Development and validation of a nomogram for predicting low birth weight among pregnant women who had antenatal care visits at Debre Markos Comprehensive and Specialized Hospital, Ethiopia - Fente, Bezawit Melak; Tesema, Getayeneh Antehunegn; Gudayu, Temesgen Worku; Asaye, Mengstu Melkamu (Frontiers in Medicine, 2023)
Background: Birth weight is associated with newborn survival as well as future health, growth, and development. Previously, researchers focused on explaining the maternal and fetal factors of low birth weight. In recent years, the emphasis changed to optimally predicting low birth weight utilizing a combination of variables. This study aim to develop and validate a nomogram for predicting low birth weight in Ethiopian.A retrospective follow-up study was conducted and a total of 1,120 pregnant women were included. Client charts were selected using a simple random sampling technique. Data were extracted using structured checklist prepared on the Kobo Toolbox and exported to STATA version 14 and R version 4.2.2 for data management and analysis. A nomogram was developed based on a binary logistic model, and its performance was assessed by discrimination power and calibration. Internal validation was performed by using bootstrapping. To evaluate the clinical impact, decision curve analysis was applied.Results: Nomogram included gestational age, hemoglobin, primigravida, unplanned pregnancy, and preeclampsia. The AUROC of the predicted nomogram was 84.3% and internal validation was 80.1%. Calibration plot showed that the nomogram had well calibrated. The model was found to have clinical benefit.The nomogram has good discrimination performance and can predict low birth weight clinically. As a result, it can be used in clinical practice. It will help clinicians make personalized predictions simply and rapidly, enabling early identification and medical intervention. To apply other facilities, the nomogram must be externally validate.