Background: Earlier investigations have demonstrated that the accuracy of foetal weight
estimation is significantly higher if several ultrasonic foetal parameters are measured, because
the total body mass depends on the size of foetal head, abdominal circumference and femur
Aim: This study aimed to determine the best ultrasound regression models that use the common
foetal biometric measurements in predicting foetal weight for normal singleton pregnancies in
ClearVue 350 ultrasound equipment, and also assess the effects of few maternal anthropometric
variables on estimated foetal weight in the Greater Accra Metropolis.
Methodology: The study was quantitative, cross-sectional and quasi-experimental in nature and
was carried out prospectively in which convenient sampling method was used. Forty (40)
participants were scanned in the study. Foetal biparietal diameter, head circumference,
abdominal circumference and femur length measurements were measured according to the
established guidelines. Microsoft Excel and IBM SPSS soft-wares were used for data analysis.
Results: The study demonstrated that, all eight regression models showed no statistically
significant difference with (p-value <0.05) at 95% confidence interval of their mean foetal
weight estimates compared to the actual birth weight of the neonates. The mean and standard
deviations were similar across the eight models.
Conclusion: Findings from this study showed that, the best regressional model is Hadlock3
model. The study further revealed that, with 87% of estimated foetal weights which were within
5% of actual birth weights, demonstrate strong correlation between EFWs and ABWs, therefore
(radiologists, sonographers/radiographers)on one side and (gynaecologists, midwives) on the
other side can (to a high degree) rely on estimated foetal weights generated from Philips
CleaVue350 ultrasound equipment using the common foetal biometric measurements in a 2D
mode to generate meaningful reports and make important decisions such as mode of delivery
Edu, F (2021). Determining Best Regressional Model in Predicting Foetal Weight in Philips Clearview 350 Ultrasound Equipment. Afribary.com: Retrieved May 08, 2021, from https://afribary.com/works/determining-best-regressional-model-in-predicting-foetal-weight-in-philips-clearview-350-ultrasound-equipment
Frontiers, Edu. "Determining Best Regressional Model in Predicting Foetal Weight in Philips Clearview 350 Ultrasound Equipment" Afribary.com. Afribary.com, 11 Apr. 2021, https://afribary.com/works/determining-best-regressional-model-in-predicting-foetal-weight-in-philips-clearview-350-ultrasound-equipment . Accessed 08 May. 2021.
Frontiers, Edu. "Determining Best Regressional Model in Predicting Foetal Weight in Philips Clearview 350 Ultrasound Equipment". Afribary.com, Afribary.com, 11 Apr. 2021. Web. 08 May. 2021. < https://afribary.com/works/determining-best-regressional-model-in-predicting-foetal-weight-in-philips-clearview-350-ultrasound-equipment >.
Frontiers, Edu. "Determining Best Regressional Model in Predicting Foetal Weight in Philips Clearview 350 Ultrasound Equipment" Afribary.com (2021). Accessed May 08, 2021. https://afribary.com/works/determining-best-regressional-model-in-predicting-foetal-weight-in-philips-clearview-350-ultrasound-equipment