Department of Pathology, Montefiore Medical Center, Albert Einstein College of Medicine, Bronx, New York, United States of America.
Department of Medicine, Saint Vincent's Medical Center, Bridgeport, Connecticut, United States of America.
PLoS One. 2020 Dec 31;15(12):e0244777. doi: 10.1371/journal.pone.0244777. eCollection 2020.
Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) cycle threshold (Ct) has been suggested as an approximate measure of initial viral burden. The utility of cycle threshold, at admission, as a predictor of disease severity has not been thoroughly investigated.
We conducted a retrospective study of SARS-CoV-2 positive, hospitalized patients from 3/26/2020 to 8/5/2020 who had SARS-CoV-2 Ct data within 48 hours of admission (n = 1044). Only patients with complete survival data, discharged (n = 774) or died in hospital (n = 270), were included in our analysis. Laboratory, demographic, and clinical data were extracted from electronic medical records. Multivariable logistic regression was applied to examine the relationship of patient mortality with Ct values while adjusting for established risk factors. Ct was analyzed as continuous variable and subdivided into quartiles to better illustrate its relationship with outcome. Cumulative incidence curves were created to assess whether there was a survival difference in the setting of the competing risks of death versus patient discharge. Mean Ct at admission was higher for survivors (28.6, SD = 5.8) compared to non-survivors (24.8, SD = 6.0, P<0.001). In-hospital mortality significantly differed (p<0.05) by Ct quartile. After adjusting for age, gender, BMI, hypertension and diabetes, increased cycle threshold was associated with decreased odds of in-hospital mortality (0.91, CI 0.89-0.94, p<0.001). Compared to the 4th Quartile, patients with Ct values in the 1st Quartile (Ct <22.9) and 2nd Quartile (Ct 23.0-27.3) had an adjusted odds ratio of in-hospital mortality of 3.8 and 2.6 respectively (p<0.001). The discriminative ability of Ct to predict inpatient mortality was found to be limited, possessing an area under the curve (AUC) of 0.68 (CI 0.63-0.71).
SARS-CoV-2 Ct was found to be an independent predictor of patient mortality. However, further study is needed on how to best clinically utilize such information given the result variation due to specimen quality, phase of disease, and the limited discriminative ability of the test.
严重急性呼吸综合征冠状病毒 2(SARS-CoV-2)循环阈值(Ct)已被认为是初始病毒载量的近似测量值。Ct 值在入院时作为疾病严重程度的预测因子的效用尚未得到彻底研究。
我们对 2020 年 3 月 26 日至 2020 年 8 月 5 日期间住院的 SARS-CoV-2 阳性患者进行了回顾性研究,这些患者在入院后 48 小时内有 SARS-CoV-2Ct 值数据(n=1044)。只有具有完整生存数据的患者,出院(n=774)或在医院死亡(n=270),才被纳入我们的分析。从电子病历中提取实验室、人口统计学和临床数据。应用多变量逻辑回归来检查患者死亡率与 Ct 值的关系,同时调整已建立的危险因素。将 Ct 作为连续变量进行分析,并细分为四分位数,以更好地说明其与结果的关系。创建累积发病率曲线,以评估在死亡与患者出院的竞争风险背景下是否存在生存差异。与非幸存者相比,幸存者的入院时平均 Ct 值更高(28.6,标准差[SD]=5.8)(P<0.001)。住院死亡率按 Ct 四分位值显著不同(p<0.05)。在调整年龄、性别、BMI、高血压和糖尿病后,循环阈值升高与住院死亡率降低相关(0.91,CI0.89-0.94,P<0.001)。与第 4 四分位值相比,Ct 值处于第 1 四分位值(Ct<22.9)和第 2 四分位值(Ct23.0-27.3)的患者住院死亡率的调整比值比分别为 3.8 和 2.6(P<0.001)。发现 Ct 预测住院死亡率的判别能力有限,其曲线下面积(AUC)为 0.68(CI0.63-0.71)。
SARS-CoV-2Ct 被发现是患者死亡率的独立预测因子。然而,鉴于标本质量、疾病阶段和测试的有限判别能力导致结果存在差异,还需要进一步研究如何在临床中最好地利用这些信息。