Greater Accuracy of the eGFR Formula by Using a Power Function of Patient Height over Its Unidimensional Value in Pediatric Kidney Transplantation

在儿科肾移植中,使用患者身高的幂函数而非其一维值来提高eGFR公式的准确性

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Abstract

Background: The updated Schwartz and CKiDU25 bedside (SCr-based) formulae for the estimated glomerular filtration rate (eGFR) in children are defined by a constant term (with the latter formula dependent upon age and sex) multiplied by the ratio of patient's height (m) to SCr (mg/dL). However, the Schwartz formula can severely underestimate the measured GFR (mGFR) at higher mGFR levels. Methods: For a single-center cohort of 92 pediatric kidney transplant recipients, we statistically determined if the log{eGFR} at 1 mo and 6 mo post-transplant might further depend upon patient demographics or height, indicating the inadequacy of these formulae for properly predicting the mGFR. We also determined how the log{SCr} at 1 mo and 6 mo post-transplant might depend upon patient demographics and height, helping to corroborate any arrived-at improved functional form for the eGFR. Results: Overall, our cohort received good-quality donor kidneys; however, both eGFR formulae calculated that the percentage of recipients with an eGFR < 60 mL/min/1.73 m(2) at 1 mo and 6 mo post-transplant was 26-28%. Furthermore, neither the updated Schwartz nor the CKiDU25 bedside formulae adequately controlled for the influence of patient height on SCr; in fact, the patient height squared was superior to its unidimensional value at accounting for the sharp increase in SCr that normally occurs as children grow from infancy to young adulthood (p < 0.000001 at mo1, p = 0.000003 at mo6 for the updated Schwartz bedside formula; p = 0.0009 at mo1, p = 0.005 at mo6 for the CKiDU25 bedside formula). The log{SCr} was also best fitted by a linear regression model that controlled for the log{patient height squared} (p < 0.000001 at both mo1 and mo6). Conclusions: A statistically more accurate eGFR formula should be based on using a power function (power > 1) for patient height rather than its unidimensional value.

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