Peking University People's Hospital, Beijing 100044, China.
Faculty of Environment and Life Sciences, Beijing University of Technology, Beijing 100124, China.
Technol Health Care. 2021;29(S1):345-350. doi: 10.3233/THC-218032.
Monitoring fetal weight during pregnancy has a guiding role in prenatal care.
To establish a personalized fetal growth curve for effectively monitoring fetal growth during pregnancy.
(1) This study retrospectively analyzed the birth weight database of 2,474 singleton newborns delivered normally at term. The personalized fetal growth curve model was formed by combining the estimating birth weight of newborns with the proportional weight formula. (2) Multiple linear stepwise regression method was used to estimate the birth weight of newborns.
(1) Delivery gestational age, weight at first visit, maternal height, pre-pregnancy body mass index, fetal sex, parity had significant effects on birth weight. Based on these parameters, the formula for calculating term optimal weight was obtained (R2= 22.8%, P< 0.001). (2) The personalized fetal growth curve was obtained according to the epidemiological factors input model of each pregnant woman.
A model of personalized fetal growth curve can be established, and be used to evaluate fetal growth and development through estimated fetal weight monitoring.
监测孕期胎儿体重对产前保健具有指导作用。
建立个性化胎儿生长曲线，以有效监测孕期胎儿生长情况。
（1）本研究回顾性分析了 2474 例足月正常分娩单胎新生儿的出生体重数据库。通过结合新生儿估计体重和比例体重公式，形成个性化胎儿生长曲线模型。（2）采用多元线性逐步回归方法估计新生儿的出生体重。
（1）分娩胎龄、初诊时体重、产妇身高、孕前体重指数、胎儿性别、产次对出生体重有显著影响。基于这些参数，得出了计算足月最佳体重的公式（R2=22.8%，P<0.001）。（2）根据每位孕妇的流行病学因素输入模型，获得了个性化胎儿生长曲线。
可以建立个性化胎儿生长曲线模型，通过估计胎儿体重监测评估胎儿生长发育情况。
