Placenta previa, anemia, care in antenatal, employment score: Development of a scoring system to predict low birth weight in underserved area in Indonesia
Journal Title: National Journal of Physiology, Pharmacy and Pharmacology - Year 2017, Vol 7, Issue 2
Abstract
Background: Early intervention of low birth weight (LBW) should reduce maternal and fetal morbidity. In underserved areas, with inadequacy of health technologies, it was very important to develop a simple scoring system based on the LBW risk factors. Aims and Objective: The aim of this study is to develop a scoring system to predict LBW in underserved area. Materials and Methods: This case–control study enrolled total of women with a singleton LBW in Padang Sidempuan General Hospital. For every case, the subsequent woman who delivered a baby weighing ≥2500 g acted as control. All data were by Chi-square or Fisher’s exact test. Significant variables were taken to be analyzed in backward stepwise binary regression. Then, receiver operating characteristic curve was developed to determine cutoff point and diagnostic value. This was done by SPSS (Statistical Product and Service Solutions, Chicago, IL, USA) 22.0 with 95% confidence interval significant value. Results: This study involved 62 LBW and 62 normal birth weight newborns. Among all variables, only four variables were found to be significant, such as employment, antenatal care, history of anemia in pregnancy, and history of placenta previa in pregnancy. The placenta previa, anemia, care in antenatal, employment (PACE) score was obtained as score for employment was +1, antenatal care was −2, history of anemia in pregnancy was +2, and history of placenta previa was +3. The cutoff point was determined as 0, where a positive score will predict fetal with LBW and total score ≤0 (negative) will predict fetal with normal weight. This model had sensitivity of 88.7%, specificity of 66.1%, and area under curve 0.844 (P < 0.001). Conclusion: Positive total score of PACE could be a promising predictor for LBW in underserved area.
Authors and Affiliations
Sarma Nursani Lumbanraja
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