Modified Biophysical Profile In Antepartum Fetal Surveillance Of High Risk Pregnancies

Abstract

Background: Fetal biophysical profile is a well established method of antepartum surveillance in high risk pregnancy. Classical biophysical profile with all parameters (fetal breathing movements, fetal tone, fetal gross body movements, amniotic fluid volume and non-stress test) needs two phase testing by ultrasound and external Doppler monitor to record fetal heart rate, is more cumbersome, time consuming and expensive. The modified biophysical profile (MBPP) suggested by Nageotte et al combines Non stress test (NST) as a short term marker of fetal status and the amniotic fluid index (AFI) as marker of long term placental function is easier to perform and less time consuming than classical biophysical profile. Objectives:- 1) To study the effectiveness of using modified biophysical profile as a primary antepartum fetal surveillance test in predicting perinatal outcome. 2) To compare the morbidity and mortality with respect to each of the parameters of modified biophysical profile, that is NST and AFI individually. Methods:- This study was a prospective clinical study which consisted of 70 patients having pregnancy with high risk factors. The patients were evaluated with the modified biophysical profile consisting of NST recording for 20mins, followed ultrasound assessment of amniotic fluid volume, using four quadrant technique.

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Results :-  When the Modified biophysical profile is normal, it gives reassurance that the foetal status is good with good perinatal outcome.  When the MBPP is abnormal there is increased incidence of perinatal morbidity as well as mortality. When considered individually, abnormal AFI was associated with increased incidence of perinatal morbidity and abnormal NST was associated with increased incidence of perinatal morbidity as well as perinatal mortality. Interpretation and conclusion:- Modified biophysical profile is an effective primary antepartum fetal surveillance test in high risk pregnancies in predicting perinatal outcome.