Objective: To compare intravenous ferric carboxymaltose, intravenous ferric derisomaltose and oral ferrous sulphate for treatment of postpartum anemia. Design: Single-center, open-label, randomized trial. Setting: Tertiary perinatal center. Population: Three-hundred women with postpartum anemia (hemoglobin < 100 g/L within 48-hours postpartum) were included between September 2020 and March 2022. Methods: Women were randomly allocated to receive intravenous ferric carboxymaltose, intravenous ferric derisomaltose or oral ferrous sulphate. Intravenous iron was given in one or two doses, while ferrous sulphate as two 80 mg tablets once daily. Main outcome measures: Primary outcome was maternal fatigue measured by Multidimensional Fatigue Inventory (MFI) six weeks postpartum. Hemoglobin, ferritin and transferrin saturation levels were analyzed as secondary outcomes. Kruskal-Wallis test was used for group comparison (p<0.05 significant). Results: MFI score at six weeks postpartum did not differ between groups (median 38 (inter-quartile range (IQR) 20-74) in the ferric carboxymaltose, median 34 (IQR 20-70) in the ferric derisomaltose, and median 36 (IQR 20-72) in the ferrous sulphate group; p=0.26). Participants receiving oral iron had lower levels of hemoglobin (135 (119-150) vs 134 (113-157) vs 131 (125-137) g/L; p=0.008), ferritin (273 (198-377) vs 187 (155-246) vs 24 (17-37) µg/L; p<0.001) and transferrin saturation (34 (28–38) vs 30 (23–37) vs 24 (17-37) %; p<0.001) than those receiving ferric carboxymaltose or ferric derisomaltose. Conclusions: Intravenous ferric carboxymaltose, intravenous ferric derisomaltose and oral ferrous sulphate had similar impact on maternal fatigue at six weeks postpartum despite improved hematological laboratory parameters in the intravenous iron groups.
Postpartum anemia is a very common maternal health problem and remains a persistent public health issue globally. It negatively affects maternal mood and could lead to depression, increased fatigue, and decreased cognitive abilities. It can and should be treated by restoring iron stores. However, in most health systems, there is typically a six-week gap between birth and the follow-up postpartum visit. Risks of postpartum maternal complications are usually assessed shortly after birth by clinicians intuitively, taking into account psychosocial and physical factors, such as the presence of anemia and the type of iron supplementation. In this paper, we investigate the possibility of using machine-learning algorithms to more reliably forecast three parameters related to patient wellbeing, namely depression (measured by Edinburgh Postnatal Depression Scale—EPDS), overall tiredness, and physical tiredness (both measured by Multidimensional Fatigue Inventory—MFI). Data from 261 patients were used to train the forecasting models for each of the three parameters, and they outperformed the baseline models that always predicted the mean values of the training data. The mean average error of the elastic net regression model for predicting the EPDS score (with values ranging from 0 to 19) was 2.3 and outperformed the baseline, which already hints at the clinical usefulness of using such a model. We further investigated what features are the most important for this prediction, where the EDPS score and both tiredness indexes at birth turned out to be by far the most prominent prediction features. Our study indicates that the machine-learning model approach has the potential for use in clinical practice to predict the onset of depression and severe fatigue in anemic patients postpartum and potentially improve the detection and management of postpartum depression and fatigue.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.