Low lying placenta: natural course, clinical data, complications and a new model for early prediction of persistency

Sivan Farladansky-Gershnabel*, Hadar Gluska, Maya Sharon-Weiner, Gil Shechter-Maor, Hanoch Schreiber, Omer Weitzner, Tal Biron-Shental, Ofer Markovitch

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

Objective: To define the natural course and complications, and develop a model for predicting persistency when low-lying placenta (LLP) is detected early in pregnancy. Methods: This retrospective cohort study included women with LLP detected during an early anatomic scan performed at 13–16 weeks gestation. Additional transvaginal ultrasound exams were assessed for resolution at 22–24 weeks and 36–39 weeks. Patients were categorized as: Group 1–LLP resolved by the second-trimester scan, Group 2–LLP resolved by the third trimester, or Group 3–LLP persisted to delivery. Clinical and laboratory parameters, as well as maternal and neonatal complications, were compared. A linear support vector machine classification was used to define a prediction model for persistent LLP. Results: Among 236 pregnancies with LLP, 189 (80%) resolved by 22–24 weeks, 25 (10.5%) resolved by 36–39 weeks and 22 (9.5%) persisted until delivery. Second trimester hCG levels were higher the longer the LLP persisted (0.8 ± 0.7MoM vs. 1.13 + 0.4 MoM vs. 1.7 ± 1.5 MoM, adjusted p =.03, respectively) and cervical length (mm) was shorter (first trimester: 4.3 ± 0.7 vs. 4.1 ± 0.5 vs. 3.6 ± 1; adjusted p =.008; Second trimester: 4.4 ± 0.1 vs. 4.1 ± 1.2 vs. 3.8 ± 0.8; adjusted p =.02). The predictive accuracy of the linear support vector machine classification model, calculated based on these parameters, was 90.3%. Conclusions: Persistent LLP has unique clinical characteristics and more complications compared to cases that resolved. Persistency can be predicted with 90.3% accuracy, as early as the beginning of the second trimester by using a linear support vector machine classification model.

Original languageEnglish
Article number2204998
JournalJournal of Maternal-Fetal and Neonatal Medicine
Volume36
Issue number1
DOIs
StatePublished - 2023

Keywords

  • Low lying placenta
  • linear support vector machine classification model
  • placenta previa
  • pregnancy outcome
  • prenatal ultrasonography

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