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Placenta Accreta Spectrum: A Narrative Review of Clinical Management, Contemporary Innovations, And Global Challenges
Chijioke Ogomegbunam Ezeigwe1, George Uchenna Eleje2,3, Uchenna Paschaline Eze3
1Department of Obstetrics and Gynaecology, Nnamdi Azikiwe University, Awka, Nigeria.
Placenta accreta spectrum (PAS) management requires timely prenatal diagnosis and multidisciplinary care. Integrating advanced imaging and machine learning can improve outcomes, especially in resource-limited settings.
Area of Science:
- Obstetrics and Gynecology
- Maternal-Fetal Medicine
- Surgical Innovation
Background:
- Placenta accreta spectrum (PAS) is a severe obstetric complication with increasing incidence globally.
- Existing clinical guidelines for PAS often lack applicability in resource-limited settings.
- There's a need to integrate advanced diagnostic and management strategies into diverse healthcare environments.
Purpose of the Study:
- To comprehensively review the evolving clinical landscape of PAS.
- To evaluate diagnostic advancements and multidisciplinary management frameworks for PAS.
- To assess the integration of emerging technologies in diverse healthcare settings.
Main Methods:
- A narrative review of peer-reviewed publications, guidelines, and clinical studies.
- Searches conducted in major databases (PubMed, SCOPUS, Web of Science, Google Scholar).
- Data synthesis focused on diagnostics, management, and outcomes, including LMIC context.
Main Results:
- PAS incidence is rising due to increased cesarean section rates.
- Key diagnostic signs like intracervical lakes and the "rail sign" improve prenatal identification.
- Multidisciplinary care and intraoperative adjuncts improve outcomes, but severe morbidity persists in low-resource settings.
Conclusions:
- Timely prenatal detection and coordinated care are crucial for optimizing PAS outcomes.
- Advances in imaging and real-time assessments aid surgical planning and risk stratification.
- Standardized frameworks and expanded access to multidisciplinary care are essential, particularly in low-resource settings.
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