Xu Liang, Sheng Xue-Juan, Gu Lian-Ping, Yang Zu-Ming, Feng Zong-Tai, Gu Dan-Feng, Gao Li
Department of Neonatology, Suzhou Ninth People's Hospital, Suzhou 215200, Jiangsu Province, China.
Department of Obstetrics, Suzhou Ninth People's Hospital, Suzhou 215200, Jiangsu Province, China.
World J Clin Cases. 2024 Sep 16;12(26):5901-5907. doi: 10.12998/wjcc.v12.i26.5901.
Being too light at birth can increase the risk of various diseases during infancy.
To 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.
A 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.
Among 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 () = 0.348 × maternal education level + 1.067 × number of prenatal examinations + 1.307 × insufficient weight gain during pregnancy + 0.563 × irregular calcium supplementation during pregnancy + 0.785 × pregnancy hypertension syndrome - 29.164. The area under the ROC curve for this model was 0.853, with a sensitivity of 0.852 and a specificity of 0.821. The Hosmer-Leme show test yielded = 2.185, = 0.449, indicating a good fit. The overall accuracy of the clinical validation model was 81.67%.
The 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.
出生时体重过轻会增加婴儿期患各种疾病的风险。
探讨围产期因素对足月低体重(LBW)婴儿的影响,并建立预测模型。该模型旨在指导孕期孕妇保健的临床管理,支持新生儿健康成长。
对1794名单胎足月分娩的孕妇的数据进行回顾性分析。新生儿根据出生体重分组:出生体重<2.5kg者分为低体重组,出生体重在2.5kg至4kg之间者纳入正常组。采用多因素logistic回归分析确定影响足月低体重发生的因素。根据分析结果建立风险预测模型。使用Hosmer-Lemeshow检验和受试者工作特征(ROC)曲线分析模型的有效性,以验证预测的准确性。
1794名孕妇中,新生儿体重<2.5kg者62例,低体重发生率为3.46%。影响足月低体重的因素包括母亲文化程度低[比值比(OR)=1.416]、产前检查次数少(OR=2.907)、孕期体重增加不足(OR=3.695)、孕期补钙不规律(OR=1.756)和妊娠高血压综合征(OR=2.192)。得到预测模型方程如下:Logit()=0.348×母亲文化程度+1.067×产前检查次数+1.307×孕期体重增加不足+0.563×孕期补钙不规律+0.785×妊娠高血压综合征-29.164。该模型的ROC曲线下面积为0.853,灵敏度为0.852,特异度为0.821。Hosmer-Lemeshow检验结果为=2.185,=0.4,49,表明拟合良好。临床验证模型的总体准确率为81.67%。
足月低体重的发生与母亲文化程度、产前检查次数、孕期体重增加、孕期补钙及妊娠高血压有关。构建的预测模型能有效预测足月低体重的风险。