Philip A Acelam

To determine and verify how anthropometric variables correlate to ureteric lengths and how well statistical models approximate the actual ureteric lengths. In this work, 129 charts of endourological patients (71 females and 58 males) were studied retrospectively. Data were gathered from various research centers from North and South America. Continuous data were studied using descriptive statistics. Anthropometric variables (age, body surface area, body weight, obesity, and stature) were utilized as predictors of ureteric lengths. Linear regressions and correlations were used for studying relationships between the predictors and the outcome variables (ureteric lengths); P-value was set at 0.05. To assess how well statistical models were capable of predicting the actual ureteric lengths, percentages (or ratios of matched to mismatched results) were employed. The results of the study show that anthropometric variables do not correlate well to ureteric lengths. Statistical models can partially estimate ureteric lengths. Out of the five anthropometric variables studied, three of them: body frame, stature, and weight, each with a P<0.0001, were significant. Two of the variables: age (R (2)=0.01; P=0.20) and obesity (R (2)=0.03; P=0.06), were found to be poor estimators of ureteric lengths. None of the predictors reached the expected (match:above:below) ratio of 1:0:0 to qualify as reliable predictors of ureteric lengths. There is not sufficient evidence to conclude that anthropometric variables can reliably predict ureteric lengths. These variables appear to lack adequate specificity as they failed to reach the expected (match:above:below) ratio of 1:0:0. Consequently, selections of ureteral stents continue to remain a challenge. However, height (R (2)=0.68) with the (match:above:below) ratio of 3:3:4 appears suited for use as estimator, but on the basis of decision rule. Additional research is recommended for stent improvements and ureteric length determinations.