Shai Ram, Hila Shalev-Ram, Shira Alon, Ziv Shapira, Roza Berkovitz-Shperling, Margaret Johansson-Lipinski, Yariv Yogev, Ariel Many
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引用次数: 0
Abstract
Objective: The increasing rate of cesarean sections (CS) raises concerns over severe intra-abdominal adhesions, which are associated with numerous complications. We aimed to identify risk factors and predictive tools for severe adhesions.
Methods: In a prospective study at a tertiary medical center from January-July 2021, women with at least one prior CS were evaluated. Surgeons assessed adhesions at four anatomical sites, scoring them from 0 (none) to 2 (dense), with a total possible score of 0-8. Severe adhesions were defined as a score of ≥5. Risk factors were analyzed using logistic regression to create a prediction model.
Results: Overall, 341 women were included in the study. Significant predictors included the number of previous CS, maternal BMI, maternal morbidity at the time of the previous CS, and operation time. The model predicted severe adhesions with 79.1% accuracy, a positive predictive value of 68.4%, and a negative predictive value of 79.5%.
Conclusion: The severity of most cases of post-CS adhesions can be predicted by a model which considers common risk factors.
期刊介绍:
This journal covers the most active and promising areas of current research in gynecology and obstetrics. Invited, well-referenced reviews by noted experts keep readers in touch with the general framework and direction of international study. Original papers report selected experimental and clinical investigations in all fields related to gynecology, obstetrics and reproduction. Short communications are published to allow immediate discussion of new data. The international and interdisciplinary character of this periodical provides an avenue to less accessible sources and to worldwide research for investigators and practitioners.