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Enregistrement W4403750060 · doi:10.1159/000541697

Optimal Strategies for Screening Common Birth Defects in Children of Low- and Middle-Income Countries: A Systematic Review

2024· review· en· W4403750060 sur OpenAlexaff
Umaima Zaki, Saqib Hamid Qazi, Urooj Shamim, Jai K Das, Zulfiqar A Bhutta

Notice bibliographique

RevueNeonatology · 2024
Typereview
Langueen
DomaineMedicine
ThématiqueCongenital Anomalies and Fetal Surgery
Établissements canadiensHospital for Sick Children
Organismes subventionnairesBill and Melinda Gates Foundation
Mots-clésMedicineGastroschisisOmphaloceleCINAHLPediatricsLow and middle income countriesMEDLINEPrenatal carePregnancyObstetricsDeveloping countryFetusPsychological interventionPopulationEnvironmental health

Résumé

récupéré en direct d'OpenAlex

INTRODUCTION: Congenital anomalies are one of the major causes of the global burden of diseases, and low- and middle-income countries (LMICs) are disproportionately affected. This review assesses the prenatal and postnatal screening methods and compares the prevalence of major congenital anomalies in LMICs. METHODOLOGY: We conducted a systematic search in MEDLINE/PubMed, CINAHL, Cochrane databases of systematic reviews, clinical trials.gov for relevant studies using Medical Subject Headings and keywords. We categorized the studies into different systems and screening methods depending on the time the tests were conducted (prenatal or postnatal). The studies were then subjected to detailed descriptive analysis. RESULTS: A total of 59 studies were selected for analysis; these focused on screening methods for congenital anomalies and compared their prevalence with regards to different systems. The most common screening techniques both prenatal and postnatal included antenatal ultrasound, fetal echocardiography, pulse oximetry, and clinical examination. The most common congenital abnormalities involved the central nervous system (neural tube defects) and musculoskeletal (clubfoot), followed by gastrointestinal (omphalocele and gastroschisis) and cardiovascular (structural heart defect). Overall, different systems had varying prevalences of different birth defects, ranging from 0.28 to 8.5%. In contrast, the prevalence of musculoskeletal system disorders varied from 1.01% to 3.96%, in the cardiovascular system from 0.57% to 10.4%, and in the urogenital group from 0.83% to 5.9%. CONCLUSION: The review highlights the lack of screening programs and studies, especially in the primary and secondary care settings in LMICs, and limited studies do indicate a high burden of various congenital anomalies. There is a need for guidelines and programs in global maternal and child health programs to include timely screening and management of common birth defects in LMICs. INTRODUCTION: Congenital anomalies are one of the major causes of the global burden of diseases, and low- and middle-income countries (LMICs) are disproportionately affected. This review assesses the prenatal and postnatal screening methods and compares the prevalence of major congenital anomalies in LMICs. METHODOLOGY: We conducted a systematic search in MEDLINE/PubMed, CINAHL, Cochrane databases of systematic reviews, clinical trials.gov for relevant studies using Medical Subject Headings and keywords. We categorized the studies into different systems and screening methods depending on the time the tests were conducted (prenatal or postnatal). The studies were then subjected to detailed descriptive analysis. RESULTS: A total of 59 studies were selected for analysis; these focused on screening methods for congenital anomalies and compared their prevalence with regards to different systems. The most common screening techniques both prenatal and postnatal included antenatal ultrasound, fetal echocardiography, pulse oximetry, and clinical examination. The most common congenital abnormalities involved the central nervous system (neural tube defects) and musculoskeletal (clubfoot), followed by gastrointestinal (omphalocele and gastroschisis) and cardiovascular (structural heart defect). Overall, different systems had varying prevalences of different birth defects, ranging from 0.28 to 8.5%. In contrast, the prevalence of musculoskeletal system disorders varied from 1.01% to 3.96%, in the cardiovascular system from 0.57% to 10.4%, and in the urogenital group from 0.83% to 5.9%. CONCLUSION: The review highlights the lack of screening programs and studies, especially in the primary and secondary care settings in LMICs, and limited studies do indicate a high burden of various congenital anomalies. There is a need for guidelines and programs in global maternal and child health programs to include timely screening and management of common birth defects in LMICs.

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)0,000
score de la tête « metaresearch » (Gemma)0,000
Version: codex-gemma-dda1882f352aStatut de validation: machine_predicted_unvalidated
Catégories candidatesMéta-épidémiologie (sens strict)
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 enseignants0,018
Score d'incertitude au seuil1,000

Scores Codex et Gemma par catégorie

CatégorieCodexGemma
Métarecherche0,0000,000
Méta-épidémiologie (sens strict)0,0000,000
Méta-épidémiologie (sens large)0,0050,001
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 Opus0,026
Tête enseignante GPT0,309
Écart entre enseignants0,283 · 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.

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

Citations4
Publié2024
Routes d'admission1
Résumé présentoui

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