Computerized curve fitting in the analysis of hydrogen gas clearance curves

Abstract

Hydrogen gas clearance curves obtained from the rat gastric corpus were digitized into a computer and then analyzed by three methods: 1) linear regression of log-transformed data, 2) direct curve fitting with a modified Gauss-Newton nonlinear regression algorithm, and 3) Zierler's height-over-area algorithm. For linear regression of log-transformed data, if the initial base-line estimate was inaccurate or normal amounts of experimental noise were present, the log-transformed data was skewed, leading to deviation of the regression line and incorrect estimation of blood flow. By utilization of the direct-fit routine, the initial estimate of the parameters or experimental noise had little influence on the blood flow determination because of iterative improvement of the parameters. In a study of isoproterenol-stimulated gastric blood flow, Zierler's algorithm underestimated the blood flow estimate. We conclude that analysis of hydrogen gas clearance curves by linear regression of log-transformed data or by Zierler's algorithm may potentially introduce errors in blood flow estimates that may be avoided by analysis with a direct-fitting, nonlinear regression algorithm.