Addressing Diagnosis, Management, and Complication Challenges in Placenta Accreta Spectrum Disorder: A Descriptive Study
Bibliographic record
Abstract
INTRODUCTION: In light of increased cesarean section rates, the incidence of placenta accreta spectrum (PAS) disorder is increasing. Despite the establishment of clinical practice guidelines offering recommendations for early and effective PAS diagnosis and treatment, antepartum diagnosis of PAS remains a challenge. This ultimately risks poor mental health and poor physical maternal and neonatal health outcomes. CASE DESCRIPTIONS: This case series details the experience of two high-risk patients who remained undiagnosed for PAS until they presented with antenatal hemorrhage, leading ultimately to necessary, complex surgical interventions, which can only be optimally provide in a tertiary care center. Patient 1 is a 37-year-old woman with a history of three cesarean sections, which elevates her risk for PAS. She had placenta previa detected at 19 weeks, and placenta percreta diagnosed upon hemorrhage. During a hysterectomy, invasive placenta was found in the patient's bladder, leading to a cystotomy and right ureteric reimplantation. After discharge, she was diagnosed with a vesicovaginal fistula, and is currently awaiting surgical repair. Patient 2 is a 34-year-old woman with two previous cesarean sections. The patient had complete placenta previa detected at 19- and 32-week gestation scans. She presented with antepartum hemorrhage at 35 weeks and 2 days. An ultrasound showed thin myometrium at the scar site with significant vascularity. A hysterectomy was performed due to placental attachment issues, with significant blood loss. Both patients were at high risk for PAS based on past medical history, risk factors, and pathognomonic imaging findings. DISCUSSION: We highlight the importance of the implementation of clinical guidelines at non-tertiary healthcare centers. We offer clinical-guideline-informed recommendations for radiologists and antenatal care providers to promote early PAS diagnosis and, ultimately, better patient and neonatal outcomes through increased access to adequate care.
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 imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".