Table 3.
Linear regression analyses of total absorbed dose on potential predictor.
| Predictor | Unadjusted regression coefficient (95% CI) p-value | Correlation | Adjusted regression coefficient for parsimonious model (95% CI) p-value | Partial correlation |
|---|---|---|---|---|
| Age (years) | 6.03 (2.14, 9.92) p = 0.003 | 0.34 | 3.64 (1.79, 5.49) p < 0.001 | 0.43 |
| Procedure time (min) | 9.30 (3.98, 14.62) p < 0.001 | 0.38 | 8.47 (5.96, 10.97) p < 0.001 | 0.63 |
| Weight (kgs) | 9.56 (7.90, 11.22) p < 0.001 | 0.80 | 11.83 (9.77, 13.90) p < 0.001 | 0.81 |
| BMI (Kgs/m2) | 43.62 (34.67, 52.57) p < 0.001 | 0.75 | A | |
| Height (m) | 829.46 (508.06, 1150.87) p < 0.001 | 0.52 | −543.24 (−814.5, −271.97) p < 0.001 | −0.43 |
| Sex (M relative to F) | 149.15 (87.98, 210.32) p < 0.001 | NA | B |
Regression coefficients represent mean change in total dose (cGy cm2) per unit increase in predictor.
NA – sex is a nominal variable so Pearson's correlation not presented.
A – BMI excluded because of collinearity with weight and height.
B – Effect of sex explained by height, weight and other variables when added to the model (p = 0.87).