Seddon 2012 [133] 599 UK P 1 month to 12 years EPLS, new APLS, Argall, BG, Luscombe None 1, 2 Low Findings: Mixed racial study population, no major racial differences found in performance of formulas.
On the contrary, performance of formulas is poor for high levels of GFR, whereas they tend to improve for lower values.
To assess the performance of formulas, the correlation coefficient (R), the mean absolute bias (eGFR − mGFR), the interquartile range of the bias (IQR), and 10% (P10) and 30% (P30) accuracies were calculated.
The performances of formulae were first assessed quantitatively using laboratory tests mainly within the CLASH database; and it was shown that the developed formulae are more accurate than the previous ones.
We also performed cleaning tests to determine if the cleaning performance of the formula was consistent with that of a strong neutral cleaner.
Bland-Altman plots, which plot the difference (delta) between two formulae against the average, were used to visually compare the relative performance of each formula.
Paw 2009 [111] 791 UK P 1 to 12 years EPLS None 1 High Findings: Very poor performance of EPLS formula.
Using a standardized Gardner Cleaning Test Method, the cleaning performance of the formula at 3.5% dilution was 67% soil removal.
Absolute estimated GFR by CKD-EPI is comparable to measured GFR, improving the performance of this formula in the assessment of individual kidney function, thus providing clinicians with an alternative to reference methods.
Such a change would be justifiable given the superior performance of the formula in estimating GFR. 10 Using the largest data set examined to date in this context, we demonstrate that the use of the CKD-EPI formula will bring about a substantial reduction in the number of people who will be classified as having CKD.
The predictive performance of the formula was evaluated by computing the mean relative prediction error (me%= N−1∑ j =1 N (pej) where N is the number of patients=15) as a measure of bias and the root mean squared relative prediction error (rmse%=[ N−1∑ j =1 N (pej)]1/2) as an assessment of precision.
