Sherif Shazly

and 46 more

Objective: To compare peripartum outcomes of uterus preserving procedures to caesarean hysterectomy in women with placenta accreta spectrum (PAS), and to identify risk factors associated with adverse maternal outcomes. Design: Retrospective study (ClinicalTrials.gov identifier: NCT04384510) Setting:11 tertiary centres from 9 countries Population or Sample: women with of PAS who were managed in participating centres between January 1st, 2010 and December 31st, 2019. Women who had confirmed diagnosis with PAS with adequate documentation and follow-up, were considered eligible. Main Outcome Measures: Primary outcome was massive PAS-associated perioperative blood loss (intraoperative blood loss ≥ 2500 ml, bleeding associated massive transfusion protocol, or complicated by disseminated intravascular coagulopathy). Results: Out of 797 women, 727 were eligible for the study. Five hundred ninety-two (81.43%) women were managed by uterus preserving procedures versus 135 (18.56%) who underwent caesarean hysterectomy. After adjustment for significant or close-to-significance variables, type of management was not associated with higher risk of massive blood loss (aOR 1.71, 95% CI 0.78 - 3.81). Other factors that were significantly associated with higher risk of massive PAS-associated blood loss included body mass index, preoperative haemoglobin, centrally located placenta, diffuse placental invasion, parametrial invasion, and intrauterine foetal death. Conclusions: In the presence of sufficient experience, uterus preserving procedures may not be associated with higher risk of massive blood loss compared to caesarean hysterectomy. Funding: none

Sherif Shazly

and 39 more

Objective: To establish a prediction model of clinical outcomes in women with placenta accreta spectrum (PAS) Design: Retrospective cohort study Setting: International multicenter study (PAS-ID); 11 centers from 9 countries Population: Women who were diagnosed with PAS and were managed in recruiting centers between January 1st, 2010 and December 31st, 2019. Methods: Data were collected using a standardized sheet, which included baseline information, medical and obstetric history, diagnosis, disease characteristics, management, and outcomes. Analysis of association between these variables and primary outcome was first conducted using conventional logistic regression. Data were reanalyzed using machine learning (ML) models, and 2 models were created to predict outcomes using antepartum and perioperative features. Main Outcome Measures: Massive PAS-associated perioperative blood loss (intraoperative blood loss ≥ 2500 ml, triggering massive transfusion protocol, or complicated by disseminated intravascular coagulopathy). Other outcomes include prolonged hospitalization > 7 days and admission to intensive care unit (ICU). Results: 727 women with PAS were included. Area under curve (AUC) for ML antepartum prediction model was 0.84, 0.81, and 0.82 for massive blood loss, prolonged hospitalization, and admission to ICU, respectively. Significant contributors to this model were parity, placental site, method of diagnosis and antepartum hemoglobin. Combing baseline and perioperative variables, ML model performed at 0.86, 0.90, and 0.86 for study outcomes, respectively. This model was most contributed by ethnicity, pelvic invasion, and uterine incision. Conclusions: ML models may be used to calculate individualized risk of morbidity in women with PAS, which may assist to outline management plan in priori