Recognizing who is at risk for postpartum hemorrhage: targeting anemic women and scoring systems for clinical use

Abstract

Iron deficiency anemia during pregnancy is a common concern, affecting 38% of women worldwide and up to 50% in developing countries. It is defined differently throughout all 3 trimesters. It has several detrimental effects on pregnancy outcomes for both the mother and the fetus, such as increasing the risk for postpartum depression, preterm delivery, cesarean delivery, preeclampsia, and low birthweight. Management of iron deficiency anemia is done classically via oral iron supplementation. However, recent evidence has shown that intravenous iron is a good alternative to oral iron if patients are unable to tolerate it, not responding, or present with a new diagnosis very late in pregnancy. Management of iron deficiency anemia was demonstrated to be protective against postpartum hemorrhage. Other ways to prevent postpartum hemorrhage include improving prediction tools that can identify those at risk. Several risk assessment kits have been developed to estimate the risk for postpartum hemorrhage among patients and have been proven useful in the prediction of patients at high risk for postpartum hemorrhage despite limitations among low-risk groups. More comprehensive tools are also being explored by determining clinically relevant factors through nomograms, with some proving their efficacy after implementation. Machine learning is also being used to develop more complete tools by including risk factors previously not accounted for. These newer tools, however, still require external validation before being adopted despite promising results under testing conditions.

Keywords: iron deficiency anemia; iron supplementation; maternal morbidity; obstetrical hemorrhage; postpartum hemorrhage; prevention.