| Multivariate Analysis of Variables Affecting on Fetal Heart Rate. |
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Moon Il Park, Won Jun Lee, Chung Han Lee, Kee Don Kim, Myung Kul Yun, Young Sun Park, Kyung Joon Cha |
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| Abstract |
OBJECTIVE
We aim to statistically analyze the variables affecting FHR using principal component analysis and multiple regression analysis. It is tried to find which variables significantly affect FHR. Thus, it would help further work of building objective decision basis to analyze variables affecting FHR. METHODS: The samples are chosen from pregnant women who took a NST at Hanyang University Hospital. It consists of 5,314 data which have been collected from 1989 to 1997. For collection of data and values of each variable, our own FHR interpretation softwares, HYFM-I (DOS version, since 1989) and HYFM-II (Windows version, since 1998) were used. Then, the principal component analysis is performed to find significant variable and multiple regression analysis is performed using these variables. RESULTS: The mean baseline FHR is not influenced by a specific factor in abnormal group. The gestational week, loss of signal, variability, and 5 minutes Apgar score are chosen as main effects through principal component analysis. From the results of regression analysis, it is noticed that 5 minutes Apgar score which is one of neonate prognosis after birth causes an increase of estimated FHR score (EFS), whereas the loss of signal causes a decrease of EFS. The variability in normal group is more active increasing factor of EFS than abnormal group. CONCLUSIONS: Based on gestational week, 5 minutes Apgar score is highly related with fetal maturity in both normal and abnormal groups. Also, it is found that different patterns of each variable by groups are due to delay of fetal growth that is caused by disease of a pregnant women. Thus, the further studies to build objective decision basis are need. |
| Key Words:
Principal component analysis, Estimated FHR, Computerized FHR monitoring, Multivariate analysis |
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