HEPARINS: INTERFERENCE IN ARGATROBAN MEASUREMENT
试验速览
- 阶段
- 不适用
- 状态
- 招募中
- 发起方
- 入组人数
- 70
- 试验地点
- 1
- 主要终点
- Pearson or Spearman correlation test
研究概览
简要总结
Unfractionated heparin (UFH) and low molecular weight heparins (LMWH) provide anticoagulation through their anti-Xa and anti-IIa activity. This anti-IIa activity can lead to an overestimation of argatroban's activity when switching to an anti-IIa anticoagulant such as argatroban. This situation can be critical because argatroban is generally administered following heparin therapy due to suspected heparin-induced thrombocytopenia. Therefore, there is both a significant thrombotic risk induced by the underlying condition and a hemorrhagic risk induced by the anticoagulation. For this reason, it is important to be able to accurately monitor the anti-IIa activity of argatroban. To date, the test used to determine the anti-IIa activity of argatroban at the Hematology Laboratory of the Strasbourg University Hospitals (HUS) is a modified thrombin time (with a calibration curve adapted for argatroban). When switching between several molecules with anti-IIa activity, this test does not allow for the differentiation of the anti-IIa activity attributable to each anticoagulant.
There are no data in the literature to determine whether heparins interfere with this test, and if so, its extent.
研究设计
- 研究类型
- Observational
- 观察模型
- Case Only
- 时间视角
- Prospective
入排标准
- 年龄范围
- 18 Years 至 —(Adult, Older Adult)
- 性别
- All
- 接受健康志愿者
- 否
入选标准
- 未提供
排除标准
- •Patient receiving an anticoagulant other than UFH or LMWH
- •Insufficient sample volume
结局指标
主要结局
Pearson or Spearman correlation test
时间窗: 1 hour after analysis
* A correlation test (Spearman or Pearson) will be performed to compare anti-Xa activity with anti-IIa activity to determine if there is a significant correlation that could lead to an overestimation of argatroban's anti-IIa activity during a heparin-argatroban switch. * Spearman correlation uses the rank of the data to measure monotonicity between ordinal or continuous variables. Pearson correlation, on the other hand, detects linear relationships between quantitative variables with data following a normal distribution.
次要结局
未报告次要终点
