Ultrasound in obstetrics & gynecology : the official journal of the International Society of Ultrasound in Obstetrics and Gynecology · 2015
Fetal middle cerebral artery and umbilical artery pulsatility index: effects of maternal characteristics and medical history.
СтатьяПоддержка исследования: вне правительства СШАНазвание и аннотация: Перевод в очереди
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Akolekar R, Sarno L, Wright A, Wright D, Nicolaides K H
Аннотация
OBJECTIVE: To define the contribution of maternal variables which influence the measured fetal middle cerebral artery (MCA) and umbilical artery (UA) pulsatility index (PI) in the assessment of fetal wellbeing.
METHODS: Maternal characteristics and medical history were recorded and fetal MCA-PI and UA-PI (n = 36,818) were measured in women with singleton pregnancies attending a routine hospital visit at 30 + 0 to 37 + 6 weeks' gestation. For pregnancies delivering phenotypically normal live births or stillbirths ≥ 30 weeks' gestation, variables among maternal demographic characteristics and medical history that are important in the prediction of MCA-PI and UA-PI were determined by multiple linear regression analysis.
RESULTS: Significant independent contributions to MCA-PI were provided by gestational age at assessment, East Asian racial origin, being parous and birth-weight Z-score of the neonate of the previous pregnancy. Significant independent contributions to UA-PI were provided by gestational age at assessment, Afro-Caribbean, East Asian and mixed racial origin, cigarette smoking, being parous and birth-weight Z-score of the neonate of the previous pregnancy. Multiple linear regression analysis was used to define the contribution of maternal variables that influence the measured MCA-PI and UA-PI and express the values as multiples of the median (MoMs). The cerebroplacental ratio (CPR) MoM was calculated by dividing MCA-PI MoM by UA-PI MoM. The model was shown to provide an adequate fit of MoM values for all covariates, both in pregnancies that delivered small-for-gestational-age neonates and in those without this pregnancy complication.
CONCLUSIONS: A model was fitted to express MCA-PI, UA-PI and CPR as MoMs after adjusting for variables from maternal characteristics and medical history that affect this measurement.
METHODS: Maternal characteristics and medical history were recorded and fetal MCA-PI and UA-PI (n = 36,818) were measured in women with singleton pregnancies attending a routine hospital visit at 30 + 0 to 37 + 6 weeks' gestation. For pregnancies delivering phenotypically normal live births or stillbirths ≥ 30 weeks' gestation, variables among maternal demographic characteristics and medical history that are important in the prediction of MCA-PI and UA-PI were determined by multiple linear regression analysis.
RESULTS: Significant independent contributions to MCA-PI were provided by gestational age at assessment, East Asian racial origin, being parous and birth-weight Z-score of the neonate of the previous pregnancy. Significant independent contributions to UA-PI were provided by gestational age at assessment, Afro-Caribbean, East Asian and mixed racial origin, cigarette smoking, being parous and birth-weight Z-score of the neonate of the previous pregnancy. Multiple linear regression analysis was used to define the contribution of maternal variables that influence the measured MCA-PI and UA-PI and express the values as multiples of the median (MoMs). The cerebroplacental ratio (CPR) MoM was calculated by dividing MCA-PI MoM by UA-PI MoM. The model was shown to provide an adequate fit of MoM values for all covariates, both in pregnancies that delivered small-for-gestational-age neonates and in those without this pregnancy complication.
CONCLUSIONS: A model was fitted to express MCA-PI, UA-PI and CPR as MoMs after adjusting for variables from maternal characteristics and medical history that affect this measurement.