ArticleWorld journal of clinical cases2024
Influence of perinatal factors on full-term low-birth-weight infants and construction of a predictive model.
Article in World journal of clinical cases, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.
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1 citing paper in PubMed.
- Developing predictive models for full-term low birth weight infants using ten machine learning algorithms.BMC pediatrics · 2025Article
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7 authors.
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Abstract
backgroundBeing too light at birth can increase the risk of various diseases during infancy.
aimTo explore the effect of perinatal factors on term low-birth-weight (LBW) infants and build a predictive model. This model aims to guide the clinical management of pregnant women's healthcare during pregnancy and support the healthy growth of newborns.
methodsA retrospective analysis was conducted on data from 1794 single full-term pregnant women who gave birth. Newborns were grouped based on birth weight: Those with birth weight < 2.5 kg were classified as the low-weight group, and those with birth weight between 2.5 kg and 4 kg were included in the normal group. Multiple logistic regression analysis was used to identify the factors influencing the occurrence of full-term LBW. A risk prediction model was established based on the analysis results. The effectiveness of the model was analyzed using the Hosmer-Leme show test and receiver operating characteristic (ROC) curve to verify the accuracy of the predictions.
resultsAmong the 1794 pregnant women, there were 62 cases of neonatal weight < 2.5 kg, resulting in an LBW incidence rate of 3.46%. The factors influencing full-term LBW included low maternal education level [odds ratio (OR) = 1.416], fewer prenatal examinations (OR = 2.907), insufficient weight gain during pregnancy (OR = 3.695), irregular calcium supplementation during pregnancy (OR = 1.756), and pregnancy hypertension syndrome (OR = 2.192). The prediction model equation was obtained as follows: Logit (
conclusionThe occurrence of full-term LBW is related to maternal education, the number of prenatal examinations, weight gain during pregnancy, calcium supplementation during pregnancy, and pregnancy-induced hypertension. The constructed predictive model can effectively predict the risk of full-term LBW.
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