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Prediction of Emergency Cesarean Section Using Detectable Maternal and Fetal Characteristics Among Saudi Women.
Wahabi, Hayfaa; Fayed, Amel; Elmorshedy, Hala; Esmaeil, Samia Ahmad; Amer, Yasser S; Saeed, Elshazaly; Jamal, Amr; Aleban, Sarah A; Aldawish, Reema Abdullah; Alyahiwi, Lara Sabri; Abdullah Alnafisah, Haya; AlSubki, Raghad E; Albahli, Norah Khalid; Almutairi, Aljohara Ayed.
Afiliação
  • Wahabi H; Research Chair for Evidence-Based Health Care and Knowledge Translation, King Saud University, Riyadh, Saudi Arabia.
  • Fayed A; Department of Family and Community Medicine, King Saud University Medical City and College of Medicine, Riyadh, Saudi Arabia.
  • Elmorshedy H; Clinical Sciences Department, College of Medicine, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
  • Esmaeil SA; Clinical Sciences Department, College of Medicine, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
  • Amer YS; Research Chair for Evidence-Based Health Care and Knowledge Translation, King Saud University, Riyadh, Saudi Arabia.
  • Saeed E; Department of Family and Community Medicine, King Saud University Medical City and College of Medicine, Riyadh, Saudi Arabia.
  • Jamal A; Research Chair for Evidence-Based Health Care and Knowledge Translation, King Saud University, Riyadh, Saudi Arabia.
  • Aleban SA; Clinical Practice Guidelines Unit, Quality Management Department, King Khalid University Hospital, King Saud University, Riyadh, Saudi Arabia.
  • Aldawish RA; Prince Abdulla bin Khaled Coeliac Disease Research Chair, King Saud University, Riyadh, Saudi Arabia.
  • Alyahiwi LS; Research Chair for Evidence-Based Health Care and Knowledge Translation, King Saud University, Riyadh, Saudi Arabia.
  • Abdullah Alnafisah H; Department of Family and Community Medicine, King Saud University Medical City and College of Medicine, Riyadh, Saudi Arabia.
  • AlSubki RE; Clinical Sciences Department, College of Medicine, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
  • Albahli NK; Clinical Sciences Department, College of Medicine, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
  • Almutairi AA; Clinical Sciences Department, College of Medicine, Princess Nourah bint Abdulrahman University, Riyadh, Saudi Arabia.
Int J Womens Health ; 15: 1283-1293, 2023.
Article em En | MEDLINE | ID: mdl-37576185
Background: The worldwide rate of cesarean section (CS) is increasing. Development of prediction models for a specific population may improve the unmet need for CS as well as reduce the overuse of CS. Objective: To explore risk factors associated with emergency CS, and to determine the accuracy of predicting it. Methods: A retrospective analysis of the medical records of women who delivered between January 1, 2021-December 2022 was conducted, relevant maternal and neonatal data were retrieved. Results: Out of 1793 deliveries, 447 (25.0%) had emergency CS. Compared to control, the risk of emergency CS was higher in primiparous women (OR 2.13, 95% CI 1.48 to 3.06), in women with higher Body mass index (BMI) (OR 1.77, 95% CI 1.27 to 2.47), in association with history of previous CS (OR 4.81, 95% CI 3.24 to 7.15) and in women with abnormal amniotic fluid (OR 2.30, 95% CI 1.55 to 3.41). Additionally, women with hypertensive disorders had a 176% increased risk of emergency CS (OR 2.76, 95% CI 1.35-5.63). Of note, the risk of emergency CS was more than three times higher in women who delivered a small for gestational age infant (OR 3.29, 95% CI 1.93-5.59). Based on the number of risk factors, a prediction model was developed, about 80% of pregnant women in the emergency CS group scored higher grades compared to control group. The area under the curve was 0.72, indicating a good discriminant ability of the model. Conclusion: This study identified several risk factors associated with emergency CS in pregnant Saudi women. A prediction model showed 72% accuracy in predicting the likelihood of emergency CS. This information can be useful to individualize the risk of emergency CS, and to implement appropriate measures to prevent unnecessary CS.
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Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article

Texto completo: 1 Base de dados: MEDLINE Tipo de estudo: Prognostic_studies / Risk_factors_studies Idioma: En Ano de publicação: 2023 Tipo de documento: Article