Publications by authors named "Cagri Ates"

High-risk pregnancies not only heighten concerns about the baby's health but also have the potential to impact the mother-infant relationship by shifting the mother's focus towards her own health needs. This study aims to delve into the intricacies of motherhood roles among women experiencing high-risk pregnancies compared to those with uncomplicated pregnancies, aiming to shed light on the disparities between the two groups. The participants of this descriptive, comparative, and correlational study consisted of literate mothers admitted to a hospital in Eastern Turkey, diagnosed with high-risk pregnancies, and with no prior history of psychological support.

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Article Synopsis
  • Placenta accreta spectrum (PAS) is a serious obstetric condition linked to high rates of morbidity and mortality, prompting the need for predictive models to assess possible clinical outcomes.
  • An international study, PAS-ID, analyzed data from 727 women diagnosed with PAS between 2010 and 2019, utilizing machine learning to create two predictive models based on various clinical features.
  • Results showed high predictive accuracy, with models identifying significant factors like parity and placental site, indicating that machine learning can effectively assess individual risk and guide management strategies for women with PAS.
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Objective: To create a model for prediction of success of uterine-preserving procedures in women with placenta accreta spectrum (PAS).

Methods: PAS-ID is a multicenter study that included 11 centers from 9 countries. Women with PAS, who were managed between January 1, 2010 and December 31, 2019, were retrospectively included.

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