Prenatal screening for preeclampsia: the roles of placental growth factor and pregnancy–associated plasma protein A in the first trimester and placental growth factor and soluble fms-like tyrosine kinase 1–placental growth factor ratio in the early second trimester
Notice bibliographique
Résumé
Professional societies have recommended universal first trimester screening for preeclampsia and a second or third trimester soluble fms-like tyrosine kinase-1–placental growth factor ratio test to assess for preeclampsia and its severity. However, it may not be feasible to implement the most optimal screening protocol for preeclampsia in the first trimester which uses a combination of maternal characteristics, maternal biophysical and biochemical markers due to limitations in the access to uterine artery doppler ultrasound. There are inconsistent findings on how early in the second trimester the fms-like tyrosine kinase-1–placental growth factor ratio begins to provide useful information in preeclampsia prediction. This study aimed to assess the accuracy of (1) a combination of maternal characteristics, maternal serum pregnancy-associated plasma protein A, and placental growth factor in the screening for preeclampsia in the first trimester; and (2) placental growth factor or soluble fms-like tyrosine kinase-1–placental growth factor ratio in the prediction of preeclampsia in the early second trimester. This retrospective case–control study used frozen residual blood samples from women who had aneuploidy screening and delivered at a tertiary center. The case group included pregnancies with gestational hypertension or preeclampsia (further classified as early-onset [birth at <34 weeks’ gestation] and preterm preeclampsia [birth at <37 weeks’ gestation]). Each case was matched with 3 control pregnancies by date of blood sample draw, gestational age at first blood sample draw, maternal age, maternal ethnicity, type of multiple-marker screening, and amount of residual sample. Mann–Whitney U tests were used to assess the associations between serum markers and the risk of preeclampsia. Logistic regressions were used to assess if the risk of preeclampsia can be predicted using a combination of maternal characteristics and serum markers. The case group included 146 preeclampsia and 295 gestational hypertension cases. Compared with the controls, preeclampsia cases had significantly lower first-trimester pregnancy-associated plasma protein A and placental growth factor. At a 20% false-positive rate, 71% of early-onset and 58% of preterm preeclampsia cases can be predicted using maternal characteristics, pregnancy-associated plasma protein A, and placental growth factor. Preeclampsia cases had lower second-trimester placental growth factor and a higher soluble fms-like tyrosine kinase-1–placental growth factor ratio. At a 10% false-positive rate, 80% and 53% of early-onset preeclampsia can be predicted using maternal characteristics and placental growth factor or soluble fms-like tyrosine kinase-1–placental growth factor ratio, respectively. The current first-trimester aneuploidy screening programs may be expanded to identify women at increased risk of developing preeclampsia. Early in the second trimester, placental growth factor alone provided better prediction for preeclampsia compared with the soluble fms-like tyrosine kinase-1–placental growth factor ratio.
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Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi 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.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,001 |
| Méta-épidémiologie (sens strict) | 0,001 | 0,000 |
| Méta-épidémiologie (sens large) | 0,001 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,000 | 0,000 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 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 tête enseignante, 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 ».