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Enregistrement W3132110757 · doi:10.1016/s2589-7500(21)00025-x

Evaluating neonatal medical devices in Africa

2021· article· en· W3132110757 sur OpenAlex
Amy Sarah Ginsburg, William Macharia, J. Mark Ansermino

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Notice bibliographique

RevueThe Lancet Digital Health · 2021
Typearticle
Langueen
DomaineMedicine
ThématiqueGlobal Maternal and Child Health
Établissements canadiensUniversity of British Columbia
Organismes subventionnairesBill and Melinda Gates Foundation
Mots-clésMedicinePsychological interventionChild mortalityNeonatal mortalityInfant mortalityMortality rateMalariaDemographyEnvironmental healthPediatricsPopulationNursing

Résumé

récupéré en direct d'OpenAlex

Globally, 47% of deaths of children younger than 5 years occur within the first 28 days of life, with sub-Saharan Africa bearing the greatest burden with the average neonatal mortality rate being 28 deaths per 1000 livebirths.1UN Inter-agency Group for Child Mortality EstimationLevels and trends in child mortality 2019: estimates developed by the UN Inter-agency group for child mortality estimation. UNICEF, New York2019Google Scholar Neonatal death can be prevented by achieving high coverage of high-quality, evidence-based, and timely interventions. To meet the Sustainable Development Goal target of reducing global neonatal mortality to 12 deaths per 1000 livebirths by 2030, accelerated improvements and innovations in neonatal care in Africa, particularly technologies that allow for early detection and intervention for major morbidities, are needed to reduce current and projected neonatal mortality rates.2Hug L Alexander M You D Alkema L National, regional, and global levels and trends in neonatal mortality between 1990 and 2017, with scenario-based projections to 2030: a systematic analysis.Lancet Glob Health. 2019; 7: e710-e720Summary Full Text Full Text PDF PubMed Scopus (245) Google Scholar Yet, very few point-of-care devices have been developed and evaluated specifically for the diagnosis and management of at-risk neonates in Africa. Robust literature exists regarding insecticide-treated bed nets for malaria prevention and point-of-care HIV testing, but few technologies exist for the targeting of improved outcomes in neonates. Devices developed for and evaluated in older populations cannot be made smaller to fit the needs of neonates. Similarly, devices developed for and evaluated in high-resource settings cannot simply be transferred to low-resource settings without appropriate customisation, validation, and feasibility evaluation. Barriers to the availability of devices for neonates in Africa include the scarcity of testing in vulnerable populations, hesitancy around the ethics of testing, and little understanding of the use cases, regulatory pathways, and market dynamics for new devices. These challenges contribute to inadequate device development and evaluation focused on at-risk neonates in African settings. The need for rigorous testing and robust clinical trials are major logistical and financial obstacles for device developers, especially when such testing and trials need to be done in low-resource settings. Initial investigational devices include selected non-invasive, multiparameter, continuous physiological monitoring (MCPM) technologies, which are used to identify and monitor at-risk neonates and direct care through automated interpretations of vital signs. Although continuous physiological monitoring is the standard-of-care in high-resource settings, which helps identify crucial events and establish the adequacy of treatment in at-risk neonates that ultimately improves newborn outcomes,3Zhu Z Liu T Li G Li T Inoue Y Wearable sensor systems for infants.Sensors (Basel). 2015; 15: 3721-3749Crossref PubMed Scopus (116) Google Scholar, 4Sahni R Continuous noninvasive monitoring in the neonatal ICU.Curr Opin Pediatr. 2017; 29: 141-148Crossref PubMed Scopus (10) Google Scholar, 5Shah PS Wireless monitoring in the ICU on the horizon.Nat Med. 2020; 26: 316-317Crossref PubMed Scopus (3) Google Scholar the devices are expensive and require specialised training to operate, making them unsuitable for application in low-resource settings. To address these barriers, exploration of how locally appropriate MCPM devices and other neonatal technologies can be developed, adapted, or optimised for safe and effective use in low-resource settings is necessary. Ideally, the devices should be non-invasive, robust in harsh environments, easy to use and maintain with little training, highly efficient in performance and operator workload, and low in cost with affordable disposable components. The goal would be that incorporating MCPM devices into care would improve health-care capacity, efficiency, and quality by allowing providers to monitor multiple neonates simultaneously. Although these devices can be used as a vehicle for improving health care, they are not sufficient by themselves; therefore, appropriate staffing, education, training, and support are also necessary.6de Graft-Johnson J Vesel L Rosen HE et al.Cross-sectional observational assessment of quality of newborn care immediately after birth in health facilities across six sub-Saharan African countries.BMJ Open. 2017; 7e014680Crossref PubMed Scopus (34) Google Scholar, 7Kawaza K Kinshella MW Hiwa T et al.Assessing quality of newborn care at district facilities in Malawi.BMC Health Serv Res. 2020; 20: 227Crossref PubMed Scopus (9) Google Scholar Furthermore, understanding and addressing these challenges, and any barriers and facilitators to uptake and adoption will be key for successful implementation and scale-up. The Evaluation of Technologies for Neonates in Africa (ETNA) platform was conceived to advance and support the development and robust evaluation of point-of-care devices and digital tools, specifically for the management of at-risk neonates in Africa, where the need for such tools is greatest.8Ginsburg AS Nkwopara E Macharia W et al.Evaluation of non-invasive continuous physiological monitoring devices for neonates in Nairobi, Kenya: a research protocol.BMJ Open. 2020; 10e035184Crossref PubMed Scopus (10) Google Scholar The ETNA testing platform provides essential opportunities for technology optimisation through iterative rounds of clinical testing and re-evaluation in the target population. We are exploring whether selected investigational MCPM devices that have already been tested for safety can accurately and reliably measure vital signs in neonates (when compared with verified reference devices), and we are assessing the feasibility, usability, and acceptability of these devices for use in neonates.8Ginsburg AS Nkwopara E Macharia W et al.Evaluation of non-invasive continuous physiological monitoring devices for neonates in Nairobi, Kenya: a research protocol.BMJ Open. 2020; 10e035184Crossref PubMed Scopus (10) Google Scholar We are working to anticipate the many challenges (eg, unreliable electricity, limited internet access and reliability, and behaviour change communication) involved in implementing such devices in low-resource settings, and the need to consider these challenges carefully before the introduction of these devices. The ETNA testing platform allows high quality independent and objective validation to inform strategic decision making, thus overcoming barriers faced by any individual technology developer or manufacturer that might not have the expertise and resources for the clinical trials. The evaluation process enables crucial insights to technology developers and manufacturers into the proposed use environment and formal end-user feedback on feasibility, usability, and acceptability. Early differentiation of technologies that are unlikely to succeed can occur, ensuring that additional resources are not invested in technologies that might not work. The platform fills the gap of translating validation studies, which include the rigorous and independent evaluation of candidate devices, and publish the results into peer-reviewed publications to provide pivotal information for regulatory approval and help drive demand and adoption by health-care facilities and providers, equipment distributors, supply chain stakeholders, and procurement organisations. The range of activities within the ETNA platform will identify and cultivate technology champions within the health-care and industry value chains and allow opportunities for local technology innovators to contribute. Additional gains in locally appropriate technologies will require investment in local entrepreneurship and commercialisation. This crucial knowledge translation process will become the cornerstone of future marketing and market-shaping strategies. The ETNA platform provides essential steps in the development and evaluation of high quality, evidence-based, and timely point-of-care health technologies for the management of at-risk neonates in Africa, transforming prototypes into products and catalysing the transition to scale. We declare no competing interests. We received financial support from the Bill & Melinda Gates Foundation. The funder had no role in the writing of the manuscript or the decision to submit for publication.

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.

Prédiction distillée sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: aucune
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,611
Score d'incertitude au seuil0,222

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0000,000
Bibliométrie0,0000,000
Études des sciences et des technologies0,0000,000
Communication savante0,0000,000
Science ouverte0,0000,000
Intégrité de la recherche0,0000,000
Charge utile insuffisante (le modèle a refusé de juger)0,0000,000

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.

Tête enseignante Opus0,088
Tête enseignante GPT0,404
Écart entre enseignants0,316 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle