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. 2025 Apr;2(2):e078.
doi: 10.1097/og9.0000000000000078. Epub 2025 Apr 24.

Development of a Risk-Scoring System for Prediction of Blood Transfusion During Hospitalization for Delivery

Affiliations

Development of a Risk-Scoring System for Prediction of Blood Transfusion During Hospitalization for Delivery

Ann M Bruno et al. O G Open. 2025 Apr.

Abstract

Objective: To develop and internally validate a practical and data-driven risk-scoring system to predict blood transfusion during hospitalization for delivery in a contemporary U.S. cohort.

Methods: This was a secondary analysis of a multicenter cohort of patients who delivered on randomly selected days at 17 U.S. hospitals (2019-2020). Patients with placenta accreta spectrum were excluded. The primary outcome was any blood transfusion during hospitalization for delivery. Candidate risk factors for transfusion were selected based on relevant literature. A multivariable logistic regression model was developed and internally validated using stratified k-fold (k=5) cross validation with stepwise backward elimination that used significance level of 0.05. Each risk factor included in the final model was assigned a point value by dividing the log of the odds ratio (OR) by the log of the OR of the factor with the lowest value. The summed points for an individual generate a numeric risk score predictive of transfusion. Performance of the risk score to predict transfusion was assessed using the area under the receiver operating curve (AUC).

Results: Of 21,780 included individuals, 2.5% (n=545) received a blood transfusion. Factors associated with the highest risk for transfusion in the final model included thrombocytopenia, and placental abruption or significant antepartum bleeding. Risk score outputs among patients in the cohort ranged from 0 to 17 (maximum possible 26) with a corresponding predicted risk for transfusion from 1.0% to 84.4%. The AUC for prediction of transfusion in the validation subsample was 0.81 (95% CI, 0.76-0.85).

Conclusion: We developed a clinically applicable numeric risk score to predict blood transfusion during hospitalization for delivery. Future work should externally validate this risk-scoring system.

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Conflict of interest statement

Financial Disclosure Brenna L. Hughes reported receiving payment from UpToDate, ABOG, and Moderna. The other authors did not report any potential conflicts of interest.

Figures

Fig. 1.
Fig. 1.. Receiver operating characteristic curve for the developed risk-scoring system to predict blood transfusion during hospitalization for delivery. The area under the receiver operating curve (AUC) was 0.77 (95% CI, 0.74–0.79) for the full cohort and 0.81 (95% CI, 0.76–0.85) for the validation subset.
Fig. 2.
Fig. 2.. Estimated blood transfusion risk (%) based on numeric risk score. The y-axis estimates the blood transfusion risk (%) by the x-axis numeric risk score for an individual (range 0–26). The minimum risk (score=0) is estimated at 1% and ranges to maximum risk (score=26) of 99.3%.

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