Beinema M J, van der Meer F J M, Brouwers J R B J, Rosendaal F R
Thrombosis Centre Deventer Hospital, Deventer, the Netherlands.
Department of Thrombosis and Haemostasis, Leiden University Medical Centre, Leiden, the Netherlands.
J Thromb Haemost. 2016 Mar;14(3):479-84. doi: 10.1111/jth.13240. Epub 2016 Feb 9.
ESSENTIALS: We developed a new algorithm to optimize vitamin K antagonist dose finding. Validation was by comparing actual dosing to algorithm predictions. Predicted and actual dosing of well performing centers were highly associated. The method is promising and should be tested in a randomized trial.
Oral vitamin K antagonists (VKAs) have a narrow therapeutic window and thus require frequent monitoring of its intensity by the international normalized ratio (INR). Improvement of VKA dosing defined as more time in therapeutic range (TTR) can reduce thrombotic disease and bleeding. Computerized decision support programs (CDSs) are used to optimize VKA dosing, but the effects are heterogeneous. CDSs significantly improve the proportion of time in the therapeutic INR range for initiation therapy but not the quality of anticoagulant management in an outpatient setting. One of the major problems of VKA dose finding is that the INR is a ratio and does not present linearity. We developed a new dose-finding algorithm, based on a novel bidirectional factor (BF). This BF is linear transformation of the nonlinear INR.
We compared the outcomes of the new algorithm, called BF-N, with dose finding performed at three highly ranked Dutch anticoagulation centers, using both acenocoumarol and phenprocoumon.
The outcomes of the BF-N algorithm showed a linear correlation with VKA doses of the three centers (y = 1.001x, r(2) 0.999 for acenocoumarol and y = 0.999x, r(2) 0.999 for phenprocoumon), with a standard deviation of 3.83%. The rate of automated dosage proposals increased to 100%.
The BF-N algorithm performs well in real-life settings and increases the rate of automated dosage proposals. The algorithm can be easily built into existing CDSs. Experienced staff remains necessary for complicated situations. The new algorithm needs to be evaluated in a prospective trial.
要点：我们开发了一种新算法来优化维生素K拮抗剂剂量的确定。通过将实际给药剂量与算法预测值进行比较来进行验证。表现良好的中心的预测给药剂量与实际给药剂量高度相关。该方法很有前景，应在随机试验中进行测试。
口服维生素K拮抗剂（VKA）的治疗窗较窄，因此需要通过国际标准化比值（INR）频繁监测其强度。将VKA给药优化定义为在治疗范围内（TTR）的时间更多，可以减少血栓性疾病和出血。计算机化决策支持程序（CDS）用于优化VKA给药，但效果各异。CDS可显著提高起始治疗时处于治疗性INR范围内的时间比例，但不能提高门诊抗凝管理的质量。VKA剂量确定的主要问题之一是INR是一个比值，不具有线性关系。我们基于一种新型双向因子（BF）开发了一种新的剂量确定算法。该BF是对非线性INR的线性变换。
我们将名为BF-N的新算法的结果与荷兰三个排名靠前的抗凝中心使用醋硝香豆素和苯丙香豆素进行的剂量确定结果进行了比较。
BF-N算法的结果与三个中心的VKA剂量呈线性相关（醋硝香豆素：y = 1.001x，r² = 0.999；苯丙香豆素：y = 0.999x，r² = 0.999），标准差为3.83%。自动给药建议率提高到了100%。
BF-N算法在实际应用中表现良好，并提高了自动给药建议率。该算法可以轻松地集成到现有的CDS中。对于复杂情况，仍需要经验丰富的工作人员。新算法需要在前瞻性试验中进行评估。
