Department of Clinical Pharmacy, Isala Clinics, Dr. van Heesweg 2, Zwolle, The Netherlands.
Department of Clinical Chemistry, Isala Clinics, Zwolle, The Netherlands.
Ther Adv Psychopharmacol. 2014 Apr;4(2):61-9. doi: 10.1177/2045125313511486.
Data about adherence of antidepressants during pregnancy are lacking. However, it is important to gain insight into adherence in this population to reduce perinatal risks for relapse of depression.
The objective of this study was to search for an inexpensive and easy method to implement daily for assessing medication adherence during pregnancy.
An observational study was conducted to measure adherence by comparing pill count, Beliefs about Medicine questionnaire (BMQ) and blood level monitoring against the standard, the Medication Event Monitoring System (MEMS). We used a logistic regression model to determine potential predictors for poor adherence (age, marital class, highest level of education, monthly net income, employment, smoking, alcohol use and type of antidepressant).
From January 2010 until January 2012, 41 women were included within the first trimester of pregnancy; data could be evaluated in 29 women. Using MEMS, 86% of the women took in more than 80% of all prescribed doses on time and could be classified as adherent. Pill counts showed good agreement with MEMS. We did not find predictors for poor adherence in our study population.
Adherence of antidepressants during pregnancy using MEMS is 86%. There was a good agreement between MEMS and pill counts. This method may serve as a good alternative that can be easily implemented into daily practice.
关于孕妇抗抑郁药物治疗依从性的数据尚缺乏。然而,深入了解该人群的依从性对于降低产后抑郁复发的风险非常重要。
本研究旨在寻找一种经济实惠且易于实施的方法,以评估孕妇在怀孕期间的药物依从性。
进行了一项观察性研究,通过比较药物计数、用药信念问卷(BMQ)和血药浓度监测与标准(用药事件监测系统(MEMS)),来衡量药物依从性。我们使用逻辑回归模型来确定依从性差的潜在预测因素(年龄、婚姻状况、最高教育水平、月净收入、就业、吸烟、饮酒和抗抑郁药类型)。
从 2010 年 1 月至 2012 年 1 月,41 名孕妇在妊娠早期入组,其中 29 名孕妇的数据可进行评估。使用 MEMS,86%的女性按时服用了超过 80%的规定剂量,可被归类为依从者。药物计数与 MEMS 具有良好的一致性。我们在研究人群中未发现依从性差的预测因素。
使用 MEMS 评估孕妇抗抑郁药物治疗的依从性为 86%。MEMS 和药物计数之间具有良好的一致性。这种方法可能是一种很好的替代方法,可以很容易地应用于日常实践中。