OR08-01 One-Step Versus Two-Step Approach for Gestational Diabetes Mellitus Screening: Comparison of Maternal and Fetal Outcomes in a Canadian Population
Notice bibliographique
Résumé
Abstract Screening for gestational diabetes mellitus (GDM) is internationally recommended however there is no universal approach. Impact of the different diagnostic strategies on maternal and neonatal complications’ rates and cost-effectiveness need to be studied. Objective To compare maternal and neonatal outcomes between the two supported screening methods for GDM; the International Association of the Diabetes and Pregnancy Study Groups (IADPSG) 75g one-step oral glucose tolerance test (OGTT) versus the 50g two-step OGTT. Methods A retrospective cohort study was performed regrouping all deliveries between 2016 and 2018 in two centers, each using one different screening method. GDM was diagnosed in center A when meeting IADPSG odds ratio (OR) 1.75 cut-offs values after a one-step 75g-OGTT. Center B used a two-step strategy and diagnosed GDM with 50g-OGTT 1hr glycemic value ≥11.1 mmol/L or failed 50g followed by 75g-OGTT results over the IADPSG OR 2.0 cut-offs. Primary outcome was the rate of large for gestational age (LGA) babies. Outcomes were analysed for singleton pregnancies with deliveries >32 weeks. Subgroup analysis of borderline GDM women (OGTT results in between IADPSG OR 1.75 and 2.0 values) were done. Group A’s borderline patients were treated as per GDM patients. Group B’s borderline patients were not considered diabetic and had normal pregnancy care. Results were adjusted for maternal age, BMI and gestational weight gain. Results At interim analysis for the year 2016, a total of 6188 pregnancies, 2664 women in center A (one-step) and 3524 in center B (two-step) were included. The prevalence of GDM was 17.1% in center A (n=456) and 14.8% in center B (n=520). Both populations were comparable in terms of risk factors for LGA except for its ethnic distribution and proportion of obese women (13.1 vs 21.6%). GDM women in center B compared to center A had significant increase in rates of LGA neonates (adjusted OR (ORa) 2.1, p=0.012); neonatal hypoglycemia (ORa 2.1, p=0.0001) and neonatal intensive care unit (NICU) admission (2.1, p=0.048). Gestational hypertension’s rate was more prevalent in center B (ORa 2.1, p=0.020) and there was a non statistical trend towards increased rate of caesareans (1.6, p=0.084). Regular prenatal care for borderline women in center B (n=94) compared to GDM care in center A (n=150) resulted in increased rate of LGA babies (ORa 3.2, p=0.049). Worse maternal outcomes were identified for gestational hypertension (9.7 vs 1.3%, p=0.035) and preeclampsia (4.3 vs 0%, p=0.021) in group B vs A, respectively. Conclusions Choosing the one-step IADPSG criteria’s for GDM screening is associated with lower rates of LGA, neonatal hypoglycemia and NICU admissions, at the expense of increased prevalence in our population. The ongoing study will include a cost-benefit evaluation to assess if improved outcomes overbalance the increased prevalence inherent to lower diagnostic criteria.
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 | 0,002 | 0,004 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,002 |
| Bibliométrie | 0,001 | 0,002 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,001 | 0,000 |
| Science ouverte | 0,001 | 0,001 |
| Intégrité de la recherche | 0,001 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,003 | 0,000 |
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.
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 ».