Néant Nadège, Lingas Guillaume, Le Hingrat Quentin, Ghosn Jade, Engelmann Ilka, Lepiller Quentin, Gaymard Alexandre, Ferré Virginie, Hartard Cédric, Plantier Jean-Christophe, Thibault Vincent, Marlet Julien, Montes Brigitte, Bouiller Kevin, Lescure François-Xavier, Timsit Jean-François, Faure Emmanuel, Poissy Julien, Chidiac Christian, Raffi François, Kimmoun Antoine, Etienne Manuel, Richard Jean-Christophe, Tattevin Pierre, Garot Denis, Le Moing Vincent, Bachelet Delphine, Tardivon Coralie, Duval Xavier, Yazdanpanah Yazdan, Mentré France, Laouénan Cédric, Visseaux Benoit, Guedj Jérémie
Université de Paris, INSERM, IAME, F-75018 Paris, France;
Université de Paris, INSERM, IAME, F-75018 Paris, France.
Proc Natl Acad Sci U S A. 2021 Feb 23;118(8). doi: 10.1073/pnas.2017962118.
The characterization of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) viral kinetics in hospitalized patients and its association with mortality is unknown. We analyzed death and nasopharyngeal viral kinetics in 655 hospitalized patients from the prospective French COVID cohort. The model predicted a median peak viral load that coincided with symptom onset. Patients with age ≥65 y had a smaller loss rate of infected cells, leading to a delayed median time to viral clearance occurring 16 d after symptom onset as compared to 13 d in younger patients ( < 10). In multivariate analysis, the risk factors associated with mortality were age ≥65 y, male gender, and presence of chronic pulmonary disease (hazard ratio [HR] > 2.0). Using a joint model, viral dynamics after hospital admission was an independent predictor of mortality (HR = 1.31, < 10). Finally, we used our model to simulate the effects of effective pharmacological interventions on time to viral clearance and mortality. A treatment able to reduce viral production by 90% upon hospital admission would shorten the time to viral clearance by 2.0 and 2.9 d in patients of age <65 y and ≥65 y, respectively. Assuming that the association between viral dynamics and mortality would remain similar to that observed in our population, this could translate into a reduction of mortality from 19 to 14% in patients of age ≥65 y with risk factors. Our results show that viral dynamics is associated with mortality in hospitalized patients. Strategies aiming to reduce viral load could have an effect on mortality rate in this population.
住院患者中严重急性呼吸综合征冠状病毒2(SARS-CoV-2)的病毒动力学特征及其与死亡率的关联尚不清楚。我们分析了来自前瞻性法国COVID队列的655名住院患者的死亡情况和鼻咽部病毒动力学。该模型预测的病毒载量中位数与症状发作时间一致。年龄≥65岁的患者感染细胞的损失率较小,导致病毒清除的中位时间延迟,症状发作后16天出现病毒清除,而年轻患者(<10岁)为13天。在多变量分析中,与死亡率相关的危险因素为年龄≥65岁、男性和存在慢性肺病(风险比[HR]>2.0)。使用联合模型,入院后的病毒动力学是死亡率的独立预测因素(HR = 1.31,<10)。最后,我们使用我们的模型来模拟有效药物干预对病毒清除时间和死亡率的影响。一种在入院时能够将病毒产生减少90%的治疗方法,可分别将<65岁和≥65岁患者的病毒清除时间缩短2.0天和2.9天。假设病毒动力学与死亡率之间的关联与我们人群中观察到的相似,这可能会使有危险因素的≥65岁患者的死亡率从19%降至14%。我们的结果表明,病毒动力学与住院患者的死亡率相关。旨在降低病毒载量的策略可能会对该人群的死亡率产生影响。