First-Trimester Screening Program for the Risk of Pre-eclampsia Using a Multiple-Marker Algorithm: A Health Technology Assessment.
Notice bibliographique
Résumé
Background: Pre-eclampsia is when high blood pressure develops after 20 weeks of pregnancy and either proteinuria, maternal end-organ dysfunction, or uteroplacental dysfunction causing fetal growth restriction also develops. The Fetal Medicine Foundation has created an algorithm ("the FMF algorithm") that uses maternal factors in combination with biophysical and biochemical markers to identify people at high risk for pre-eclampsia so that they can been offered acetylsalicylic acid (Aspirin) as a preventive measure. We conducted a health technology assessment to evaluate the safety, effectiveness, and cost-effectiveness of a first-trimester population-wide screening program for pre-eclampsia risk that uses the FMF algorithm ("the FMF-based screening program"). We also evaluated the accuracy of the FMF algorithm, the budget impact of publicly funding the population-wide FMF-based screening program, and patient preferences and values. Methods: We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each study using the Risk of Bias in Non-randomized Studies-of Interventions tool and the Quality Assessment of Diagnostic Accuracy Studies-Comparative tool, and the quality of the body of evidence according to the Grading of Recommendations Assessment, Development, and Evaluation (GRADE) Working Group criteria. We performed a systematic economic literature search and conducted a cost-effectiveness analysis comparing the FMF-based screening program to standard care (screening for risk of pre-eclampsia using maternal factors alone) from a public payer perspective. We also analyzed the budget impact of publicly funding a population-wide FMF-based screening program in Ontario. We spoke with people who have experience with pregnancy and preeclampsia and their family members through direct interviews to gather preferences and values surrounding pre-eclampsia and the potential screening program. Results: weeks' gestation; risk ratios ranged from 0.64 (95% confidence interval [CI] 0.46-0.93) to 0.70 (95% CI 0.58-0.84) (GRADE: Moderate). It may reduce the risks of low birth weight (risk ratio 0.89 [95% CI 0.85-0.94]) and low Apgar score (risk ratio 0.73 [95% CI 0.63-0.85]) (GRADE: Low). Evidence on the effectiveness of the FMF-based screening program in reducing the risk of stillbirth and neonatal death was highly uncertain (GRADE: Very low). In addition, the FMF algorithm can improve the detection rate of pre-eclampsia with delivery at less than 37 weeks' gestation or at less than 34 weeks' gestation compared with conventional algorithms, although there are concerns about bias and applicability across studies. The population-wide FMF-based screening program is more effective and more costly than standard care. The incremental cost-effectiveness ratio of the population-wide FMF-based screening program compared with standard care is $3,446 per prevented case of pre-eclampsia with delivery at less than 37 weeks. The annual budget impact of publicly funding the population-wide FMF-based screening program in Ontario ranges from an additional $1.23 million in year 1 to $3.56 million in year 5, for a total of $8.50 million over the next 5 years. The population-wide FMF-based screening program was seen as valuable by those who have experienced pregnancy and their family members. Strong emphasis was placed on providing education and equitable access as part of any screening program, and participants valued the potential clinical benefits that the population-wide FMF-based screening program could provide. Conclusions: The FMF-based screening program is likely more effective than standard care in reducing the risk of pre-eclampsia with delivery at less than 37 weeks' gestation. Also, the FMF algorithm can improve the detection rate of pre-eclampsia with delivery at less than 37 weeks' gestation or at less than 34 weeks' gestation when compared with conventional algorithms. The population-wide FMF-based screening program is more effective and more costly than standard care. We estimate that publicly funding the population-wide FMF-based screening program in Ontario would result in additional costs of $8.50 million over the next 5 years. Pregnant people and their family members valued the potential equitable access, information, and clinical benefits that the population-wide FMF-based screening program could provide.
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 | 0,038 | 0,144 |
| Méta-épidémiologie (sens strict) | 0,002 | 0,001 |
| Méta-épidémiologie (sens large) | 0,007 | 0,016 |
| Bibliométrie | 0,020 | 0,013 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,003 | 0,004 |
| Science ouverte | 0,002 | 0,003 |
| Intégrité de la recherche | 0,003 | 0,002 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,004 | 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 ».