Dalla Man Chiara, Caumo Andrea, Cobelli Claudio
Department of Electronics and Informatics, University of Padova, Italy.
IEEE Trans Biomed Eng. 2002 May;49(5):419-29. doi: 10.1109/10.995680.
Recently, a new approach has been proposed to estimate insulin sensitivity (S(I)) from an oral glucose tolerance test or a meal using an "integral equation". Here, we improve on the "integral equation" by resorting to a "differential equation" approach. The classic glucose kinetics minimal model was used with the addition of a parametric model for the rate of appearance into plasma of oral glucose (Ra). Three behavioral models of Ra were proposed: piecewise-linear (P), spline (S) and dynamic (D). All three models performed satisfactorily allowing a precise estimation of S(I) and a plausible reconstruction of Ra. Mean S(I) estimates were virtually identical: S(I)P = 6.81 +/- 0.87 (SE); S(I)S = 6.53 +/- 0.80; and S(I)D = 6.62 +/- 0.79. S(I) strongly correlated with the integral-equation index (I) S(I)I: r = 0.99, p < 0.01 for models D and S, and r 0.97, p < 0.01 for P. Also, SI compared well with insulin sensitivity estimated from intravenous glucose tolerance test in the same subjects (r = 0.75, p < 0.01; r = 0.71, p < 0.01; r = 0.73, p < 0.01, respectively, for P, S, and D models versus s(I)IVGTT). Finally, the novel approach allows estimation of SI from a shorter test (120 min): model P yielded S(I)R = 7.16 +/- 1.0 (R for reduced) which correlated very well with S(I)P and S(I)I (respectively, r = 0.94, p < 0.01; r = 0.95, p < 0.01) and still satisfactorily with S(I)IVGTT (r = 0.77, p < 0.01).
最近,有人提出了一种新方法,可通过使用“积分方程”从口服葡萄糖耐量试验或一顿餐来估计胰岛素敏感性(S(I))。在此,我们借助“微分方程”方法对“积分方程”进行了改进。使用经典的葡萄糖动力学最小模型,并添加了口服葡萄糖进入血浆速率(Ra)的参数模型。提出了Ra的三种行为模型:分段线性(P)、样条(S)和动态(D)。所有这三种模型均表现良好,能够精确估计S(I)并合理重建Ra。S(I)的平均估计值几乎相同:S(I)P = 6.81 +/- 0.87(标准误);S(I)S = 6.53 +/- 0.80;S(I)D = 6.62 +/- 0.79。S(I)与积分方程指数(I)S(I)I高度相关:模型D和S的r = 0.99,p < 0.01,模型P的r = 0.97,p < 0.01。此外,在同一受试者中,S(I)与通过静脉葡萄糖耐量试验估计的胰岛素敏感性相比也表现良好(对于P、S和D模型与s(I)IVGTT相比,r分别为0.75,p < 0.01;r = 0.71,p < 0.01;r = 0.73,p < 0.01)。最后,这种新方法允许从更短的试验(120分钟)估计S(I):模型P得出S(I)R = 7.16 +/- 1.0(R表示简化),它与S(I)P和S(I)I相关性非常好(分别为r = 0.94,p < 0.01;r = 0.95,p < 0.01),与S(I)IVGTT的相关性也仍令人满意(r = 0.77,p < 0.01)。