Charles D Russell | PubMed Health

PubMed2003

A Bayesian 3-compartment model for 99mTc-MAG3 clearance.

UNLABELLED: Because recent reports have questioned the traditional 2-compartment model for calculating tracer clearance after a single intravenous injection, a 3-compartment model was evaluated in this study. METHODS: Bayesian statistics were used, which facilitated curve fitting by treating all subjects simultaneously. (99m)Tc-Mercaptoacetyltriglycine clearance data from 154 adults and 109 children were measured at several centers, typically 6-9 plasma samples spanning 5-90 min, and fitted by 2- and 3-compartment Bayesian models. RESULTS: Clearance estimates were found to be systematically lower for the 3-compartment model than for the 2-compartment model. A single-sample procedure based on the 3-compartment model was found to eliminate most of the known discrepancy between formulas based on single-injection and continuous-infusion reference methods. CONCLUSION: A 3-compartment model led to lower and probably more accurate clearance estimates than the conventional 2-compartment model. A new single-sample method is presented, based on the 3-compartment model as reference standard.

Adolescent↗

PubMed2002

A Bayesian regression model for plasma clearance.

UNLABELLED: Nonlinear Bayesian regression permits curve fitting to a group of subjects simultaneously rather than individually. We evaluated this approach for interpreting plasma clearance curves with the goal of reducing curve-fitting failures and dealing objectively with problem datasets that may arise in clinical settings. METHODS: (99m)Tc-Diethylenetriaminepentaacetic acid plasma clearance curves from 79 subjects were analyzed. The data typically comprised 7-9 samples obtained from 5-10 to 180-240 min after injection. A 2-compartment model was fitted by Bayesian regression to yield compartmental hyperparameters V1, L21, and L12 corresponding to the volume of the compartment into which tracer was injected and the transfer rates from compartment 1 to compartment 2 and from compartment 2 to compartment 1, respectively. This also yielded a clearance estimate for each subject. RESULTS: Estimated hyperparameters were V1 = 8.9 L, L21 = 0.026 min(-1), and L12 = 0.040 min(-1). Conventional methods led to fitting failures in 2 of the 79 subjects but there were no failures with the Bayesian method. The hyperparameters were used to calculate the glomerular filtration rate for each subject from a single plasma sample with a root-mean-square error of 7.3 mL/min, which was not significantly different from the widely used Christensen-Groth formula. CONCLUSION: Fewer fitting failures were encountered than with conventional methods, offering an objective means of dealing with problem data. This conceptually simple model can be used directly to calculate clearance from a single plasma sample. It requires only the 3 parameters described above, whereas the Christensen-Groth method requires 6 parameters.

Adult↗