Background: Coronavirus disease caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2 or COVID-19) is a heterogeneous disorder with a complex pathogenesis. Recent studies from Spain and France have indicated that underlying phenotypes may exist among patients admitted to the hospital with COVID-19. Whether those same phenotypes exist in the United States (US) remains unclear. Using latent class analysis (LCA), we sought to determine whether clinical phenotypes exist among patients admitted for COVID-19.
Methods: We reviewed the charts of adult patients who were hospitalized primarily for COVID-19 at Greenwich Hospital and performed LCA using variables based on patient demographics and comorbidities. To further examine the reliability and replicability of the clustering results, we repeated LCA on the cohort of patients who died during hospitalization for COVID-19.
Results: Two phenotypes were identified in patients admitted for COVID-19 (N = 483). According to phenotype, patients were designated as cluster 1 (C1) or cluster 2 (C2). C1 (n = 193) consisted of older individuals with more comorbidities and a higher mortality rate (25.4% vs 8.97%, p < 0.001) than patients in C2. C2 (n = 290) consisted of younger individuals who were more likely to be obese, male, and nonwhite, with higher levels of the inflammatory markers C-reactive protein and alanine aminotransferase. When we performed LCA on the cohort of patients who died during hospitalization for COVID-19 (n = 75), we found that the distribution of patient baseline characteristics and comorbidities was similar to that of the entire cohort of patients admitted for COVID-19.
Conclusion: Using LCA, we identified two clinical phenotypes of patients who were admitted to our hospital for COVID-19. These findings may reflect different pathophysiologic processes that lead to moderate to severe COVID-19 and may be useful for identifying treatment targets and selecting patients with severe COVID-19 disease for future clinical trials.



中文翻译：

---

使用潜在类别分析鉴定美国 COVID-19 患者的表型

背景：由严重急性呼吸综合征冠状病毒 2（SARS-CoV-2 或 COVID-19）引起的冠状病毒病是一种具有复杂发病机制的异质性疾病。西班牙和法国最近的研究表明，住院的 COVID-19 患者可能存在潜在的表型。在美国 (US) 是否存在这些相同的表型仍不清楚。使用潜在类别分析 (LCA)，我们试图确定因 COVID-19 入院的患者中是否存在临床表型。
方法：我们回顾了在格林威治医院主要因 COVID-19 住院的成年患者的图表，并使用基于患者人口统计和合并症的变量进行 LCA。为了进一步检查聚类结果的可靠性和可复制性，我们对 COVID-19 住院期间死亡的患者队列重复了 LCA。
结果：在因 COVID-19 入院的患者中发现了两种表型（N = 483）。根据表型，患者被指定为集群 1 (C1) 或集群 2 (C2)。C1 (n = 193) 由比 C2 患者具有更多合并症和更高死亡率 (25.4% vs 8.97%, p < 0.001) 的老年人组成。C2 (n = 290) 由更可能是肥胖、男性和非白人的年轻人组成，其炎症标志物 C 反应蛋白和丙氨酸氨基转移酶水平较高。当我们对因 COVID-19 住院期间死亡的患者队列（n = 75）进行 LCA 时，我们发现患者基线特征和合并症的分布与因 COVID-19 入院的整个患者队列相似。
结论：使用 LCA，我们确定了因 COVID-19 而入院的患者的两种临床表型。这些发现可能反映了导致中度至重度 COVID-19 的不同病理生理过程，并可能有助于确定治疗目标和选择患有严重 COVID-19 疾病的患者进行未来的临床试验。