Professor of Cardiology, Fellowship of Interventional Cardiology, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran.
Assistant professor of Cardiology, Tehran Heart Center, Tehran University of Medical Sciences, Tehran, Iran.
BMC Complement Med Ther. 2023 Jan 19;23(1):16. doi: 10.1186/s12906-023-03833-z.
Considerable number of people still use opium worldwide and many believe in opium's health benefits. However, several studies proved the detrimental effects of opium on the body, especially the cardiovascular system. Herein, we aimed to provide the first evidence regarding the effects of opium use on one-year major adverse cardiovascular events (MACE) in the patients with ST-elevation MI (STEMI) who underwent primary PCI.
We performed a propensity score matching of 2:1 (controls: opium users) that yielded 518 opium users and 1036 controls. Then, we performed conventional statistical and machine learning analyses on these matched cohorts. Regarding the conventional analysis, we performed multivariate analysis for hazard ratio (HR) of different variables and MACE and plotted Kaplan Meier curves. In the machine learning section, we used two tree-based ensemble algorithms, Survival Random Forest and XGboost for survival analysis. Variable importance (VIMP), tree minimal depth, and variable hunting were used to identify the importance of opium among other variables.
Opium users experienced more one-year MACE than their counterparts, although it did not reach statistical significance (Opium: 72/518 (13.9%), Control: 112/1036 (10.8%), HR: 1.27 (95% CI: 0.94-1.71), adjusted p-value = 0.136). Survival random forest algorithm ranked opium use as 13th, 13th, and 12th among 26 variables, in variable importance, minimal depth, and variable hunting, respectively. XGboost revealed opium use as the 12th important variable. Partial dependence plot demonstrated that opium users had more one-year MACE compared to non-opium-users.
Opium had no protective effects on one-year MACE after primary PCI on patients with STEMI. Machine learning and one-year MACE analysis revealed some evidence of its possible detrimental effects, although the evidence was not strong and significant. As we observed no strong evidence on protective or detrimental effects of opium, future STEMI guidelines may provide similar strategies for opium and non-opium users, pending the results of forthcoming studies. Governments should increase the public awareness regarding the evidence for non-beneficial or detrimental effects of opium on various diseases, including the outcomes of primary PCI, to dissuade many users from relying on false beliefs about opium's benefits to continue its consumption.
全世界仍有大量的人在使用鸦片,许多人相信鸦片对健康有益。然而,多项研究证明了鸦片对身体的有害影响,尤其是对心血管系统。在此,我们旨在提供关于使用鸦片对接受直接经皮冠状动脉介入治疗(PCI)的 ST 段抬高型心肌梗死(STEMI)患者一年内主要不良心血管事件(MACE)的影响的第一个证据。
我们进行了倾向评分匹配 2:1(对照组:鸦片使用者),得出 518 名鸦片使用者和 1036 名对照组。然后,我们对这些匹配队列进行了常规统计和机器学习分析。关于常规分析,我们对不同变量和 MACE 的风险比(HR)进行了多变量分析,并绘制了 Kaplan-Meier 曲线。在机器学习部分,我们使用了两种基于树的集成算法,生存随机森林和 XGBoost 进行生存分析。使用变量重要性(VIMP)、树最小深度和变量搜索来确定鸦片与其他变量之间的重要性。
尽管没有达到统计学意义(鸦片:72/518(13.9%),对照组:112/1036(10.8%),HR:1.27(95%CI:0.94-1.71),调整后的 p 值=0.136),但与对照组相比,鸦片使用者在一年内经历了更多的 MACE。生存随机森林算法在 26 个变量中分别将鸦片使用排名为 13、13 和 12,在变量重要性、最小深度和变量搜索中。XGBoost 显示鸦片使用是第 12 个重要变量。部分依赖图表明,与非鸦片使用者相比,鸦片使用者在一年内发生 MACE 的可能性更大。
在 STEMI 患者接受直接 PCI 后,鸦片对一年内 MACE 没有保护作用。机器学习和一年内 MACE 分析显示了其可能产生有害影响的一些证据,尽管证据不强且不显著。由于我们没有观察到关于鸦片对保护或有害影响的强有力证据,因此未来的 STEMI 指南可能会为鸦片和非鸦片使用者提供类似的策略,等待即将到来的研究结果。政府应提高公众对鸦片在各种疾病(包括直接 PCI 结果)方面没有益处或有害影响的证据的认识,以阻止许多人依赖于关于鸦片益处的错误信念继续使用。