Yonsei Med J.  2020 Feb;61(2):154-160. 10.3349/ymj.2020.61.2.154.

Prediction Model for Massive Transfusion in Placenta Previa during Cesarean Section

Affiliations
  • 1Department of Obstetrics and Gynecology, Yonsei University Wonju College of Medicine, Wonju, Korea. choisj@yonsei.ac.kr
  • 2Center of Biomedical Data Science, Yonsei University Wonju College of Medicine, Wonju, Korea.
  • 3Department of Anesthesiology and Pain Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea.
  • 4Department of Laboratory Medicine, Yonsei University Wonju College of Medicine, Wonju, Korea.
  • 5Department of Obstetrics and Gynecology, School of Medicine, Kangwon National University, Chuncheon, Korea.
  • 6Department of Precision Medicine and Biostatistics, Yonsei University Wonju College of Medicine, Wonju, Korea.

Abstract

PURPOSE
Recently, obstetric massive transfusion protocols have shifted toward early intervention. This study aimed to develop a prediction model for transfusion of ≥5 units of packed red blood cells (PRBCs) during cesarean section in women with placenta previa.
MATERIALS AND METHODS
We conducted a cohort study including 287 women with placenta previa who delivered between September 2011 and April 2018. Univariate and multivariate logistic regression analyses were used to test the association between clinical factors, ultrasound factors, and massive transfusion. For the external validation set, we obtained data (n=50) from another hospital.
RESULTS
We formulated a scoring model for predicting transfusion of ≥5 units of PRBCs, including maternal age, degree of previa, grade of lacunae, presence of a hypoechoic layer, and anterior placentation. For example, total score of 223/260 had a probability of 0.7 for massive transfusion. Hosmer-Lemeshow goodness-of-fit test indicated that the model was suitable (p>0.05). The area under the receiver operating characteristics curve (AUC) was 0.922 [95% confidence interval (CI) 0.89-0.95]. In external validation, the discrimination was good, with an AUC value of 0.833 (95% CI 0.70-0.92) for this model. Nomogram calibration plots indicated good agreement between the predicted and observed outcomes, exhibiting close approximation between the predicted and observed probability.
CONCLUSION
We constructed a scoring model for predicting massive transfusion during cesarean section in women with placenta previa. This model may help in determining the need to prepare an appropriate amount of blood products and the optimal timing of blood transfusion.

Keyword

Blood transfusion; cesarean section; placenta previa; postpartum hemorrhage; prediction model

MeSH Terms

Area Under Curve
Blood Transfusion
Calibration
Cesarean Section*
Cohort Studies
Discrimination (Psychology)
Early Intervention (Education)
Erythrocytes
Female
Humans
Logistic Models
Maternal Age
Nomograms
Placenta Previa*
Placenta*
Placentation
Postpartum Hemorrhage
Pregnancy
ROC Curve
Ultrasonography
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