ReviewArchives of gynecology and obstetrics2025
The molecular pathogenesis of placenta accreta spectrum disorder and its clinical applications.
Review in Archives of gynecology and obstetrics, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
1 citing paper in PubMed.
- Article
Corrections and comments
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Authors and funding
3 authors.
Funding
No grant is acknowledged in the PubMed record.
Abstract
Placenta accreta spectrum (PAS) is a serious obstetric complication, characterized by the placenta accreta and increta to the uterine wall, which fails to detach spontaneously from the uterine following childbirth, potentially resulting in severe hemorrhage and additional complications. The incidence of PAS is increasing in the world, which is mainly attributed to a global escalation in cesarean section rates, underscoring the critical need to elucidate its molecular pathogenesis and to devise efficacious clinical interventions. Recent studies have identified novel molecular mechanisms that have significantly enhanced our comprehension of disease pathophysiology and informed predictive and therapeutic strategies. Here, we review the principal molecular pathogenesis of PAS, explore the potential translation of these findings into clinical applications, and assess the impact of emerging technologies on advancing research in this domain.
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Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.