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Enregistrement W4404105559 · doi:10.1159/000541384

The Effectiveness of Regionalization of Perinatal Care and Specific Facility-Based Interventions: A Systematic Review

2024· review· en· W4404105559 sur OpenAlexaff
Ayesha Arshad Ali, Hamna Amir Naseem, Zoha Allahuddin, Rahima Yasin, Maha Azhar, Sawera Hanif, Jai K Das, Zulfiqar A Bhutta

Notice bibliographique

RevueNeonatology · 2024
Typereview
Langueen
DomaineMedicine
ThématiqueGlobal Maternal and Child Health
Établissements canadiensHospital for Sick Children
Organismes subventionnairesnon disponible
Mots-clésPsychological interventionMedicineSystematic reviewMEDLINEEnvironmental healthPediatricsNursing

Résumé

récupéré en direct d'OpenAlex

INTRODUCTION: Appropriate perinatal care provision and utilization is crucial to improve maternal and newborn survival and potentially meet Sustainable Development Goal 3. Ensuring availability of healthcare infrastructure as well as skilled personnel can potentially help improve maternal and neonatal outcomes globally as well as in resource-limited settings. METHODS: A systematic review on effectiveness of perinatal care regionalization was updated, and a new review on facility-based interventions to improve postnatal care coverage and outcomes was conducted. The interventions were identified through literature reviews and included transport, mHealth, telemedicine, maternal education, capacity building, and incentive packages. Search was conducted in relevant databases and meta-analysis conducted on Review Manager 5.4. We conducted subgroup analysis for evidence from low- and middle-income countries (LMICs). RESULTS: Implementation of regionalization programs significantly decreased maternal mortality in LMICs (OR: 0.43; 95% CI: 0.34-0.55, 2 studies), stillbirth overall (OR: 0.70; 95% CI: 0.54-0.89, 5 studies), perinatal mortality overall (OR: 0.54; 95% CI: 0.5-0.58, 2 studies), and LMICs (OR: 0.54; 95% CI: 0.50-0.58, 1 study). Transport-related interventions significantly decreased maternal mortality overall (OR: 0.55; 95% CI: 0.40-0.74, 1 study), neonatal mortality (RR: 0.76; 95% CI: 0.66-0.88, 1 study), perinatal mortality (RR: 0.86; 95% CI: 0.77-0.95, 1 study), and improved postnatal care coverage (OR: 6.89; 95% CI: 5.15-9.21, 1 study) in LMICs. Adding maternity homes/units significantly decreased stillbirth (OR: 0.75; 95% CI: 0.61-0.93, 1 study) in LMICs. Incentives for postnatal care significantly improved infant mortality (RR: 0.79; 95% CI: 0.65-0.96, 1 study), stillbirth (OR: 0.60; 95% CI: 0.44-0.83, 1 study), and postnatal care coverage (RR: 1.13; 95% CI: 1.03-1.25, 1 study) in LMICs. Telemedicine improved postnatal care coverage significantly in LMICs (RR: 2.54; 95% CI: 1.22-5.28, 3 studies) and decreased maternal mortality (OR: 0.46; 95% CI: 0.21-0.98, 1 study) and infant mortality (OR: 0.65; 95% CI: 0.45-0.95) in LMICs. Maternal education significantly decreased neonatal mortality (RR: 0.75; 95% CI: 0.66-0.84, 2 studies), perinatal mortality (RR: 0.86; 95% CI: 0.77-0.95, 1 study), infant mortality (RR: 0.79; 95% CI: 0.65-0.96, 1 study), and stillbirth (RR: 0.61; 95% CI: 0.45-0.82, 1 study). Capacity-building interventions significantly decreased maternal mortality in LMICs (OR: 0.37; 95% CI: 0.29-0.46, 5 studies), neonatal mortality overall (OR: 0.72; 95% CI: 0.53-0.98, 4 studies) and in LMICs (OR: 0.63; 95% CI: 0.54-0.74, 3 studies, and RR: 0.61; 95% CI: 0.48-0.79, 3 studies), perinatal mortality (OR: 0.53; 95% CI: 0.45-0.62, 2 studies, and RR: 0.86; 95% CI: 0.77-0.95, 1 study), infant mortality (OR: 0.50; 95% CI: 0.43-0.59, 1 study, and RR: 0.79; 95% CI: 0.65-0.96, 1 study), under-5 mortality (RR: 0.79; 95% CI: 0.66-0.94, 1 study), and stillbirth in LMICs (OR: 0.71; 95% CI: 0.62-0.82, 4 studies), and preterm birth overall (OR: 0.39; 95% CI: 0.19-0.81, 1 study). CONCLUSION: Perinatal regionalization and facility-based interventions have a positive impact on maternal and neonatal outcomes and calls for implementation in high burden settings but a better understanding of optimal interventions is needed through comprehensive trials in diverse settings. INTRODUCTION: Appropriate perinatal care provision and utilization is crucial to improve maternal and newborn survival and potentially meet Sustainable Development Goal 3. Ensuring availability of healthcare infrastructure as well as skilled personnel can potentially help improve maternal and neonatal outcomes globally as well as in resource-limited settings. METHODS: A systematic review on effectiveness of perinatal care regionalization was updated, and a new review on facility-based interventions to improve postnatal care coverage and outcomes was conducted. The interventions were identified through literature reviews and included transport, mHealth, telemedicine, maternal education, capacity building, and incentive packages. Search was conducted in relevant databases and meta-analysis conducted on Review Manager 5.4. We conducted subgroup analysis for evidence from low- and middle-income countries (LMICs). RESULTS: Implementation of regionalization programs significantly decreased maternal mortality in LMICs (OR: 0.43; 95% CI: 0.34-0.55, 2 studies), stillbirth overall (OR: 0.70; 95% CI: 0.54-0.89, 5 studies), perinatal mortality overall (OR: 0.54; 95% CI: 0.5-0.58, 2 studies), and LMICs (OR: 0.54; 95% CI: 0.50-0.58, 1 study). Transport-related interventions significantly decreased maternal mortality overall (OR: 0.55; 95% CI: 0.40-0.74, 1 study), neonatal mortality (RR: 0.76; 95% CI: 0.66-0.88, 1 study), perinatal mortality (RR: 0.86; 95% CI: 0.77-0.95, 1 study), and improved postnatal care coverage (OR: 6.89; 95% CI: 5.15-9.21, 1 study) in LMICs. Adding maternity homes/units significantly decreased stillbirth (OR: 0.75; 95% CI: 0.61-0.93, 1 study) in LMICs. Incentives for postnatal care significantly improved infant mortality (RR: 0.79; 95% CI: 0.65-0.96, 1 study), stillbirth (OR: 0.60; 95% CI: 0.44-0.83, 1 study), and postnatal care coverage (RR: 1.13; 95% CI: 1.03-1.25, 1 study) in LMICs. Telemedicine improved postnatal care coverage significantly in LMICs (RR: 2.54; 95% CI: 1.22-5.28, 3 studies) and decreased maternal mortality (OR: 0.46; 95% CI: 0.21-0.98, 1 study) and infant mortality (OR: 0.65; 95% CI: 0.45-0.95) in LMICs. Maternal education significantly decreased neonatal mortality (RR: 0.75; 95% CI: 0.66-0.84, 2 studies), perinatal mortality (RR: 0.86; 95% CI: 0.77-0.95, 1 study), infant mortality (RR: 0.79; 95% CI: 0.65-0.96, 1 study), and stillbirth (RR: 0.61; 95% CI: 0.45-0.82, 1 study). Capacity-building interventions significantly decreased maternal mortality in LMICs (OR: 0.37; 95% CI: 0.29-0.46, 5 studies), neonatal mortality overall (OR: 0.72; 95% CI: 0.53-0.98, 4 studies) and in LMICs (OR: 0.63; 95% CI: 0.54-0.74, 3 studies, and RR: 0.61; 95% CI: 0.48-0.79, 3 studies), perinatal mortality (OR: 0.53; 95% CI: 0.45-0.62, 2 studies, and RR: 0.86; 95% CI: 0.77-0.95, 1 study), infant mortality (OR: 0.50; 95% CI: 0.43-0.59, 1 study, and RR: 0.79; 95% CI: 0.65-0.96, 1 study), under-5 mortality (RR: 0.79; 95% CI: 0.66-0.94, 1 study), and stillbirth in LMICs (OR: 0.71; 95% CI: 0.62-0.82, 4 studies), and preterm birth overall (OR: 0.39; 95% CI: 0.19-0.81, 1 study). CONCLUSION: Perinatal regionalization and facility-based interventions have a positive impact on maternal and neonatal outcomes and calls for implementation in high burden settings but a better understanding of optimal interventions is needed through comprehensive trials in diverse settings.

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 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: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,166
Score d'incertitude au seuil0,365

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0010,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0020,001
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 Opus0,034
Tête enseignante GPT0,369
Écart entre enseignants0,336 · 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

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeRevue systématique
Domainenon disponible
GenreSynthèse

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations7
Publié2024
Routes d'admission1
Résumé présentoui

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