Towards automated identification of changes in laboratory measurement of renal function: implications for longitudinal research and observing trends in glomerular filtration rate (GFR)

Norman Poh; Andrew McGovern; Simon de Lusignan

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arXiv · 1409.1542

Towards automated identification of changes in laboratory measurement of renal function: implications for longitudinal research and observing trends in glomerular filtration rate (GFR)

Norman Poh·Andrew McGovern·Simon de Lusignan

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Abstract

Introduction: Kidney function is reported using estimates of glomerular filtration rate (eGFR). However, eGFR values are recorded without reference to the creatinine (SCr) assays used to derive them, and newer assays were introduced at different time points across laboratories in UK. These changes may cause systematic bias in eGFR reported in routinely collected data; even though laboratory reported eGFR values have a correction factor applied. Design: An algorithm to detect changes in SCr which affect eGFR calculation method by comparing the mapping of SCr values on to eGFR values across a time-series of paired eGFR and SCr measurements. Setting: Routinely collected primary care data from 20,000 people with the richest renal function data from the Quality Improvement in Chronic Kidney Disease (QICKD) trial. Results: The algorithm identified a change in eGFR calculation method in 80 (63%) of the 127 included practices. This change was identified in 4,736 (23.7%) patient time series analysed. This change in calibration method was found to cause a significant step change in reported eGFR values producing a systematic bias. eGFR values could not be recalibrated by applying the Modification of Diet in Renal Disease (MDRD) equation to the laboratory reported SCr values. Conclusions: This algorithm can identify laboratory changes in eGFR calculation methods and changes in SCr assay. Failure to account for these changes may misconstrue renal function changes over time. Researchers using routine eGFR data should account for these effects.

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Norman Poh, Andrew McGovern, Simon de Lusignan. 2014-09-03. Towards automated identification of changes in laboratory measurement of renal function: implications for longitudinal research and observing trends in glomerular filtration rate (GFR). https://arxiv.org/abs/1409.1542

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