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咪达唑仑诱导终末期成年患者镇静的群体药效动力学模型。

Population pharmacodynamic modelling of midazolam induced sedation in terminally ill adult patients.

机构信息

Department of Hospital Pharmacy, Erasmus Medical Centre, Rotterdam, The Netherlands.

Palliative Care Centre, Laurens Cadenza, Rotterdam, The Netherlands.

出版信息

Br J Clin Pharmacol. 2018 Feb;84(2):320-330. doi: 10.1111/bcp.13442. Epub 2017 Oct 26.

Abstract

AIMS

Midazolam is the drug of choice for palliative sedation and is titrated to achieve the desired level of sedation. A previous pharmacokinetic (PK) study showed that variability between patients could be partly explained by renal function and inflammatory status. The goal of this study was to combine this PK information with pharmacodynamic (PD) data, to evaluate the variability in response to midazolam and to find clinically relevant covariates that may predict PD response.

METHOD

A population PD analysis using nonlinear mixed effect models was performed with data from 43 terminally ill patients. PK profiles were predicted by a previously described PK model and depth of sedation was measured using the Ramsay sedation score. Patient and disease characteristics were evaluated as possible covariates. The final model was evaluated using a visual predictive check.

RESULTS

The effect of midazolam on the sedation level was best described by a differential odds model including a baseline probability, Emax model and interindividual variability on the overall effect. The EC50 value was 68.7 μg l for a Ramsay score of 3-5 and 117.1 μg l for a Ramsay score of 6. Comedication with haloperidol was the only significant covariate. The visual predictive check of the final model showed good model predictability.

CONCLUSION

We were able to describe the clinical response to midazolam accurately. As expected, there was large variability in response to midazolam. The use of haloperidol was associated with a lower probability of sedation. This may be a result of confounding by indication, as haloperidol was used to treat delirium, and deliria has been linked to a more difficult sedation procedure.

摘要

目的

咪达唑仑是姑息性镇静治疗的首选药物,并通过滴定来达到所需的镇静水平。先前的药代动力学(PK)研究表明,患者之间的变异性部分可以通过肾功能和炎症状态来解释。本研究的目的是将该 PK 信息与药效学(PD)数据相结合,评估对咪达唑仑的反应变异性,并找到可能预测 PD 反应的临床相关协变量。

方法

对 43 名终末期患者的数据进行了基于非线性混合效应模型的群体 PD 分析。PK 曲线由先前描述的 PK 模型预测,镇静深度使用 Ramsay 镇静评分进行测量。评估患者和疾病特征作为可能的协变量。使用视觉预测检查评估最终模型。

结果

咪达唑仑对镇静水平的影响最好用包括基线概率、Emax 模型和总体效应的个体间变异性的差异优势模型来描述。Ramsay 评分为 3-5 时 EC50 值为 68.7μg/l,Ramsay 评分为 6 时 EC50 值为 117.1μg/l。与氟哌啶醇合用是唯一有显著意义的协变量。最终模型的视觉预测检查显示出良好的模型预测能力。

结论

我们能够准确描述对咪达唑仑的临床反应。正如预期的那样,对咪达唑仑的反应存在很大的变异性。氟哌啶醇的使用与镇静的可能性降低相关。这可能是由于指示性混杂,因为氟哌啶醇被用于治疗谵妄,而谵妄与更困难的镇静过程有关。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/bd50/5777431/9ea4b18c948e/BCP-84-320-g001.jpg

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