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Am J Perinatol 2024; 41(S 01): e3391-e3400
DOI: 10.1055/a-2234-8171
Original Article

Validation of Three Models for Prediction of Blood Transfusion during Cesarean Delivery Admission

Ann M. Bruno
1   Department of Obstetrics and Gynecology, University of Utah Health Sciences Center, Salt Lake City, Utah
,
Jerome J. Federspiel 
2   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Duke University School of Medicine, Durham, North Carolina
,
Paula McGee
3   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The George Washington University Biostatistics Center, Washington, District of Columbia
,
Luis D. Pacheco
4   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, Texas
,
George R. Saade
4   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Texas Medical Branch, Galveston, Texas
,
Samuel Parry
5   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Pennsylvania, Philadelphia, Pennsylvania
,
Monica Longo
6   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Eunice Kennedy Shriver National Institute of Child Health and Human Development, Bethesda, Maryland
,
Alan T.N. Tita
7   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Alabama at Birmingham, Birmingham, Alabama
,
Cynthia Gyamfi-Bannerman
8   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Columbia University, New York, New York
,
Suneet P. Chauhan
9   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Texas Health Science Center at Houston, Children's Memorial Hermann Hospital, Houston, Texas
,
Brett D. Einerson
1   Department of Obstetrics and Gynecology, University of Utah Health Sciences Center, Salt Lake City, Utah
,
Kara Rood
10   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The Ohio State University, Columbus, Ohio
,
Dwight J. Rouse
11   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Brown University, Providence, Rhode Island
,
Jennifer Bailit
12   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, The MetroHealth Medical System, Case Western Reserve University, Cleveland, Ohio
,
William A. Grobman
13   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, Northwestern University, Chicago, Illinois
,
Hyagriv N. Simhan
14   Division of Maternal-Fetal Medicine, Department of Obstetrics and Gynecology, University of Pittsburgh, Pittsburgh, Pennsylvania
,
for the Eunice Kennedy Shriver National Institute of Child Health Human Development Maternal-Fetal Medicine Units Network› Author Affiliations
Funding This work was funded by the Eunice Kennedy Shriver National Institute of Child Health and Human Development (UG1 HD087230, UG1 HD027869, UG1 HD027915, UG1 HD034208, UG1 HD040500, UG1 HD040485, UG1 HD053097, UG1 HD040544, UG1 HD040545, UG1 HD040560, UG1 HD040512, UG1 HD087192, and U24 HD036801). J.J.F. was supported by K12HD103083 during the completion of this work. A.M.B. was supported by K12HD085816 during the completion of this work. The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.
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Abstract

Objective Prediction of blood transfusion during delivery admission allows for clinical preparedness and risk mitigation. Although prediction models have been developed and adopted into practice, their external validation is limited. We aimed to evaluate the performance of three blood transfusion prediction models in a U.S. cohort of individuals undergoing cesarean delivery.

Study Design This was a secondary analysis of a multicenter randomized trial of tranexamic acid for prevention of hemorrhage at time of cesarean delivery. Three models were considered: a categorical risk tool (California Maternal Quality Care Collaborative [CMQCC]) and two regression models (Ahmadzia et al and Albright et al). The primary outcome was intrapartum or postpartum red blood cell transfusion. The CMQCC algorithm was applied to the cohort with frequency of risk category (low, medium, high) and associated transfusion rates reported. For the regression models, the area under the receiver-operating curve (AUC) was calculated and a calibration curve plotted to evaluate each model's capacity to predict receipt of transfusion. The regression model outputs were statistically compared.

Results Of 10,785 analyzed individuals, 3.9% received a red blood cell transfusion during delivery admission. The CMQCC risk tool categorized 1,970 (18.3%) individuals as low risk, 5,259 (48.8%) as medium risk, and 3,556 (33.0%) as high risk with corresponding transfusion rates of 2.1% (95% confidence interval [CI]: 1.5–2.9%), 2.2% (95% CI: 1.8–2.6%), and 7.5% (95% CI: 6.6–8.4%), respectively. The AUC for prediction of blood transfusion using the Ahmadzia and Albright models was 0.78 (95% CI: 0.76–0.81) and 0.79 (95% CI: 0.77–0.82), respectively (p = 0.38 for difference). Calibration curves demonstrated overall agreement between the predicted probability and observed likelihood of blood transfusion.

Conclusion Three models were externally validated for prediction of blood transfusion during cesarean delivery admission in this U.S. cohort. Overall, performance was moderate; model selection should be based on ease of application until a specific model with superior predictive ability is developed.

Key Points

  • A total of 3.9% of individuals received a blood transfusion during cesarean delivery admission.

  • Three models used in clinical practice are externally valid for blood transfusion prediction.

  • Institutional model selection should be based on ease of application until further research identifies the optimal approach.

Keywords

blood preparedness - CMQCC risk tool - external validation - prediction models - transfusion prediction

Note

This work was presented at the 43rd Annual Pregnancy Meeting, Society for Maternal-Fetal Medicine, February 6 to 11, 2023, San Francisco, CA.


Supplementary Material



Publication History

Received: 17 November 2023

Accepted: 20 December 2023

Accepted Manuscript online:
22 December 2023

Article published online:
16 January 2024

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