CORRELATION ANALYSIS OF FOETAL KIDNEY DIMENSIONS IN THE THIRD TRIMESTER UNRAVELING DEVELOPMENTAL PATTERNS ACROSS GESTATIONAL AGES

Abstract

Introduction: Timely implantation, fertilisation, and ovulation all depend on accurate gestational age (GA) calculation, yet there are ambiguities in these processes that make this difficult to achieve. There are issues with traditional approaches, particularly during the third trimester, which has led to research into other biometric criteria. One potential measure that shows consistent increase during gestation and connection with maternal age is foetal kidney length (FKL).

Objective: The purpose of this study is to look into the relationship between mean FKL among various age groups and GA, expressed in weeks. The mean FKL is also contrasted with other biometric measurements, such as femur length, head circumference, belly circumference, and biparietal diameter.

Methods and Materials: Using standardised proforma and ultrasound measures, 120 pregnant women in their third trimester participated in the study. Comprehensive data was gathered. Regression coefficients and Pearson's correlation are used to examine relationships between renal length, other biometric data, and GA.

Result: Maternal age-based categorization indicates that women in the 20–29 age range are disproportionately represented. The average kidney length based on gestational age, the distribution of maternal ages, and connections with different biometric indicators are all shown in detail in the study's tables and figures. Mean kidney length is positively correlated with head circumference, femur length, biparietal diameter, GA by last menstrual period, and abdominal circumference.

Conclusion: mean kidney length outperforms individual kidney measurements as a reliable and accurate method for estimating GA. The study shows its association with recognised biometric markers and emphasises its reliability, especially in the third trimester. Mean kidney length might be incorporated into routine exams to improve the accuracy of GA estimates, which would allow for better prenatal care and intervention planning.