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A Regression Model for Prediction of Cesarean-Associated Blood Transfusion.

Publication ,  Journal Article
Albright, CM; Spillane, TE; Hughes, BL; Rouse, DJ
Published in: Am J Perinatol
July 2019

OBJECTIVE: To develop a model to predict cesarean-associated red blood cell transfusion. STUDY DESIGN: Secondary analysis of all cesarean deliveries in the Maternal-Fetal Medicine Units Network Cesarean Registry. Using a split-sample technique, the derivation group was used to identify associated factors and build predictive models, and the validation group was used to estimate classification errors and determine test characteristics. Using factors available at the time of cesarean, we developed a multivariable logistic regression prediction model. RESULTS: A total of 59,468 women were split evenly and randomly into the derivation and validation groups. The overall rate of transfusion was 2.7%. The area under the receiver operating characteristic curve for the derivation and validation groups were 0.82 (95% confidence interval [CI]: 0.80-0.84) and 0.84 (95% CI: 0.82-0.85), respectively (p = 0.16). The strongest predictors of transfusion were placenta previa (odds ratio [OR]: 7.06, 95% CI: 5.19-9.61) and eclampsia/Hemolysis Elevated Liver Enzymes Low Platelets syndrome (OR: 5.67, 95% CI: 3.77-8.51). In the validation group, the model had a sensitivity, specificity, positive, and negative predictive values of 55.8, 91.5, 16.2, and 98.6%, respectively. Overall, 90.5% of patients were correctly classified. CONCLUSION: A regression model incorporating variables available at the time of cesarean accurately predicts the need for intra- or postoperative transfusion.

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Published In

Am J Perinatol

DOI

EISSN

1098-8785

Publication Date

July 2019

Volume

36

Issue

9

Start / End Page

879 / 885

Location

United States

Related Subject Headings

  • Sensitivity and Specificity
  • Risk Factors
  • Risk Assessment
  • ROC Curve
  • Pregnancy
  • Placenta Previa
  • Obstetrics & Reproductive Medicine
  • Logistic Models
  • Humans
  • Female
 

Citation

APA
Chicago
ICMJE
MLA
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Albright, C. M., Spillane, T. E., Hughes, B. L., & Rouse, D. J. (2019). A Regression Model for Prediction of Cesarean-Associated Blood Transfusion. Am J Perinatol, 36(9), 879–885. https://doi.org/10.1055/s-0039-1678604
Albright, Catherine M., Timothy E. Spillane, Brenna L. Hughes, and Dwight J. Rouse. “A Regression Model for Prediction of Cesarean-Associated Blood Transfusion.Am J Perinatol 36, no. 9 (July 2019): 879–85. https://doi.org/10.1055/s-0039-1678604.
Albright CM, Spillane TE, Hughes BL, Rouse DJ. A Regression Model for Prediction of Cesarean-Associated Blood Transfusion. Am J Perinatol. 2019 Jul;36(9):879–85.
Albright, Catherine M., et al. “A Regression Model for Prediction of Cesarean-Associated Blood Transfusion.Am J Perinatol, vol. 36, no. 9, July 2019, pp. 879–85. Pubmed, doi:10.1055/s-0039-1678604.
Albright CM, Spillane TE, Hughes BL, Rouse DJ. A Regression Model for Prediction of Cesarean-Associated Blood Transfusion. Am J Perinatol. 2019 Jul;36(9):879–885.
Journal cover image

Published In

Am J Perinatol

DOI

EISSN

1098-8785

Publication Date

July 2019

Volume

36

Issue

9

Start / End Page

879 / 885

Location

United States

Related Subject Headings

  • Sensitivity and Specificity
  • Risk Factors
  • Risk Assessment
  • ROC Curve
  • Pregnancy
  • Placenta Previa
  • Obstetrics & Reproductive Medicine
  • Logistic Models
  • Humans
  • Female