Abstract
Introduction: Congenital anomalies of the kidney and urinary tract (CAKUT) represent 20– 30% of all antenatally diagnosed fetal congenital anomalies in western countries. In Saudi Arabia they constitute about 40% of all anomalies. Antenatal ultrasound is considered the gold standard tool to detect fetal anomalies during the antenatal period. However, it is highly operator dependent and may be affected by other variables such as machine quality and patient characteristics. The aim of this study is to evaluate the agreement of the antenatal and postnatal ultrasound diagnoses of CAKUT at King Abdulaziz Medical City-Western Region (KAMC-WR). Objectives: To compare the antenatal detection of CAKUT using ultrasound findings with postnatal outcomes. Materials and methods: This study was a retrospective chart review, conducted at the Maternal Fetal Medicine Unit at KAMC-WR, reviewing antenatally detected CAKUT between 2009 and 2014. The data were collected by utilizing multiple congenital anomalies databases. A data sheet was completed and divided into four sections: maternal data, antenatal data, delivery and postnatal data. Results: There were 139 patients with renal anomalies, with 16.5% perinatal deaths, 12.9% loss of follow-up and 1.4% missing data cases. Abnormal amniotic fluid was detected in 32%, as well as bilateral anomalies in 41% and it was most commonly seen in male fetuses. Forty-one per cent of the fetuses were the product of consanguineous marriages and 82.8% of cases corresponded to the antenatal diagnosis. The most common anomaly found antenatally and confirmed postnatally was hydronephrosis (60%) followed by multicystic dysplastic kidney disease (12%). Conclusions: The rate of discrepancy for detection of CAKUT between antenatal and postnatal ultrasound was different from that reported in recent studies. Prospective studies are recommended in this field for further understanding. However, the consanguinity rate in our population was significantly higher than the international reports, 41% versus 10%, respectively. Acknowledgements: Dr Basim Alsaywid, Mr Sharif Hala, Dr Fayez Nasrallah and Dr Ghassan Sukkar for supervising this project.
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