recommended regimens and to carbapenems in 43 (32.6%) and 50 (71.4%) of cases, respectively. MRSA accounted for 33 (61.1%) of 54 Staphylococcus aureus isolates. Overall, 350/3,204 infants died (11.3%; 95% CI 10.2% to 12.5%), 17.7% if blood cultures were positive for pathogens (95% CI 14.7% to 21.1%, n = 99/564). A baseline NeoSep Severity Score had a C-index of 0.76 (0.69 to 0.82) in the validation sample, with mortality of 1.6% (3/189; 95% CI: 0.5% to 4.6%), 11.0% (27/245; 7.7% to 15.6%), and 27.3% (12/44; 16.3% to 41.8%) in low (score 0 to 4), medium (5 to 8), and high (9 to 16) risk groups, respectively, with similar performance across subgroups. A related NeoSep Recovery Score had an area under the receiver operating curve for predicting death the next day between 0.8 and 0.9 over the first week. There was significant variation in outcomes between sites and external validation would strengthen score applicability. Antibiotic regimens used in neonatal sepsis commonly diverge from WHO guidelines, and trials of novel empiric regimens are urgently needed in the context of increasing antimicrobial resistance (AMR). The baseline NeoSep Severity Score identifies high mortality risk criteria for trial entry, while the NeoSep Recovery Score can help guide decisions on regimen change. NeoOBS data informed the NeoSep1 antibiotic trial (ISRCTN48721236), which aims to identify novel first- and second-line empiric antibiotic regimens for neonatal sepsis. ClinicalTrials.gov, (NCT03721302).

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. Fear of missing neonatal sepsis has led to early in life antibiotic administration, even without culture-proven sepsis. Here, the authors discuss the potential impact on antimicrobial resistance, and chronic disease later in life, due to effect on the developing microbiome, suggesting a factual based approach in quantifying burden of treatment in relation to the burden of disease.

The expert guidelines highlighted in this review provide an evidence-based framework for approaching at-risk infants and allow for a more limited and standardised approach to antibiotic use. While these guidelines have significantly reduced antibiotic utilisation worldwide, optimally each unit would individualise their approach to early onset sepsis (EOS) based on the neonatal population they serve and available resources. As advancements in EOS research continue and limitations with sepsis prediction tools are addressed, it is inevitable that our risk stratification and management guidelines will become more precise.

Sepsis remains a significant cause of neonatal morbidity and mortality in China. A better understanding of neonatal sepsis in China as compared with other industrialized and non-industrialized countries may help optimize neonatal health care both regionally and globally. Literature cited in this review was retrieved from PubMed using the keywords \"neonatal sepsis,\" \"early-onset (EOS)\" and \"late-onset (LOS)\" in English, with the focus set on population-based studies. This review provides an updated summary regarding the epidemiology, pathogen profile, infectious work-up, and empirical treatment of neonatal sepsis within and beyond China. The incidence of neonatal EOS and the proportion of Group B Streptococcus (GBS) within pathogens causing EOS in China seem to differ from those in developed countries, possibly due to different population characteristics and intrapartum/postnatal health care strategies. Whether to adopt GBS screening and intrapartum antibiotic prophylaxis in China remains highly debatable. The pathogen profile of LOS in China was shown to be similar to other countries. However, viruses as potential pathogens of neonatal LOS have been underappreciated. Growing antimicrobial resistance in China reflects limitations in adapting antibiotic regimen to local microbial profile and timely cessation of treatment in non-proven bacterial infections. This review stresses that the local epidemiology of neonatal sepsis should be closely monitored in each institution. A prompt and adequate infectious work-up is critically important in diagnosing neonatal sepsis. Adequate and appropriate antibiotic strategies must be overemphasized to prevent the emergence of multi-resistant bacteria in China.

ObjectiveAssess the impact of introducing a consensus guideline incorporating an adapted Sepsis Risk Calculator (SRC) algorithm, in the management of early onset neonatal sepsis (EONS), on antibiotic usage and patient safety.DesignMulticentre prospective studySettingTen perinatal hospitals in Wales, UK.PatientsAll live births ≥34 weeks’ gestation over a 12-month period (April 2019–March 2020) compared with infants in the preceding 15-month period (January 2018–March 2019) as a baseline.MethodsThe consensus guideline was introduced in clinical practice on 1 April 2019. It incorporated a modified SRC algorithm, enhanced in-hospital surveillance, ongoing quality assurance, standardised staff training and parent education. The main outcome measure was antibiotic usage/1000 live births, balancing this with analysis of harm from delayed diagnosis and treatment, disease severity and readmissions from true sepsis. Outcome measures were analysed using statistical process control charts.Main outcome measuresProportion of antibiotic use in infants ≥34 weeks’ gestation.Results4304 (14.3%) of the 30 105 live-born infants received antibiotics in the baseline period compared with 1917 (7.7%) of 24 749 infants in the intervention period (45.5% mean reduction). All 19 infants with culture-positive sepsis in the postimplementation phase were identified and treated appropriately. There were no increases in sepsis-related neonatal unit admissions, disease morbidity and late readmissions.ConclusionsThis multicentre study provides evidence that a judicious adaptation of the SRC incorporating enhanced surveillance can be safely introduced in the National Health Service and is effective in reducing antibiotic use for EONS without increasing morbidity and mortality.

Background Use of serum procalcitonin (PCT), an inflammatory biomarker for bacterial infections, has shown promising results for early stopping antibiotic treatment among patients with respiratory infections and sepsis. There is need for additional data regarding effectiveness and safety of this concept among patients with cancer. Methods Individual data of patients with a documented diagnosis of cancer and proven or suspected respiratory infection and/or sepsis were extracted from previous trials where adult patients were randomized to receive antibiotic treatment based on a PCT protocol or usual care (control group). The primary efficacy and safety endpoints were antibiotic exposure and 28-day all-cause mortality. Results This individual-patient data meta-analysis included 777 patients with a diagnosis of cancer from 15 randomized-controlled trials. Regarding efficacy, there was a 18% reduction in antibiotic exposure in patients randomized to PCT-guided care compared to usual care ([days] 8.2 ± 6.6 vs. 9.8 ± 7.3; adjusted difference, − 1.77 [95% CI, − 2.74 to − 0.80]; p  < 0.001). Regarding safety, there were 72 deaths in 379 patients in the PCT-guided group (19.0%) compared to 91 deaths in 398 participants in the usual care group (22.9%) resulting in an adjusted OR of 0.78 (95% CI, 0.60 to 1.02). A subgroup analysis showed a significant reduction in mortality in patients younger than 70 years (adjusted OR, 0.58 [95% CI, 0.40 to 0.86]). Conclusion Result of this individual patient meta-analysis from 15 previous trials suggests that among patients with cancer and suspected or proven respiratory infection or sepsis, use of PCT to guide antibiotic treatment decisions results in reduced antibiotic exposure with a possible reduction in mortality, particularly among younger patients.

Retrospective virtual application of the National Institute for Health and Care Excellence (NICE) guidelines for neonatal infection 2021 compared with Kaiser Permanente Sepsis Risk Calculator (KP-SRC) and previous NICE guidelines 2012. NICE 2021 may reduce this to 4.4% and KP-SRC may reduce it to 2.7%, treating those recommended both culture and antibiotics.Table 1 Estimated percentages of live births >34 weeks receiving antibiotics in postnatal settings, following virtual application of NICE 2021 guidelines and KP-SRC Live births total January–February 2020 Current practice Abx NICE 2012 applied* KP-SRC 2/1000 Abx indicated plus NICE 2012* KP-SRC 2/1000 Abx and culture indicated plus NICE 2012* NICE 2021* KP-SRC 2/1000 Abx indicated plus NICE 2021* KP-SRC 2/1000 Abx and culture indicated plus NICE 2021* n 7833 624 572 118 306 346 103 209 % 8.0 7.3 1.5 3.9 4.4 1.3 2.7 NICE 2012: LM (1), SS (2), TvH (2), NM (2), AKE (2,3), PS (1), Paediatric Research Across the Midlands (PRAM) Network: (1) Birmingham Heartlands Hospital, (2) Birmingham Women’s and Children’s NHS Foundation Trust, (3) Institute of Metabolism and Systems Research, University of Birmingham.

Neonatal sepsis is a leading cause of mortality and morbidity. To improve the clinical outcomes of neonates with sepsis, treatment should be based on bacteriological identification and antibiotic susceptibility. This study aims to assess the proportion of culture-positive gram-negative bacteria (GNB), the antibiotic susceptibility patterns, and treatment outcomes of neonatal sepsis at two neonatal intensive care units (NICUs) in Addis Ababa. A retrospective observational study was conducted among gram-negative sepsis suspected neonates admitted at Zewditu Memorial Hospital and Tikur Anbessa Specialized Hospital NICUs from January to December 2023. All neonates who were suspected of having sepsis were included in this study. Standard microbiological culture and biochemical tests were used to identify bacterial species and the Kirby-Bauer disc diffusion assay using Mueller-Hinton agar was employed to test the antimicrobial susceptibility of bacterial isolates as per Clinical Laboratory Standard Institute guidelines. Descriptive statistics were used to describe the study variables. Bivariable and multivariable logistic regression analyses were used to identify the factors associated with the treatment outcomes of neonatal sepsis. A p-value < 0.05 was set for statistical significance. A total of 933 neonates were diagnosed with sepsis during the study period, of which 166 neonates were enrolled in the study for gram-negative sepsis: 84 (51%) were female and 97 (58%) had early onset sepsis. The median length of hospital stay was nine days with interquartile range of 16 days. The predominant GNB identified was Klebsiella spp. (n = 89; 49%), followed by Acinetobacter spp. (n = 38; 21%) and Escherichia coli (n = 19; 11%). In both hospitals, Klebsiella spp. was resistant to most of the routinely prescribed antibiotics: (n = 68; 89%) were resistant to ceftriaxone, (n = 56, 89%) cefepime and (n = 60; 75%) to gentamicin. Lower rates of resistance were recorded for other antibiotics such as ciprofloxacin (n = 12; 18%), ertapenem (n = 11; 16%), meropenem (n = 9; 13%), and amikacin (n = 3; 4%). A total of 92 (55%) neonates with the GNB isolated in the current study had multidrug-resistant (MDR) organisms. The study found that newborns with MDR infections were five times more likely to experience poor treatment outcomes compared to those with non-resistant strains (AOR, 5.23 95% CI [2.59, 11.11]). In addition, newborns who stayed less than seven days, compared to those who spent seven or more days in the hospital was four times (AOR: 4.16, 95% CI (2.0-9.01) more likely to experience poor health outcomes. Klebsiella spp. was the most common GNB isolated from the NICUs. More than half neonatal sepsis was caused by MDR organisms and associated with significant poor treatment outcomes. high prevalence of MDR-gram-negative bacteremia is alarming and highlights the need for the implementation of routine surveillance and infection control measures to decrease morbidity and mortality and to combat the development of antimicrobial resistance.

ObjectivesWe studied neonates with suspected early-onset sepsis (EOS, sepsis developing in the first 72 hours after delivery) in Malawi to (1) describe clinical characteristics and microbiological findings, (2) identify which patient characteristics may be associated with pathogen positivity on blood culture, and (3) describe mortality and its potential determinants.DesignProspective observational study (May 2018–June 2019).SettingNeonatal ward in Queen Elizabeth Central Hospital, the largest government hospital in Malawi.PatientsAll neonates with suspected EOS in whom a blood culture was obtained.ResultsOut of 4308 neonatal admissions, 1244 (28.9%) had suspected EOS. We included 1149 neonates, of which 109 blood cultures had significant growth (9.5%). The most commonly isolated pathogens were Staphylococcus aureus, Klebsiella pneumoniae, Enterobacter cloacae, Escherichia coli and Acinetobacter baumanii. Many of the Gram negatives were extended-spectrum beta lactamase-producing Enterobacteriaceae, and these were 40–100% resistant to first-line and second-line antimicrobials. Gestational age (GA) of <32 weeks was associated with pathogen-positive blood cultures (<28 weeks: adjusted OR (AOR) 2.72, 95% CI 1.04 to 7.13; 28–32 weeks: AOR 2.26, 95% CI 1.21 to 4.21; p=0.005). Mortality was 17.6% (202/1149) and associated with low birth weight (<1000 g: AOR 47.57, 95% CI 12.59 to 179.81; 1000–1500 g: AOR 11.31, 95% CI 6.97 to 18.36; 1500–2500 g: AOR 2.20, 95% CI 1.42 to 3.39; p<0.001), low Apgar scores at 5 min (0–3: AOR 18.60, 95% CI 8.81 to 39.27; 4–6: AOR 4.41, 95% CI 2.81 to 6.93; p<0.001), positive maternal venereal disease research laboratory status (AOR 2.53, 95% CI 1.25 to 5.12; p=0.001) and congenital anomalies (AOR 7.37, 95% CI 3.61 to 15.05; p<0.001). Prolonged rupture of membranes was inversely associated with mortality (AOR 0.43, 95% CI 0.19 to 0.98; p 0.007).ConclusionIn Malawi, EOS was suspected in nearly a third of neonatal admissions and had a high mortality. Ten per cent were culture-confirmed and predicted by low GA. To reduce the impact of suspected neonatal sepsis in least developed countries, improved maternal and antenatal care and development of rapid point of care methods to more accurately guide antimicrobial use could simultaneously improve outcome and reduce antimicrobial resistance.

Introduction Neonatal sepsis is a major cause of health loss and mortality worldwide. Without proper treatment, neonatal sepsis can quickly develop into multisystem organ failure. However, the signs of neonatal sepsis are non-specific, and treatment is labour-intensive and expensive. Moreover, antimicrobial resistance is a significant threat globally, and it has been reported that over 70% of neonatal bloodstream infections are resistant to first-line antibiotic treatment. Machine learning is a potential tool to aid clinicians in diagnosing infections and in determining the most appropriate empiric antibiotic treatment, as has been demonstrated for adult populations. This review aimed to present the application of machine learning on neonatal sepsis treatment. Methods PubMed, Embase, and Scopus were searched for studies published in English focusing on neonatal sepsis, antibiotics, and machine learning. Results There were 18 studies included in this scoping review. Three studies focused on using machine learning in antibiotic treatment for bloodstream infections, one focused on predicting in-hospital mortality associated with neonatal sepsis, and the remaining studies focused on developing machine learning prediction models to diagnose possible sepsis cases. Gestational age, C-reactive protein levels, and white blood cell count were important predictors to diagnose neonatal sepsis. Age, weight, and days from hospital admission to blood sample taken were important to predict antibiotic-resistant infections. The best-performing machine learning models were random forest and neural networks. Conclusion Despite the threat antimicrobial resistance poses, there was a lack of studies focusing on the use of machine learning for aiding empirical antibiotic treatment for neonatal sepsis.