No abstract available.
Birth Weight* ; Female ; Fetal Heart* ; Heart Rate, Fetal* ; Parturition* ; Pregnancy

OBJECTIVE: Nonstress test(NST) has become an important method of antepartum evaluation of fetal well-being. The fetal heart rate(FHR) testing is used frequently as a nonstress test(NST). However, NST highly depends on whom to interpret the result of FHR testing. Recently, for interpretation of FHR, objective decision methods using softwares have been introduced. In this study, we aim to analyse the correlation between each variable affecting FHR and fetal outcome using objective decision basis with principal component analysis and multiple regression analysis. MATERIALS AND METHODS: The clinical observation was made on 5,314 data from pregnant women who took a NST which had been collected from 1989 to 1997 at Hanyang University Hospital. For collection of data and values of each variable, we used our own FHR interpretation softwares, HYFM-I(DOS version, 1989) and HYFM-II(Window-version, 1998). Then, the principal component analysis is performed to find significant variable and multiple regression analysis using these variables. RESULTS: Each groups were divided and classified as followings ; 1 minute Apgar score-normal, 1 minute Apgar score-abnormal, 5 minute Apgar score-nomal, 5 minutes Apgar score-abnormal; there is significant difference between signal loss and 1 minute Apgar score only. And significant difference was shown between mean baseline FHR, FHR variability-amplitude, FHR variability-MMR, and fetal outcomes(body weight of newborn & Apgar score). The FHR variability-amplitude, FHR variability-MMR, and weight of baby were important values in predict of fetal well-being. CONCLUSIONS: In conclusion, there are close relation in each variable of FHRand fetal outcome. The result of this study would be useful background data in the development of objective and automated FHR analysis software, especially in the computerized FHR analysis system.
Apgar Score ; Female ; Fetal Heart* ; Heart Rate, Fetal* ; Humans ; Infant, Newborn* ; Pregnancy ; Pregnant Women ; Principal Component Analysis

OBJECTIVES: To investigate the relationship of internet addiction and depression, and evaluate other possible related factors. METHODS: Data was based on the questionnaires from 300 college students in Seoul. Gender, age, major, family income, academic performance, people they live with, location, and main use of internet were included. We used Young`s Internet Addiction Test and Beck Depression Inventory(BDI) to measure the depression and addiction degree. RESULTS: In logistic regression analysis, it was found that gender, depression degree and main use of internet were significant variables. There were 136 males, 144 females in this study, and the risk of being addicted to internet were 10.9 times(CI:2.67~44.68) higher in male than female. People with moderate depression (Beck`s Depression Inventory(BDI) Score>20) also had higher risk(11.4 times, CI:2.03~63.95) to be addicted in internet than normal group. Lastly, in case of internet use, people who use internet for games and chatting were 6.38(CI:1.38~29.63) and 4.84 times(CI:1.30~18.06) risky compare to the group with web surfing. CONCLUSION: The result of this study suggests that there is noticeable relationship of internet addiction and depression. However we do not have evidence of exact relation between them, therefore more studies should be done.
Depression* ; Female ; Humans ; Internet* ; Logistic Models ; Male ; Seoul ; Surveys and Questionnaires