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Placenta Accreta Spectrum
Open accessAbstract
Placenta accreta spectrum, formerly known as morbidly adherent placenta, refers to the range of pathologic adherence of the placenta, including placenta increta, placenta percreta, and placenta accreta. The most favored hypothesis regarding the etiology of placenta accreta spectrum is that a defect of the endometrial-myometrial interface leads to a failure of normal decidualization in the area of a uterine scar, which allows abnormally deep placental anchoring villi and trophoblast infiltration. Maternal morbidity and mortality can occur because of severe and sometimes life-threatening hemorrhage, which often requires blood transfusion. Although ultrasound evaluation is important, the absence of ultrasound findings does not preclude a diagnosis of placenta accreta spectrum; thus, clinical risk factors remain equally important as predictors of placenta accreta spectrum by ultrasound findings. There are several risk factors for placenta accreta spectrum. The most common is a previous cesarean delivery, with the incidence of placenta accreta spectrum increasing with the number of prior cesarean deliveries. Antenatal diagnosis of placenta accreta spectrum is highly desirable because outcomes are optimized when delivery occurs at a level III or IV maternal care facility before the onset of labor or bleeding and with avoidance of placental disruption. The most generally accepted approach to placenta accreta spectrum is cesarean hysterectomy with the placenta left in situ after delivery of the fetus (attempts at placental removal are associated with significant risk of hemorrhage). Optimal management involves a standardized approach with a comprehensive multidisciplinary care team accustomed to management of placenta accreta spectrum. In addition, established infrastructure and strong nursing leadership accustomed to managing high-level postpartum hemorrhage should be in place, and access to a blood bank capable of employing massive transfusion protocols should help guide decisions about delivery location.
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“ML, with its ability to read complex imaging data [17] and to reduce the dependence on operator skill, has great potential as a method of improving consistency and enabling earlier diagnosis of PAS [6].”
From Machine Learning in Maternity: Early Diagnosis of Placenta Accreta Spectrum (2026) · cites this paper as [6]
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Cesarean section one hundred years 1920–2020: the Good, the Bad and the Ugly
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Metadata
- Authors
- Cahill, A. G., Beigi, R., Heine, R. P., Silver, R. M., & Wax, J. R.
- Affiliations
- Society for Maternal-Fetal Medicine (US)
- Venue
- American Journal of Obstetrics and Gynecology
- Publisher
- Elsevier BV
- Published
- 2018-12
- Volume
- 219
- Issue
- 6
- Pages
- B2-B16
- ISSN
- 0002-9378 (ISSN-L)
- OpenAlex
- W2901857044
- Cited by
- 481
- References
- 99
- Citations by year
- 2026: 34 · 2025: 76 · 2024: 82 · 2023: 85 · 2022: 62 · 2021: 70 · 2020: 42 · 2019: 25
- FWCI
- 38.07
- Type
- journal article
- Language
- en
- Open access
- bronze
- doi.org
- Locations
- American Journal of Obstetrics and Gynecology (publishedVersion)
- PubMed (publishedVersion)
- Topics
- Health Sciences › Medicine › Pediatrics, Perinatology and Child Health › Maternal and fetal healthcare
- Health Sciences › Medicine › Hematology › Blood transfusion and management
- Health Sciences › Medicine › Obstetrics and Gynecology › Uterine Myomas and Treatments
- Keywords
- placenta accreta spectrum, placenta increta, placenta percreta, placenta accreta, decidualization, uterine scar, cesarean section, postpartum hemorrhage, prenatal diagnosis, cesarean hysterectomy, placental retention, risk factors, multidisciplinary care, massive transfusion
- MeSH terms
- Cesarean Section, Female, Gynecology, Humans, Hysterectomy, Obstetrics, Placenta Accreta, Pregnancy, Prenatal Diagnosis, Societies, Medical, United States
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Registry, retraction, Cites and statistics results are computed, not judged, with one exception: a printed reference that no index lists is read once by a model before it counts as a citation error. Claims are extracted by a model and kept only when their quote appears verbatim in the text; each cited source is then checked, with a model’s help, for whether it says what the claim relies on. Those verdicts can be wrong — read the claim’s quote and the cited source before relying on one.
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