PRAYAS: Cohort profile for Pooled Research and Analysis for Yielding Anemia-free Solutions in India
Notice bibliographique
Résumé
Abstract Purpose This cohort would aim to estimate the prevalence of anemia among children under 18 years, non-pregnant and non-lactating (NPNL) women, and pregnant women (by trimester), with further stratification by age group, year, and region of India. Cohort would also help address extended deliberation concerning etiological fraction of iron and other key erythropoietic micronutrient deficiencies contributing to anemia in India. Additionally, this will help assess the effectiveness of existing anaemia prevention and treatment interventions and examine factors associated with non-response, thereby supporting the “test–treat–track” approach. Participants Children under 18 years, pregnant women, and non-pregnant-non-lactating women (NPNL) in India. Findings to date This cohort profile comprises 88 datasets spanning between 1994 to 2023, encompassing a total of 319,721 participants for prevalence analysis [children(19,762), NPNL(17,883), and pregnant women(282,076)]. Additionally, 59,292 participants were included in intervention studies [children(13,435), NPNL(11,594), and pregnant women(34,263)]. RCTs comprised 55.7% (49/88) of the datasets whereas observational studies comprise 35.2% (31/88) of the datasets. Majority of the studies were from the norther region - 38 studies (43.2%), followed by the western part - 20 studies (22.7%). The southern part contributed 16 studies (18.2%). Major [59/88 (67%)] datasets in cohort were from community-based studies. The sample included NPNL and pregnant women with a median age of 26 years (IQR 23-32), and 23 years (IQR 21-25) respectively. Information from 6 months up to 18 years was pooled within the children’s cohort. Within the pregnancy cohort the mean gestational age at enrollment was 10.24 weeks(SD-17.65). Of total 10.8% (34,442/ 319,721), 9% (28,672), 4.5% (14,240) of the sample had information on complete blood count, ferritin and vitamin B12 respectively. A total of 33 datasets (sample - 59,292) were from intervention studies. Among pregnant women, a broader range of interventions was implemented, including intravenous iron sucrose, ferric carboxymaltose, iron isomaltoside, IV iron combined with vitamin B12, folic acid, and niacinamide, integrated interventions, as well as low-dose calcium supplementation. A similar set of interventions were delivered to NPNL group with being distinct which compared Ferrous sulfate tablets of 60 mg elemental iron daily with a control of 120 mg on alternate days. Ferrous sulfate was the major interventions amongst children along with food supplements and some were Ayush trials. Future plans The PRAYAS will provide robust, high-quality evidence to inform public health policy in India. The findings will feed into the Anemia Mukt Bharat program recommendations for pregnant women, NPNL women and children to guide targeted strategies for reduction of anemia and its associated health burdens across vulnerable populations. Strengths and limitations of this study The harmonized PRAYAS pooled Indian dataset is one of the largest, reliable and most comprehensive datasets on pregnant/ non-pregnant and non-lactating women and children. One of its kind of dataset with information on hemoglobin levels, relevant biochemical and key micronutrients parameters and varied interventions from across India. Heterogeneity of interventions, dosage, duration and data collection approaches. Studies lack critical parameters needed to assess changes in haemoglobin concentration like non-availability of key erythropoietic micronutrients in most of the studies, limiting the scope of certain analyses.
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 enseignantsNi 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.
Scores du classifieur distillé par catégorie (deux têtes)
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,023 | 0,062 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,001 |
| Méta-épidémiologie (sens large) | 0,002 | 0,007 |
| Bibliométrie | 0,005 | 0,008 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,003 | 0,001 |
| Science ouverte | 0,002 | 0,004 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,013 | 0,002 |
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; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».