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Article type: Research Article
Authors: Ahmadzia, H.K.a; * | Wiener, A.A.a | Felfeli, M.a | Berger, J.S.b | Macri, C.J.a | Gimovsky, A.C.a | Luban, N.L.c | Amdur, R.L.d
Affiliations: [a] Department of Obstetrics & Gynecology, Division of Maternal-Fetal Medicine, George Washington University, Washington, DC, USA | [b] Department of Anesthesiology and Critical Care Medicine, George Washington University, Washington, DC, USA | [c] Department of Pediatrics George Washington University, Division of Pediatric Hematology, Children’s National Hospital, Washington, DC, USA | [d] Department of Surgery, George Washington University, Washington, DC, USA
Correspondence: [*] Address for correspondence: Homa K. Ahmadzia, MD, MPH, 2150 Pennsylvania Ave NW, Washington, DC 20037, USA. Tel.: +1 202 741 3000, E-mail: [email protected].
Abstract: OBJECTIVE:The objective of this study is to develop a model that will help predict the risk of blood transfusion using information available prior to delivery. STUDY DESIGN:The study is a secondary analysis of the Consortium on Safe Labor registry. Women who had a delivery from 2002 to 2008 were included. Pre-delivery variables that had significant associations with transfusion were included in a multivariable logistic regression model predicting transfusion. The prediction model was internally validated using randomly selected samples from the same population of women. RESULTS:Of 156,572 deliveries, 5,463 deliveries (3.5%) required transfusion. Women who had deliveries requiring transfusion were more likely to have a number of comorbidities such as preeclampsia (6.3% versus 4.1%, OR 1.21, 95% CI 1.08–1.36), placenta previa (1.8% versus 0.4%, OR 4.11, 95% CI 3.25–5.21) and anemia (10.6% versus 5.4%, OR 1.30, 95% CI 1.21–1.41). Transfusion was least likely to occur in university teaching hospitals compared to community hospitals. The c statistic was 0.71 (95% CI 0.70–0.72) in the derivation sample. The most salient predictors of transfusion included type of hospital, placenta previa, multiple gestations, diabetes mellitus, anemia, asthma, previous births, preeclampsia, type of insurance, age, gestational age, and vertex presentation. The model was well-calibrated and showed strong internal validation. CONCLUSION:The model identified independent risk factors that can help predict the risk of transfusion prior to delivery. If externally validated in another dataset, this model can assist health care professionals counsel patients and prepare facilities/resources to reduce maternal morbidity.
Keywords: Blood transfusion, Consortium on Safe Labor, maternal morbidity, maternal mortality, postpartum hemorrhage, risk prediction model
DOI: 10.3233/NPM-230079
Journal: Journal of Neonatal-Perinatal Medicine, vol. 16, no. 3, pp. 375-385, 2023
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