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Enregistrement W4379600201

Placental Growth Factor (PlGF)- Based Biomarker Testing to Help Diagnose Pre-eclampsia in People With Suspected Pre-eclampsia: A Health Technology Assessment.

2023· review· en· W4379600201 sur OpenAlexaboutno aff

Notice bibliographique

RevuePubMed · 2023
Typereview
Langueen
DomaineMedicine
ThématiquePregnancy and preeclampsia studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésPlacental growth factorMedicineEclampsiaBiomarkerGrading (engineering)ObstetricsPregnancyInternal medicineVEGF receptorsVascular endothelial growth factor
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

Background: Pre-eclampsia is a potentially serious condition affecting up to 5% of pregnancies, most frequently after 20 weeks' gestation. Placental growth factor (PlGF)-based tests measure either the blood level of PlGF or the ratio of soluble fms-like tyrosine kinase-1 (sFlt-1) to PlGF. They are intended to complement standard clinical assessment to help diagnose pre-eclampsia in people with suspected pre-eclampsia. We conducted a health technology assessment of PlGF-based biomarker testing as an adjunct to standard clinical assessment to help diagnose pre-eclampsia in pregnant people with suspected pre-eclampsia, which included an evaluation of diagnostic accuracy, clinical utility, cost-effectiveness, the budget impact of publicly funding PlGF-based biomarker testing, and an assessment of preferences and values. Methods: We performed a systematic literature search of the clinical evidence. We assessed the risk of bias of each included study using AMSTAR 2, Cochrane Risk of Bias tool, the Quality of Diagnostic Accuracy Studies 2 (QUADAS-2) 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 literature search of the economic evidence. We did not conduct a primary economic evaluation as the impact of the test on maternal and neonatal outcomes is uncertain. We also analyzed the budget impact of publicly funding PlGF-based biomarker testing in pregnant people with suspected pre-eclampsia in Ontario. To contextualize the potential value of PlGF-based biomarker testing, we spoke with people whose pregnancies had been impacted by pre-eclampsia as well as their family members. Results: We included one systematic review and one diagnostic accuracy study in the clinical evidence review. The Elecsys sFlt-1/PlGF ratio test using a test cut-off of less than 38 for ruling out pre-eclampsia within 1 week yielded a negative predictive value (NPV) of 99.2% and the DELFIA Xpress PlGF 1-2-3 test using a cut-off of 150 pg/mL or greater for ruling out pre-eclampsia within 1 week yielded a NPV of 94.8% (diagnostic GRADE: Moderate for both tests). All clinical utility outcomes were associated with uncertainties (GRADE: Low).We included 13 studies in the economic evidence review, most of which concluded that the use of PlGF-based biomarker testing resulted in cost savings. Seven studies were partially applicable to the Ontario health care setting but have some important limitations; the remaining 6 studies were not applicable. We estimated that publicly funding PlGF-based biomarker testing for people with suspected pre-eclampsia in Ontario would lead to an additional annual cost of $0.27 million in year 1 to $0.46 million in year 5, for a total additional cost of $1.83 million over 5 years.Direct engagement included 24 people who had been impacted by pre-eclampsia during their pregnancies as well as one family member. Participants described the emotional and physical impacts of having suspected pre-eclampsia and subsequent treatments. Those that we spoke with valued shared decision-making and identified potential gaps in patient education, specifically as it relates to symptom management for suspected pre-eclampsia. Overall, the participants viewed PlGF-based biomarker testing positively for its perceived medical benefits and minimal invasiveness. They felt that access to PlGF-based biomarker testing may also improve health outcomes through improved patient education, care coordination, and patient-centred care (e.g., prompting more frequent prenatal monitoring, when needed). In addition, PlGF-based biomarker testing was perceived to be equally beneficial for family members who may act as the health care proxy in an emergency. Lastly, participants emphasized that there should be equitable access to PlGF-based biomarker testing and support from a care provider should be offered when trying to interpret the results, particularly if the results are accessible through an online patient portal. Conclusions: Compared with standard clinical assessment alone in people with suspected pre-eclampsia (gestational age between 20 and 36 weeks + 6 days), PlGF-based biomarker testing as an adjunct to standard clinical assessment likely improves prediction of pre-eclampsia. It may also reduce time to pre-eclampsia diagnosis, severe adverse maternal outcomes, and length of stay in the neonatal intensive care unit, although the evidence is uncertain. PlGF-based biomarker testing may result in little to no difference in other clinical outcomes such as maternal admission to hospital and perinatal adverse outcomes.The economic literature review showed that PlGF-based biomarker testing was cost-effective for use in people with suspected pre-eclampsia, but with some uncertainties. A primary economic evaluation was not done for this health technology assessment because the impact of the test on maternal and neonatal outcomes is uncertain. Publicly funding PlGF-based biomarker testing for people with suspected pre-eclampsia would lead to an additional cost of $1.83 million over 5 years.Publicly funding PlGF-based biomarker testing was viewed favourably by people directly impacted by pre-eclampsia as well as their family members. Those with whom we spoke valued testing to help diagnose suspected pre-eclampsia and valued the potential medical benefits. Participants emphasized that patient education, and equitable access to PlGF-based biomarker testing should be requirements for implementation in Ontario.

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)0,075
score de la tête « metaresearch » (Gemma)0,249
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Revue systématique · Signal consensuel: Revue systématique
GenreSignal candidat: Synthèse · Signal consensuel: Synthèse
Score de désaccord entre enseignants0,075
Score d'incertitude au seuil0,394

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0750,249
Méta-épidémiologie (sens strict)0,0010,001
Méta-épidémiologie (sens large)0,0070,012
Bibliométrie0,0210,011
Études des sciences et des technologies0,0010,001
Communication savante0,0050,004
Science ouverte0,0020,003
Intégrité de la recherche0,0050,003
Charge utile insuffisante (le modèle a refusé de juger)0,0040,000

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.

Tête enseignante Opus0,082
Tête enseignante GPT0,352
Écart entre enseignants0,270 · 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'étudeRevue systématique
Domainenon disponible
GenreSynthèse

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

En bref

Citations10
Publié2023
Routes d'admission1
Résumé présentoui

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