Berger M P, Gelfand R A, Miller P L
Medical Informatics Program, Yale University School of Medicine, New Haven, Connecticut 06510.
Comput Biomed Res. 1990 Aug;23(4):346-57. doi: 10.1016/0010-4809(90)90026-9.
Self-monitoring of capillary blood glucose is used by most patients with insulin-dependent diabetes mellitus as a means of assessing metabolic control. Therapeutic interventions are based on retrospective analysis of glycemic response to various factors, with insulin and diet playing the key roles. We describe a computer system being developed for intelligent automated analysis and interpretation of data relevant to glycemic control. CADMO (Computer-Assisted Diabetes Monitor) is intended to assist health care professionals with the management of patients with insulin-dependent diabetes. It takes as input glucose values and insulin doses collected via a memory meter by the patient over a period of several weeks. Rule-based logic, statistical methods, and a physiologic model of insulin pharmacokinetics and glucose dynamics are used to help detect meaningful patterns and trends in glucose and insulin data and to suggest approaches for optimizing insulin regimens.
大多数胰岛素依赖型糖尿病患者通过自我监测毛细血管血糖来评估代谢控制情况。治疗干预措施基于对各种因素的血糖反应的回顾性分析，其中胰岛素和饮食起着关键作用。我们描述了一个正在开发的计算机系统，用于对与血糖控制相关的数据进行智能自动分析和解释。CADMO（计算机辅助糖尿病监测仪）旨在协助医护人员管理胰岛素依赖型糖尿病患者。它将患者在几周时间内通过记忆仪收集的血糖值和胰岛素剂量作为输入。基于规则的逻辑、统计方法以及胰岛素药代动力学和葡萄糖动力学的生理模型，用于帮助检测血糖和胰岛素数据中有意义的模式和趋势，并提出优化胰岛素治疗方案的方法。
