Trimble I M, West M, Knapp M S, Pownall R, Smith A F
Br Med J (Clin Res Ed). 1983 May 28;286(6379):1695-9. doi: 10.1136/bmj.286.6379.1695.
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.
一个采用了统计方法（多进程卡尔曼滤波器）改进版的计算机程序，被用于检测血浆肌酐和尿素浓度趋势的变化。在28例同种异体肾移植受者中，一位经验丰富的肾脏内科医生在不依赖统计分析的情况下，回顾性地确定了32次肾功能的明确恶化情况。计算机利用肌酐和尿素结果识别出了这32次事件中的31次，仅利用肌酐结果识别出了29次。计算机识别出功能障碍的时间比临床医生显著更早（p<0.05），且比实际开始治疗的时间中位数早一天（p<0.02）。在临床医生未怀疑排斥反应的1259天中，计算机识别出了11天存在功能障碍。尽管未做出临床诊断，但这11次事件可能具有病理学意义。这种计算机方法对于即时分析传入结果以及前瞻性或回顾性地确定事件时间很有用。
