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Enregistrement W4417477052 · doi:10.64898/2025.12.17.25342279

Cohort Profile: PRECISE-DYAD: a prospective cohort study linking maternal and infant health trajectories in sub-Saharan Africa

2025· preprint· en· W4417477052 sur OpenAlexaff
Marie‐Laure Volvert, Milly Wilson, RO Owino, Angela Koech, Hawanatu Jah, Hannah Blencowe, Yahaya Idris, Onesmus Wanje, Joseph Mutunga, Fatima Touray, Emily Mwadime, Anna Roca, Geoffrey Omuse, Rachel Craik, Fatoumata Kongira, Moses Mukhanya, Kalilu Bojang, B. Njie, Marvine Caren Ochieng, Umberto D’Alessandro, Grace Mwashigadi, Agnes M. Mutua, Anne J. Rerimoi, Marleen Temmerman, Joseph Akuze, Melisa Martínez-Álvarez, Dorcas N. Magai, Benjamin Barratt, Jing Li, Jaya Chandna, Melissa Gladstone, Amina Abubakar, Rachel M. Tribe, Asma Khalil, Tatenda Makanga, Tatiana Taylor Salisbury, Hiten D. Mistry, Sophie E. Moore, Helen Nabwera, Véronique Filippi, Laura A. Magee, Liberty Makacha, Lucilla Poston, Esperança Sevene, Peter von Dadelszen

Notice bibliographique

RevuemedRxiv · 2025
Typepreprint
Langueen
DomaineMedicine
ThématiqueGlobal Maternal and Child Health
Établissements canadiensBC Children's Hospital
Organismes subventionnairesFogarty International CenterNational Institute of Mental HealthMinisterio de Ciencia e InnovaciónNational Institute for Health and Care ResearchAgencia Estatal de InvestigaciónNational Institutes of HealthUK Research and Innovation
Mots-clésEpidemiologyCohort studyProspective cohort studyMental healthCohortEnvironmental epidemiologyPublic healthChild development

Résumé

récupéré en direct d'OpenAlex

Abstract Purpose The PRECISE-DYAD study is a prospective observational cohort, designed to investigate health outcomes among mother-child pairs (dyads), over the first three years of life in two contexts from sub-Saharan Africa. The primary objective of the study was to explore the effects of selected placenta-related complications, such as pregnancy hypertension, fetal growth restriction, and preterm birth, on 1) child health and development, and 2) women’s health and well-being, including outcomes after stillbirth Participants The PRECISE-DYAD study enrolled women (and their children) originally recruited into the PRECISE regnancy cohort study in The Gambia and Kenya between July 2021 and April 2024. Participants were seen at 6 weeks to 6 months, 12 months, 24 months, and 36 months post-partum. Clinical and health data, including anthropometry and diet were collected for both mothers and children. Mother assessment included a cardiology assessment and collection of data about symptoms of COVID-19 infection. In a subset of participants, mothers were asked about their mental health, their health care costs during and after pregnancy, and experiences of care during labour and childbirth / delivery. Additonally, a personal environmental exposure assessement was performed for a subset of the cohort, by collecting air and water quality data alongside geographical, demographic, and behavioural factors. Child development was assessed using neurodevelopmental assessments, home environment evaluation, and quality of life measures. Biological samples were collected from mothers and children, processed promptly and biobanked locally. Sample data were entered into an OpenSpecimen database and linked to each individual, as well as to their corresponding social determinants and clinical data. Findings to date A total of 2,980 women and 2,909 children completed at least one PRECISE-DYAD study visit. The biorepository contains 108,897 biological samples from mothers and children. Baseline descriptive analysis of the cohort are reported here. Future plans Analysis of data and samples will include biomarker studies, social determinants of health, and epidemiological investigations. These analyses will explore how placenta-related complications and environmental exposures, such as nutrition and air quality, interact to shape maternal health, mental well-being, subsequent pregnancies, and mother-child interaction, as well as child growth and neurodevelopment through early childhood. Additional work will examine the biological pathways linking these exposures to outcomes and the impacts of caring for children with moderate-to-severe disabilities on maternal well-being. Findings will be disseminated through scientific publications, conference presentations, engagement with local stakeholders, and continued community outreach. Strengths and limitations - This is a unique pregnancy-enrolled, population-based cohort with extensive social, clinical, and biological data, including biospecimens, collected across two geographically diverse settings in sub-Saharan Africa. Women were recruited at the time of booking for antenatal care, allowing early identification and longitudinal follow-up of those with placenta-related complications. The integration of PRECISE and PRECISE-DYAD data enables the comprehensive investigation of the drivers and impacts of placental disorders on maternal and child health, and outcomes related to the COVID-19 pandemic. - Data were collected on women’s social and physical environments, including air quality, and water, sanitation, and hygiene (WASH) conditions. In-depth data were also gathered on children, with a focus on neurodevelopmental assessments. Consistent data collection procedures and standardised methodologies were used across both study sites. - Extensive and sustained community engagement, including 108 sensitisation meetings with nearly 4,000 participants, enhanced trust, study understanding, and acceptability. - A limitation of the study is the loss to follow-up of participants who relocated outside of the study area during pregnancy or after the child’s birth, or changed their contact details. - A second limitation is that the Mozambique pregnancy cohort has provided only air quality data through PRECISE-DYAD, and has not been followed up otherwise at this time.

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 machine sur la base complète

Imitation des enseignants

Ni 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.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,002
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Observationnel · Signal consensuel: Observationnel
GenreSignal candidat: Empirique · Signal consensuel: Empirique
Score de désaccord entre enseignants0,024
Score d'incertitude au seuil0,048

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,002
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0010,002
Études des sciences et des technologies0,0020,000
Communication savante0,0010,001
Science ouverte0,0010,002
Intégrité de la recherche0,0010,001
Charge utile insuffisante (le modèle a refusé de juger)0,0020,001

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 Opus0,015
Tête enseignante GPT0,296
Écart entre enseignants0,282 · 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 source (Gemma direct ou Codex distillé), pas un consensus.

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

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

En bref

Citations1
Publié2025
Routes d'admission1
Résumé présentoui

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