Modelling peritonitis rates and associated risk factors for individuals on continuous ambulatory peritoneal dialysis.

Abstract

A mixed effects Poisson regression model is proposed for analysing potential risk factors associated with peritonitis, a bacterial infection of the peritoneum which is common among individuals on continuous ambulatory peritoneal dialysis (CAPD). The model incorporates a set of fixed effects corresponding to concomitant information collected across individuals as well as a random effect due to individuals. The method of maximum likelihood is used to estimate the unknown parameters. When applied to clinical data obtained on 81 CAPD patients from four centres, the mixed effects model demonstrated a much better fit than the corresponding fixed effects Poisson regression model.