Leslie J.C.Bluck and Sarah J.Jackson and Georgios Vlasakakis and Adrian Mander
A Bayesian Hierarchical 13COBT to Correct Estimates Associated with a Delayed Gastric Emptying
190 - 194
2010
4
5
International Journal of Biomedical and Biological Engineering
https://publications.waset.org/pdf/3809
https://publications.waset.org/vol/41
World Academy of Science, Engineering and Technology
The use of a Bayesian Hierarchical Model (BHM) to interpret breath measurements obtained during a 13C Octanoic Breath Test (13COBT) is demonstrated. The statistical analysis was implemented using WinBUGS, a commercially available computer package for Bayesian inference. A hierarchical setting was adopted where poorly defined parameters associated with a delayed Gastric Emptying (GE) were able to "borrow" strength from global distributions. This is proved to be a sufficient tool to correct model&39;s failures and data inconsistencies apparent in conventional analyses employing a Nonlinear least squares technique (NLS). Direct comparison of two parameters describing gastric emptying ng ( tlag lag phase, t1 2 half emptying time) revealed a strong correlation between the two methods. Despite our large dataset ( n 164 ), Bayesian modeling was fast and provided a successful fitting for all subjects. On the contrary, NLS failed to return acceptable estimates in cases where GE was delayed.
Open Science Index 41, 2010