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Record W4407189630 · doi:10.4103/joacc.joacc_12_24

Anesthetic Management of Placenta Accreta Spectrum Disorders: A Narrative Review

2025· review· en· W4407189630 on OpenAlexaff
Sara Alwatban, Bruno C. R. Borges, Sara Miller

Bibliographic record

VenueJournal of Obstetric Anaesthesia and Critical Care · 2025
Typereview
Languageen
FieldMedicine
TopicMaternal and fetal healthcare
Canadian institutionsMcMaster University
Fundersnot available
KeywordsPlacenta accretaMedicineAnestheticNarrative reviewPlacentaObstetricsIntensive care medicineAnesthesiaPregnancyFetus

Abstract

fetched live from OpenAlex

Placenta accreta spectrum (PAS) is a rapidly increasing medical condition due to the high prevalence of cesarean section procedures worldwide. PAS presents in various ways and is a high-risk condition, often leading to parturient morbidity and death. Management of patients with PAS can be very challenging due to its rarity, the lack of high-quality evidence, and its associated anesthetic and surgical challenges. This review provides up-to-date information on detection, surgical management, and anesthetic management using the currently available evidence. This article highlights the parturient course of care from the first antenatal visit to the postoperative period, including preoperative and intraoperative evaluation and postoperative disposition of such patients. We discuss the various anesthetic techniques provided to the parturient and how to manage their downfalls, focusing on improved patient care and outcomes throughout the course of pregnancy.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: Review
Teacher disagreement score0.004
Threshold uncertainty score0.013

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.002
Science and technology studies0.0000.000
Scholarly communication0.0010.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.001

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.028
GPT teacher head0.371
Teacher spread0.343 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2025
Admission routes1
Has abstractyes

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