长新冠研究中的统计学考量
Statistical Considerations in Long COVID Research
AI总结：
该研究针对长新冠临床研究中的新数据分析挑战，结合RECOVER项目的观察性元队列，探讨长新冠定义特征与研究设计带来的统计学问题。
AI中文摘要：
长新冠是一种由SARS-CoV-2感染引发的、在感染后3个月或更久仍存在持续或复发症状的病症，它是重大的临床与公共卫生问题，据估计，5%-10%有SARS-CoV-2感染史的个体存在从轻度到致残的长期后遗症，对生活质量有深远影响。过去几年，长新冠的临床研究快速涌现，同时也出现了若干新的数据分析挑战。本手稿重点关注长新冠（LC）的定义特征及相关研究设计策略所带来的统计学挑战，该研究由“通过研究COVID促进康复（RECOVER）”成人与儿科观察性元队列研究驱动。
英文摘要：
Long COVID is a condition characterized by ongoing or relapsing symptoms attributable to SARS-CoV-2 infection that are present three or more months after infection. It represents a major clinical and public health concern as an estimated 5-10\% of individuals with a history of SARS-CoV-2 infection present with long term sequelae that range from mild to debilitating with profound impacts on quality of life. Clinical research studies of Long COVID have emerged rapidly over the past few years, and with them we are seeing several new data analytic challenges. In this manuscript, we highlight statistical challenges arising from the defining features of LC and associated study design strategies. This work is motivated by the Researching COVID to Enhance Recovery (RECOVER) Adult and Pediatric observational meta-cohort studies.
