Patterns of antibiotic use, pathogens and clinical outcomes in hospitalised neonates and young infants with sepsis in the NeoOBS global neonatal sepsis observational cohort study
Notice bibliographique
Résumé
Abstract Background Neonatal sepsis is a leading cause of child mortality, and increasing antimicrobial resistance threatens progress towards the Sustainable Development Goals. Evidence to guide antibiotic treatment for sepsis in neonates and young infants from randomized controlled trials or observational studies in low- and middle-income countries (LMICs) is scarce. We aimed to describe patterns of antibiotic use, pathogens and outcomes in LMIC hospital settings globally to inform future clinical trials on the management of neonatal sepsis. Methods & Findings Hospitalised infants aged <60 days with clinical sepsis were enrolled during 2018-2020 by 19 sites in 11 countries (mainly Asia and Africa). Prospective daily data was collected on clinical signs, supportive care, antibiotic treatment, microbiology and clinical outcome at 28 days. The study was observational, with no changes to routine clinical practice. 3204 infants were enrolled, with median birth weight 2500g (IQR 1400-3000) and postnatal age 5 days (IQR 2-15). Of 309 enrolled aged 28-60 days, 58.6% (n=181) were ex-preterm and/or a neonate at admission. 2215 (69%) infants had been in hospital since birth. 206 different empiric antibiotic combinations were used, which were structured into 5 groups that were developed from the World Health Organisation (WHO) AWaRe classification. 25.9% (n=814) of infants started a WHO first line regimen (Group 1 -Access, penicillin-based regimen) and 13.8% (n=432) started WHO second-line cephalosporins (cefotaxime/ceftriaxone) (Group 2- ‘Low’ Watch). The largest group (34.0%, n=1068) 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) started a Reserve antibiotic (Group 5, largely colistin-based). Predictors of starting non-WHO recommended regimens included lower birth weight, longer in-hospital stay, central vascular catheter use, previous culture positive sepsis or antibiotic exposure, previous surgery and greater sepsis severity. 728/2880 (25.3%) of initial regimens in Group 1-4 were escalated, mainly to carbapenems, and usually for clinical indications (n=480; 65.9%). 564 infants (17.6%) isolated a pathogen from their baseline blood culture, of which 62.9% (n=355) had a Gram-negative organism, predominantly Klebsiella pneumoniae (n=132) and Acinetobacter spp. (n=72). These leading Gram-negatives were both mostly resistant to WHO-recommended regimens, and also resistant to carbapenems in 32.6% and 71.4% of cases respectively. MRSA accounted for 61.1% of Staphylococcus aureus (n=54) isolates. Overall, 350/3204 infants died (11.3%; 95%CI 10.2-12.5%), with 17.7% case fatality rate among infants with a pathogen in baseline culture (95%CI 14.7-20.1%, n=99/564). Gram-negative infections accounted for 75/99 (75.8%) of pathogen-positive deaths, especially Klebsiella pneumoniae (n=28; 28.3%), and Acinetobacter spp. (n=24; 24.2%). Conclusion A very wide range of antibiotic regimens are now used to treat neonatal sepsis globally. There is common use of higher-level Watch antibiotics, frequent early switching and very infrequent de-escalation of therapy. Future hospital based neonatal sepsis trials will ideally need to account for the multiple regimens used as standard of care globally and include both empiric first line regimens and subsequent switching in the trial design. Author Summary Why was this study done? ➢ Increasing trends in antimicrobial resistance (AMR) disproportionately affect neonates and young infants with sepsis in LMIC settings and undermine the effectiveness of WHO-recommended antibiotics. ➢ Despite this, longitudinal data on antibiotic management strategies and outcomes of affected hospitalised neonates and young infants in LMIC settings are extremely limited, impeding the design of robust antibiotic trials. What did the researchers do and find? ➢ To our knowledge this is the first global, prospective, hospital-based observational study of clinically diagnosed neonatal sepsis across 4 continents including LMIC settings, with daily data on clinical status, antibiotic use and outcomes. ➢ There was a high mortality among infants with culture positive sepsis (almost 1 in 5), and a significant burden of antibiotic resistance. ➢ This study highlights wide variations in standard of care for sepsis in neonates and young infants with more than 200 different antibiotic combinations, significant divergence from WHO-recommended regimens, and frequent switching of antibiotics. What do these findings mean? ➢ These data demonstrate that patterns of routine antibiotic use are now markedly divergent from global guidance ➢ There is an urgent need for randomised controlled trials to address optimal empiric first and second line antibiotic treatment strategies in LMIC hospital settings with a significant AMR burden. ➢ Data from this study can inform the design of multicentre hospital-based neonatal antibiotic trials in LMIC settings. ➢ The wide range of multiple antibiotic regimens routinely used as Standard of Care (SOC) suggests the need for novel trial designs.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,001 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».