Population-based Novel Molecular Diagnostics to Move the Neonatal Sepsis Agenda Forward
Notice bibliographique
Résumé
Although mortality in children younger than 5 years decreased globally by 39% from 9.9 million in 2000 to 5.9 million in 2015,1 mortality in neonates fell only 32% from 4 million to 2.7 million during the same period of time. As a result, the proportion of neonatal deaths in children younger than 5 years increased from 38% to 45%,2 and this has led to an heightened focus on reducing neonatal mortality. Most neonatal deaths continue to be because of 3 major causes: preterm birth, intrapartum complications (birth asphyxia) and neonatal sepsis/meningitis/pneumonia that are also known as possible severe bacterial infections (pSBIs).1 A recent systematic review estimated that the incidence of neonatal infection globally in 2012 was between 5.5 and 8.3 million and the average case fatality rate was 9.8%.3 Interventions, such as simplified antibiotic regimens for outpatient-based treatment of neonatal pSBI where timely hospitalization is not feasible,4,5 have the potential to reduce global mortality from pSBI, but there is ever increasing concern about the emergence of antimicrobial resistance in the community and health facilities where women are being encouraged to deliver their babies. A recent systematic review and meta-analysis found that resistance rates to penicillin and gentamicin versus third-generation cephalosporins were 43% and 44%, respectively,6 meaning that first-line antibiotic regimens for hospitalized neonates (ampicillin/penicillin and gentamicin) and simplified regimens for neonates (amoxicillin and gentamicin) are potentially already compromised globally although neonates with pSBI still responded clinically to penicillin/amoxicillin-based and gentamicin-based regimens in outpatients.4,5,7 The majority of the studies contributing to the systematic review/meta-analysis included children taken to hospitals, rather than children with pSBI/neonatal sepsis in the community who may not be taken to hospitals with microbiologic laboratories. The diagnosis of neonatal sepsis/pSBI is challenging even in well-equipped tertiary care facilities in resource-rich settings.8,9 In settings where there is limited or no access to microbiologic, hematologic and biochemical laboratory diagnostic tools, the World Health Organization’s (WHO) Integrated Management of Childhood Illness algorithm is used to make a clinical diagnosis pSBI, which encompasses neonatal sepsis/meningitis/pneumonia.10 However, the symptoms are nonspecific and can vary by language, cultural perspectives and the educational level of those providing information. The algorithm, initially developed after the first WHO Young Infants Study in the 1990s, found 14 clinical signs and symptoms that had a reasonable sensitivity to predict isolation of bacteria in blood or cerebrospinal fluid, or culture-positive severe bacterial disease.11 These signs and symptoms were simplified to the presence of any 1 of 7 clinical signs, and symptoms that predicted severe illness (based on an expert pediatrician’s assessment) in the second WHO Young Infants Clinical Signs Study.10 However, the signs and symptoms of Young Infants Clinical Signs Study were not evaluated against blood or cerebrospinal fluid culture results, so the diagnosis likely includes respiratory distress associated with preterm birth, birth asphyxia and viral respiratory infections. Based on available data, it is still recommended that neonates with these signs and symptoms be referred to a hospital and treated for pSBI. So it is clear that diagnosis of pSBI/neonatal sepsis is difficult, and studies based in hospitals may not capture the range of pathogens that cause pSBI/neonatal sepsis in the community. Given the new threats of antimicrobial resistance in the neonates who do present to referral facilities, the Aetiology of Neonatal Infections in South Asia study (ANISA) was initiated in 2010. The study was conceptualized by Child Health Research Foundation and Bill & Melinda Gates Foundation recognizing the urgent need to understand the organisms causing neonatal sepsis mortality and to determine appropriate interventions needed to reduce the burden of pSBI/neonatal sepsis. To manage this large initiative, ANISA project leadership at Child Health Research Foundation established a collaborative partnership of multiple organizations including the Centers for Disease Control and Prevention, United States, the WHO, Switzerland, International Centre for Diarrhoeal Disease Research, Bangladesh, University of Toronto, Canada, Oxford University, United Kingdom, and Johns Hopkins University, United States. The project coordination team worked together with the local institutions in Bangladesh, India and Pakistan to establish 5 study sites in South Asia. In this supplement, the bold and innovative methods to study the etiology of community-based neonatal sepsis are described. ANISA’s strengths include (1) being a community-based study with a centralized data management system supported by Short Message Service for important study-related communications, (2) use of innovative and novel diagnostics, (3) standardized approaches to diagnosis of pSBI/neonatal sepsis, training and laboratory-based methods at all sites, (4) monitoring by WHO and Centers for Disease Control and Prevention experts as well as external and internal quality control procedures, state-of-the-art monitoring and quality control through data-based systems and also physical visits by study personnel and external monitors to all sites following standardized check lists and (5) and most importantly use of labeling and tracking systems for processing of samples. Another unique feature of ANISA was the selection of controls using automated Short Message Service to address the interpretation of novel diagnostics—what would be found in neonates with real infections and what would be found in healthy neonates who did not have any illness. Finally, the ANISA team obtained complete clinical details of the neonates diagnosed with pSBI, their clinical course and outcomes so that it was possible to correlate clinical outcomes with the novel diagnostics and use a rigorous approach to ascertain whether isolated organisms were real pathogens or contaminants. ANISA focused on South Asia where there is a highest burden of pSBI/neonatal sepsis, but did not have any African site where the burden is also very high. The ANISA sites had low rates of HIV-infected and exposed infants. There is an urgent need for a parallel study in sub-Saharan Africa that leverages the results of ANISA. It is time for the cousin of ANISA–ANISSA (Aetiology of Neonatal Infections in Sub Saharan Africa) with addition of some new innovative approaches to make a difference in neonatal mortality globally. ANISA and ANISSA have to tell us about antimicrobial resistance patterns to pathogens causing neonatal infections as neonates globally just cannot be left behind.
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Comment cette classification a été obtenuedéplier
Prédiction machine sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,012 | 0,048 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,002 | 0,002 |
| Bibliométrie | 0,002 | 0,002 |
| Études des sciences et des technologies | 0,000 | 0,001 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,003 | 0,003 |
| Intégrité de la recherche | 0,004 | 0,005 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,024 | 0,004 |
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 source (Gemma direct ou Codex distillé), 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 ».