McCartney M L
Biomedical Engineering Program Office, Research Triangle Institute, Research Triangle Park, NC 27709.
Am Ind Hyg Assoc J. 1990 Mar;51(3):169-77. doi: 10.1080/15298669091369493.
When mathematical model predictions disagree with the behavior of the physiological system modeled, blame is generally placed on the inadequacy of the model. It was shown using the Coburn-Forster-Kane (CFK) models of carboxyhemoglobin (COHb) formation as illustrations, that a sensitivity analysis of the model can provide estimates of the effects of data variability and inaccuracy on model predictions. Sensitivity functions were derived for each variable in the model, and families of them were plotted as functions of time with work level as a parameter. The sensitivity plots identify the variables which can contribute the most to disparities between model and system behavior and illustrate how the relative importance of the error in each variable changes with both time and work level. For example, with exposure to a constant concentration of carbon monoxide (CO) at a constant level of exercise, errors in blood volume determination, initial [COHb], and total hemoglobin concentration do not affect the calculated equilibrium value of blood [COHb]; neither inspired concentration of carbon monoxide nor endogenous production rate affect the rate at which equilibrium is achieved; and all other variables affect both the equilibrium value of blood [COHb] and the rate at which it is achieved. The sensitivity analysis provides a link between model output variability and input or data variability which can be used to assess the value of efforts to reduce data error and to estimate the overall uncertainty of model predictions.
当数学模型预测结果与所模拟的生理系统行为不一致时,通常会将原因归咎于模型的不充分性。以羧基血红蛋白(COHb)形成的科伯恩 - 福斯特 - 凯恩(CFK)模型为例表明,对模型进行敏感性分析可以估计数据变异性和不准确性对模型预测的影响。为模型中的每个变量推导了敏感性函数,并将它们的族作为时间的函数绘制,以工作水平作为参数。敏感性图确定了对模型与系统行为之间差异贡献最大的变量,并说明了每个变量中误差的相对重要性如何随时间和工作水平而变化。例如,在恒定运动水平下暴露于恒定浓度的一氧化碳(CO)时,血容量测定误差、初始[COHb]和总血红蛋白浓度不会影响计算出的血液[COHb]平衡值;一氧化碳的吸入浓度和内源性产生速率都不会影响达到平衡的速率;而所有其他变量既影响血液[COHb]的平衡值,也影响其达到平衡的速率。敏感性分析提供了模型输出变异性与输入或数据变异性之间的联系,可用于评估减少数据误差的努力的价值,并估计模型预测的总体不确定性。