Detection of renal allograft rejection by computer

Abstract

A computer program incorporating an adaptation of a statistical method, the multiprocess Kalman filter, was used to detect changes in trends of plasma creatinine and urea concentrations. In 28 recipients of renal allografts a definite deterioration in renal function was identified retrospectively on 32 occasions by an experienced renal physician independently of the statistical analysis. The computer identified 31 of these 32 episodes using creatinine and urea results, and 29 using creatinine alone. Dysfunction was identified by the computer significantly earlier (p less than 0.05) than by the clinician and a median of one day earlier (p less than 0.02) than treatment was actually initiated. The computer identified dysfunction on 11 out of 1259 days when the clinician did not suspect rejection. These 11 episodes may have had a pathological importance, though no clinical diagnosis was made. This computer method is useful for immediate analysis of incoming results and for timing events either prospectively or retrospectively.