Department of Neuropsychiatry, Keio University School of Medicine, Tokyo, Japan.
Geriatric Psychiatry Division, Centre for Addiction and Mental Health, Toronto, ON, Canada.
Pharmacopsychiatry. 2018 May;51(3):82-88. doi: 10.1055/s-0043-116855. Epub 2017 Aug 2.
Therapeutic drug monitoring is necessary for lithium, but clinical application of several prediction strategies is still limited because of insufficient predictive accuracy. We herein proposed a suitable model, using creatinine clearance (CLcr)-based lithium clearance (Li-CL).
Patients receiving lithium provided the following information: serum lithium and creatinine concentrations, time of blood draw, dosing regimen, concomitant medications, and demographics. Li-CL was calculated as a daily dose per trough concentration for each subject, and the mean of Li-CL/CLcr was used to estimate Li-CL for another 30 subjects. Serum lithium concentrations at the time of sampling were estimated by 1-compartment model with Li-CL, fixed distribution volume (0.79 L/kg), and absorption rate (1.5/hour) in the 30 subjects.
One hundred thirty-one samples from 82 subjects (44 men; mean±standard deviation age: 51.4±16.0 years; body weight: 64.6±13.8 kg; serum creatinine: 0.78±0.20 mg/dL; dose of lithium: 680.2±289.1 mg/day) were used to develop the pharmacokinetic model. The mean±standard deviation (95% confidence interval) of absolute error was 0.13±0.09 (0.10-0.16) mEq/L.
Serum concentrations of lithium can be predicted from oral dosage with high precision, using our prediction model.
锂的治疗药物监测是必要的，但由于预测准确性不足，几种预测策略的临床应用仍然有限。我们在此提出了一种合适的模型，使用基于肌酐清除率（CLcr）的锂清除率（Li-CL）。
接受锂治疗的患者提供了以下信息：血清锂和肌酐浓度、采血时间、给药方案、伴随药物和人口统计学数据。Li-CL 被计算为每个受试者的每个谷浓度的每日剂量，并且 Li-CL/CLcr 的平均值用于估计另外 30 名受试者的 Li-CL。在 30 名受试者中，通过 Li-CL、固定分布体积（0.79 L/kg）和吸收率（1.5/小时）的 1 室模型估计采样时的血清锂浓度。
从 82 名受试者（44 名男性；平均±标准差年龄：51.4±16.0 岁；体重：64.6±13.8 kg；血清肌酐：0.78±0.20 mg/dL；锂剂量：680.2±289.1 mg/天）的 131 个样本用于开发药代动力学模型。绝对误差的平均值±标准差（95%置信区间）为 0.13±0.09（0.10-0.16）mEq/L。
使用我们的预测模型，从口服剂量可以高精度预测锂的血清浓度。
