Causal Inference During a Pandemic: Evidence on the Effectiveness of Nebulized Ibuprofen as an Unproven Treatment for COVID-19 in Argentina

Sebastian Calonico, R. Tella, J. L. del Valle
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引用次数: 3

Abstract

Many medical decisions during the pandemic were made without the support of causal evidence obtained in clinical trials. We study the case of nebulized ibuprofen (NaIHS), a drug that was extensively used on COVID-19 patients in Argentina amidst wild claims about its effectiveness and without regulatory approval. We study data on 5,146 patients hospitalized in 11 health centers spread over 4 provinces, of which a total of 1,019 (19.8%) received the treatment. We find a large, negative and statistically significant correlation between NaIHS treatment and mortality using inverse probability weighting estimators. We consider several threats to identification, including the selection of "low" risks into NaIHS, spillovers affecting patients in the control group, and differences in the quality of care in centers that use NaIHS. While the negative correlation appears to be, broadly, robust, our results are best interpreted as emphasizing the benefits of running a randomized controlled trial and the challenges of incorporating information produced in other, less rigorous circumstances.
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大流行期间的因果推断:在阿根廷,雾化布洛芬作为一种未经证实的COVID-19治疗方法的有效性证据
大流行期间的许多医疗决定是在没有临床试验中获得的因果证据支持的情况下做出的。我们研究了雾化布洛芬(NaIHS)的案例,这种药物在阿根廷被广泛用于COVID-19患者,对其有效性提出了疯狂的说法,而且没有获得监管部门的批准。我们研究了分布在4个省的11个卫生中心的5146名住院患者的数据,其中共有1019名(19.8%)接受了治疗。使用逆概率加权估计,我们发现NaIHS治疗与死亡率之间存在显著的负相关。我们考虑了几种对鉴定的威胁,包括选择“低”风险进入NaIHS,影响对照组患者的溢出效应,以及使用NaIHS的中心的护理质量差异。虽然负相关性似乎是广泛而有力的,但我们的结果最好被解释为强调进行随机对照试验的好处,以及在其他不那么严格的情况下纳入信息的挑战。
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