Department of Family Medicine, Faculty of Medicine, McGill University, 5858 Chemin de la Côte-des-Neiges, suite 300, H3S 1Z1, Montréal, Qc, Canada.
Department of Neurology & Neurosurgery, McGill University, 3801 Rue Université, H3A 2B4, Montréal, Qc, Canada; Department of Epidemiology and Biostatistics, McGill University, Montréal, Qc, Canada; Centre for Clinical Epidemiology, Lady Davis Institute for Medical Research, Jewish General Hospital, Montréal, Qc, Canada.
J Affect Disord. 2021 Dec 1;295:1310-1318. doi: 10.1016/j.jad.2021.08.018. Epub 2021 Aug 12.
Patients with depression and comorbid obesity may be more prone to weight modulating and cardiovascular side effects of selected antidepressants (AD). It is important to ascertain whether these AD prescriptions differ by patient weight status.
Canadian Primary Care Sentinel Surveillance Network (CPCSSN) electronic medical records were used. Participants were adults with depression prescribed an AD in 2000-2016, with weight categories established before the first prescription. Logistic regression and mixed effects models were applied to examine associations between obesity and AD prescribing, adjusted for sex, age, and comorbidities. Machine learning algorithm random forest (RF) was used to evaluate the importance of weight in predicting prescribing patterns.
Of 26,571 participants, 72.4% were women, mean age was 38.9 years (standard deviation (SD)=14.2) and mean BMI 27.0 kg/m (SD = 6.5); 9.5% had ≥ 1 comorbidity. Patients with obesity, compared to normal weight patients, were more likely to receive bupropion (adjusted odds ratio (aOR) 1.24, 95%CI: 1.09,1.42), fluoxetine (aOR 1.14, 95%CI: 0.97,1.34), and amitriptyline (aOR 1.13, 95%CI: 0.93,1.36), and less likely to receive mirtazapine (aOR 0.55, 95%CI: 0.44,0.68) and escitalopram (aOR 0.88, 95%CI: 0.80, 0.97). RF analysis showed that weight was among the most important predictors of prescribing patterns, equivalent to age and more important than sex.
AD prescribing patterns for patients with obesity appear to be different for selected AD types, including AD known for their weight-modulating and cardiovascular side effects. Longitudinal studies are needed to examine whether these prescribing patterns are associated with significant health outcomes.
患有抑郁症和合并肥胖症的患者可能更容易出现所选抗抑郁药(AD)的体重调节和心血管副作用。确定这些 AD 处方是否因患者体重状况而异很重要。
使用加拿大初级保健监测网络(CPCSSN)电子病历。参与者为 2000 年至 2016 年期间被处方 AD 的患有抑郁症的成年人,体重类别在首次处方前建立。应用逻辑回归和混合效应模型,在校正性别、年龄和合并症后,研究肥胖症与 AD 处方之间的关联。机器学习算法随机森林(RF)用于评估体重在预测处方模式中的重要性。
在 26571 名参与者中,72.4%为女性,平均年龄为 38.9 岁(标准差(SD)=14.2),平均 BMI 为 27.0kg/m(SD=6.5);9.5%有≥1 种合并症。与正常体重患者相比,肥胖患者更有可能接受安非他酮(调整后的优势比(aOR)1.24,95%CI:1.09,1.42)、氟西汀(aOR 1.14,95%CI:0.97,1.34)和阿米替林(aOR 1.13,95%CI:0.93,1.36),而不太可能接受米氮平(aOR 0.55,95%CI:0.44,0.68)和依地普仑(aOR 0.88,95%CI:0.80,0.97)。RF 分析表明,体重是处方模式的最重要预测因素之一,与年龄相当,比性别更重要。
对于某些特定类型的 AD,肥胖患者的 AD 处方模式似乎有所不同,包括具有体重调节和心血管副作用的 AD。需要进行纵向研究,以检查这些处方模式是否与重大健康结果相关。