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Improved Predictions of Total Kidney Volume Growth Rate in ADPKD Using Two-parameter Least Squares Fitting

Overview
Journal Sci Rep
Specialty Science
Date 2024 Jun 14
PMID 38877066
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Abstract

Mayo Imaging Classification (MIC) for predicting future kidney growth in autosomal dominant polycystic kidney disease (ADPKD) patients is calculated from a single MRI/CT scan assuming exponential kidney volume growth and height-adjusted total kidney volume at birth to be 150 mL/m. However, when multiple scans are available, how this information should be combined to improve prediction accuracy is unclear. Herein, we studied ADPKD subjects ( ) with 8+ years imaging follow-up (mean = 11 years) to establish ground truth kidney growth trajectory. MIC annual kidney growth rate predictions were compared to ground truth as well as 1- and 2-parameter least squares fitting. The annualized mean absolute error in MIC for predicting total kidney volume growth rate was compared to ( ) for a 2-parameter fit to the same exponential growth curve used for MIC when 4 measurements were available or ( ) with 3 measurements averaging together with MIC. On univariate analysis, male sex ( ) and PKD2 mutation ( ) were associated with poorer MIC performance. In ADPKD patients with 3 or more CT/MRI scans, 2-parameter least squares fitting predicted kidney volume growth rate better than MIC, especially in males and with PKD2 mutations where MIC was less accurate.

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