Data_Sheet_1_Survival Factors and Metabolic Pathogenesis in Elderly Patients (≥65) With COVID-19: A Multi-Center Study.PDF

Background: Elderly patients infected with COVID-19 are reported to be facing a substantially increased risk of mortality. Clinical characteristics, treatment options, and potential survival factors remain under investigation. This study aimed to fill this gap and provide clinically relevant factors associated with survival of elderly patients with COVID-19.Methods: In this multi-center study, elderly patients (age ≥65 years old) with laboratory-confirmed COVID-19 from 4 Wuhan hospitals were included. The clinical end point was hospital discharge or deceased with last date of follow-up on Jul. 08, 2020. Clinical, demographic, and laboratory data were collected. Univariate and multivariate analysis were performed to analyze survival and risk factors. A metabolic flux analysis using a large-scale molecular model was applied to investigate the pathogenesis of SARS-CoV-2 with regard to metabolism pathways.Results: A total of 223 elderly patients infected with COVID-19 were included, 91 (40.8%) were discharged and 132 (59.2%) deceased. Acute respiratory distress syndrome (ARDS) developed in 140 (62.8%) patients, 23 (25.3%) of these patients survived. Multivariate analysis showed that potential risk factors for mortality were elevated D-Dimer (odds ratio: 1.13 [95% CI 1.04 - 1.22], p = 0.005), high immune-related metabolic index (6.42 [95% CI 2.66–15.48], p < 0.001), and increased neutrophil-to-lymphocyte ratio (1.08 [95% 1.03–1.13], p < 0.001). Elderly patients receiving interferon atmotherapy showed an increased probability of survival (0.29 [95% CI 0.17–0.51], p < 0.001). Based on these factors, an algorithm (AlgSurv) was developed to predict survival for elderly patients. The metabolic flux analysis showed that 12 metabolic pathways including phenylalanine (odds ratio: 28.27 [95% CI 10.56–75.72], p < 0.001), fatty acid (15.61 [95% CI 6.66–36.6], p < 0.001), and pyruvate (12.86 [95% CI 5.85–28.28], p < 0.001) showed a consistently lower flux in the survivors vs. the deceased subgroup. This may reflect a key pathogenic mechanism of COVID-19 infection.Conclusion: Several factors such as interferon atmotherapy and recreased activity of specific metabolic pathways were found to be associated with survival of elderly patients. Based on these findings, a survival algorithm (AlgSurv) was developed to assist the clinical stratification for elderly patients. Dysregulation of the metabolic pathways revealed in this study may aid in the drug and vaccine development against COVID-19.

背景：据报告，感染COVID-19的老年患者面临显著增高的死亡率风险。临床特征、治疗方案及潜在存活因素仍处于研究之中。本研究旨在填补这一空白，并提供与COVID-19老年患者存活相关的临床相关因素。方法：在本多中心研究中，纳入了来自武汉4家医院的实验室确诊的COVID-19老年患者（年龄≥65岁）。临床终点为截至2020年7月8日的最后随访日期的出院或死亡。收集了临床、人口统计学和实验室数据。进行了单变量和多变量分析，以分析存活和风险因素。采用大规模分子模型进行的代谢通量分析，旨在调查SARS-CoV-2的发病机制与代谢途径的关系。结果：共纳入223例感染COVID-19的老年患者，其中91例（40.8%）出院，132例（59.2%）死亡。在140例（62.8%）患者中发生了急性呼吸窘迫综合征（ARDS），其中23例（25.3%）存活。多变量分析显示，死亡的风险因素包括升高的D-二聚体（优势比：1.13 [95% CI 1.04 - 1.22]，p = 0.005）、高免疫相关代谢指数（6.42 [95% CI 2.66–15.48]，p < 0.001）和增高的中性粒细胞与淋巴细胞比率（1.08 [95% 1.03–1.13]，p < 0.001）。接受干扰素治疗的老年患者的存活概率增加（0.29 [95% CI 0.17–0.51]，p < 0.001）。基于这些因素，开发了一种算法（AlgSurv），用于预测老年患者的存活。代谢通量分析显示，与死亡亚组相比，12种代谢途径（包括苯丙氨酸[优势比：28.27 [95% CI 10.56–75.72]，p < 0.001]、脂肪酸[15.61 [95% CI 6.66–36.6]，p < 0.001]和丙酮酸[12.86 [95% CI 5.85–28.28]，p < 0.001]）的通量在存活者中普遍较低。这可能反映了COVID-19感染的关键致病机制。结论：发现了一些与老年患者存活相关的因素，如干扰素治疗和特定代谢途径的再生活性。基于这些发现，开发了一种存活算法（AlgSurv），以辅助对老年患者的临床分层。本研究揭示的代谢途径失调可能有助于COVID-19的药物和疫苗开发。