Editorial: Technologies for neonatal care in LMICs
Notice bibliographique
Résumé
Newborn babies are among the most vulnerable class of patients in any society. They are entirely incapable of surviving on their own without external help from caregivers and society. A poorly attended newborn will more likely die compared to another who received well-guided and knowledgeable care [1]. Therefore, the neonatal mortality rate of any society represents a quick measure of the efficiency of its healthcare system, available technologies, and knowledge base. It is common knowledge that the low-and middle-income countries (LMICs) disproportionately contribute over 98% of the global annual burden of neonatal deaths [2,3]. Limited access to sustainable affordable technologies for neonatal care is one of the major impediments in lowering neonatal mortality in LMICs [4]. Expensive medical equipment that works well in high income countries (HICs) may be unsustainable in LMICs due to poor operational infrastructure [5]. Thus making sophisticated technologies as applied in HICs both unaffordable and unsustainable in LMICs. However, a well-crafted basic technology, may be extremely affordable, easily maintainable by in-house technicians, and effective in saving lives.Therefore, we encouraged researchers to submit their practical demonstrations of applicable LMIC innovations to enable a Collection of crossbreed-able ideas for empowering the rest of the LMICs in neonatal care.Our Topic Collection has showcased ten rigorous research from 64 collaborating authors across many continents, drawing from easy-to-apply innovative technologies to address a variety of neonatal conditions. Singh et al. (India-Australia collaboration), explored the "diagnostic utility of lung ultrasound" in predicting when surfactant therapy is needed during neonatal respiratory support. They noted that lung pathologies for respiratory distress at birth have overlapping symptomatology with other conditions, hence the need to research the diagnostic accuracy of a cutoff for the lung ultrasound score (LUS) in predicting the need for surfactant therapy in neonatal respiratory distress. They corelated LUS and corresponding SPO2 to FiO2 in 100 neonates and found that LUS cutoff of 7 predicted the need for the first dose of surfactant.In another randomised controlled trial, Singh et al. compared the effect of Premature Infant Oral Motor Intervention (PIOMI) and routine oromotor stimulation (OMS) on oral feeding readiness.They concluded that PIOMI is a more effective oromotor stimulation method for improved oral feeding in preterm neonates. From the Republic of Korea, we have Hwang and Lee conduct a cross-sectional study, where safe-delivery kits were distributed to 534 mothers in Rural Ethiopian Communities to investigate the impacts this has on preventing newborn and maternal infection. The outcome demonstrates that single-use delivery kits decrease the likelihood of maternal infection, emphasizing the need for adoption in vulnerable countries to improve hygienic birthing, especially for deliveries outside healthcare facilities.Finally, a team of Nigeria-UK-Canada researchers-Amadi et al.-in their courtroom, "jury-style systematic review of 32 years of literature without significant mortality reduction", wondered why high neonatal-mortality-rate has persisted in Nigeria and some LMICs since the days of MDG_(4).They reviewed 4,286 publications but only 19 were assessed to possess potentials for reducing neonatal mortality, however, these remained largely unutilized by policymakers. Recommendation: LMIC healthcare systems may have to look inwards to strengthen identifiable game-changing discoveries they already possess.We invite organizations and policymakers of relevant countries to avail themselves of the rich contents of this Collection to implement a far-reaching neonatal life-saving campaign across LMICs-inspiring further research for inclusion in our next edition.Hippolite drafted the manuscript and contributed to its polishing and readiness. Tina, Olugbenga, and John contributed equally to the manuscript editing and polishing.
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 | 0,000 | 0,002 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,002 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,000 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,003 | 0,002 |
| 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; les deux têtes enseignantes s’accordent sur ce qui est montré ici.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».