Department of Pharmacy Systems, Outcomes, and Policy (PSOP), College of Pharmacy, University of Illinois at Chicago, Chicago, Illinois, United States of America.
Department of Pharmacy Practice, College of Pharmacy, University of Illinois at Chicago, Chicago, Illinois, United States of America.
PLoS One. 2020 Oct 15;15(10):e0240379. doi: 10.1371/journal.pone.0240379. eCollection 2020.
Previous studies have suggested an increased risk of cardiac events with azithromycin, but the predictors of such events are unknown. We sought to develop and validate two prediction models to identify such predictors. We used data from Truven Marketscan Database (01/2009 to 06/2015). Using a split-sample approach, we developed two prediction models, which included baseline demographics, clinical conditions (Model 1), concurrent use of any drug (Model 1) and therapeutic class (Model 2) with a risk of QT-prolongation (CQT-Rx). Patients enrolled in a health plan for 365 days before and five days after dispensing of azithromycin (episodes). Cardiac events included syncope, palpitations, ventricular arrhythmias, cardiac arrest as a primary diagnosis for hospitalization including death. For each model, a backward elimination of predictors using logistic regression was applied to identify predictors in 100 random samples of the training cohort. Predictors prevalent in >50% of the models were included in the final model. A score for the Assessment of Cardiac Risk with Azithromycin (ACRA) was generated using the training cohort then tested in the validation cohort. A cohort of 20,134,659 episodes with 0.03% cardiac events were included. Over 60% included females with mean age of 40.1±21.3 years. Age, sex, history of syncope, cardiac dysrhythmias, non-specific chest pain, and presence of a CQT-Rx were included as predictors for Model-1 (c-statistic = 0.68). For Model-2 (c-statistic = 0.64), predictors included age, sex, anti-arrhythmic agents, anti-emetics, antidepressants, loop diuretics, and ACE inhibitors. ACRA score is available online (bit.ly/ACRA_2020). The ACRA score may help identify patients who are at higher risk of cardiac events following treatment with azithromycin. Providers should assess the risk-benefit of using azithromycin and consider alternative antibiotics among high-risk patients.
先前的研究表明，使用阿奇霉素会增加心脏事件的风险，但此类事件的预测因素尚不清楚。我们试图开发和验证两个预测模型来确定这些预测因素。我们使用了 Truven Marketscan 数据库的数据（2009 年 1 月至 2015 年 6 月）。我们采用分割样本的方法，开发了两个预测模型，其中包括基线人口统计学特征、临床情况（模型 1）、同时使用任何具有 QT 延长风险的药物（模型 1）和治疗类别（模型 2）。纳入计划中患者在开出处方前 365 天和开出处方后 5 天的健康状况（事件）。心脏事件包括晕厥、心悸、室性心律失常、心脏骤停，作为住院的主要诊断，包括死亡。对于每个模型，我们使用逻辑回归向后消除预测因素，以确定 100 个训练队列随机样本中的预测因素。在超过 50%的模型中普遍存在的预测因素被纳入最终模型。使用训练队列生成阿奇霉素心脏风险评估（ACRA）评分，然后在验证队列中进行测试。共纳入 20134659 例事件，其中 0.03%发生心脏事件。超过 60%的患者为女性，平均年龄为 40.1±21.3 岁。年龄、性别、晕厥史、心律失常、非特异性胸痛和存在 QT 延长风险药物被纳入模型 1（c 统计量=0.68）的预测因素。对于模型 2（c 统计量=0.64），预测因素包括年龄、性别、抗心律失常药物、止吐药、抗抑郁药、噻嗪类利尿剂和 ACE 抑制剂。ACRA 评分可在线获取（bit.ly/ACRA_2020）。ACRA 评分可能有助于识别接受阿奇霉素治疗后心脏事件风险较高的患者。医生应评估使用阿奇霉素的风险-效益，并在高风险患者中考虑替代抗生素。
