扬州市妇幼保健院产科,江苏 扬州 225002
杨林,第一作者,研究方向: 妊娠期高血压疾病、高危孕产妇的孕期管理,E-mail: 65892268@qq.com
收稿:2024-10-28,
修回:2024-12-12,
录用:2024-12-20,
纸质出版:2025-01-20
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杨林,王亦雄,潘辉等.妊娠晚期缺铁性贫血的危险因素和列线图预测模型[J].中山大学学报(医学科学版),2025,46(01):116-122.
YANG Lin,WANG Yixiong,PAN Hui,et al.Risk Factors and Nomogram Prediction Model for Iron Deficiency Anemia in Late Pregnancy[J].Journal of Sun Yat-sen University(Medical Sciences),2025,46(01):116-122.
杨林,王亦雄,潘辉等.妊娠晚期缺铁性贫血的危险因素和列线图预测模型[J].中山大学学报(医学科学版),2025,46(01):116-122. DOI: 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).2025.0113.
YANG Lin,WANG Yixiong,PAN Hui,et al.Risk Factors and Nomogram Prediction Model for Iron Deficiency Anemia in Late Pregnancy[J].Journal of Sun Yat-sen University(Medical Sciences),2025,46(01):116-122. DOI: 10.13471/j.cnki.j.sun.yat-sen.univ(med.sci).2025.0113.
目的
2
对孕妇妊娠期缺铁性贫血(IDA)的相关因素进行分析,根据其独立的危险因素,构建预测妊娠晚期缺铁性贫血的列线图预测模型,以期获得IDA的有效干预方案。
方法
2
将2022年7月—2023年12月在扬州市妇幼保健院定期产检的孕妇为调查对象,采取统一调查问卷结合监测血常规的方法跟踪孕妇直至分娩,入组500例,最终完成482例。根据孕晚期有无IDA分为IDA组与非IDA组。对可能影响缺铁性贫血的危险因素进行单因素分析及多因素logistic回归分析,并采用R软件建立预测发生的列线图模型。
结果
2
482例妊娠晚期女性发生IDA有96例,发生率为19.92%;单因素分析显示,经济独立情况、孕前体质指数、孕次及孕期有无正规补铁与妊娠晚期IDA的发生有关,差异均有统计学意义(
P
<0.05)。多因素Logistic回归分析显示,经济独立(
P
=0.031,OR=0.583)、孕期正规补铁(
P
<
0.001,OR=5.337)是IDA的保护因素;孕前低体质指数(
P
=0.021,OR=2.375),孕次≥3次(
P
=0.015,OR=2.253)是IDA的危险因素。ROC曲线显示,列线图模型预测IDA发生的曲线下面积为0.84,最佳截断值为-1.481,预测灵敏度为81.2%,特异度分别为75.1%。
结论
2
妊娠晚期IDA发病率较高;孕前低体质指数、孕次大于3次是妊娠晚期IDA的危险因素;经济独立、正规补铁是妊娠晚期IDA的保护因素。可利用上述因素构建预测模型、采取预防性措施研究降低妊娠晚期IDA发病率的可行性方案。
Objective
2
This study aims to identify potential risk factors, establish a nomogram prediction model and propose intervention strategies for iron deficiency anemia (IDA) in late pregnancy.
Methods
2
Questionnaire surveys and routine blood tests were performed on pregnant women who received regular antenatal check-ups at Yangzhou Maternal and Child Health Hospital from July 2022 to December 2023. Of the 500 cases enrolled, 482 completed the trial and were divided into IDA and non-IDA groups based on the presence of IDA in the third trimester. Univariate analysis and multivariate logistic regression were employed to identify risk factors for IDA, while R software was used to construct a nomogram prediction model.
Results
2
The incidence of IDA in late pregnancy was 19.92% (96/482). Univariate analysis revealed significant associations between IDA in late pregnancy and factors such as economic independence, preconception body mass index (BMI), number of pregnancies, and regular iron supplementation during pregnancy (
P
<
0.05). Multivariate logistic regression showed that economic independence (
P
=0.031, OR=0.583) and regular iron supplementation during pregnancy (
P
<
0.001, OR=5.337) were protective factors against IDA. Conversely, a low preconception BMI (
P
=0.021, OR=2.375) and three or more pregnancies (
P
=0.015, OR=2.253) emerged as significant risk factors. The receiver operating characteristic (ROC) curve analysis demonstrated that the area under the curve (AUC) for the nomogram predicting IDA was 0.84, with an optimal cutoff value of -1.481, a sensitivity of 81.2% and a specificity of 75.1%.
Conclusions
2
The incidence of IDA in late pregnancy is quite high. A low preconception BMI and three or more pregnancies are risk factors, while economic independence and regular iron supplementation are protective factors. These insights have enabled the construction of a prediction model, which, in turn, could provide guidance for prediction and treatment of IDA in late pregnancy.
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