Assessment of COVID-19 progression on day 5 from symptoms onset.
Assessment of COVID-19 progression on day 5 from symptoms onset.
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DOI：
10.1186/s12879-021-06596-5
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发表时间：
2021-08-28
影响因子：
3.7
通讯作者：
Tacconelli E
中科院分区：
文献类型：
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作者：
Gentilotti E;Savoldi A;Compri M;Górska A;De Nardo P;Visentin A;Be G;Razzaboni E;Soriolo N;Meneghin D;Girelli D;Micheletto C;Mehrabi S;Righi E;Tacconelli E
目前COVID-19患者预测预后模型的一个主要局限性是疾病阶段和持续时间方面的人群异质性。本研究旨在确定一组临床和实验室参数，这些参数在症状发作的第5天可以预测COVID-19住院患者的疾病进展。对COVID-19住院成人患者的前瞻性队列研究。在固定时间点收集患者水平的流行病学、临床和实验室数据：症状发作后第5、10和15天。COVID-19进展定义为症状发作后第11天内的院内死亡和/或转入ICU和/或呼吸衰竭（PaO 2/FiO 2比值< 200）。进行多变量回归以确定COVID-19进展的预测因素。提出了在症状发作的第5天评估的模型，包括男性、年龄> 65岁、呼吸困难、心血管疾病以及CRP（> 80 U/L）、ALT（> 40 U/L）、NLR（> 4.5）、LDH（> 250 U/L）和CK（> 80 U/L）中的至少三个异常实验室参数。通过计算受试者工作特征（AUC）值下的面积来评估辨别力。总共有235名COVID-19患者被前瞻性纳入3个月的研究。大多数患者为男性（148，63%），平均年龄为71岁（SD 15.9）。190例患者（81%）患有至少一种基础疾病，最常见的是心血管疾病（47%）、神经/精神疾病（35%）和糖尿病（21%）。其中88人（37%）出现COVID-19进展。所提出的模型显示预测第11天疾病进展的AUC为0.73（95% CI 0.66-0.81）。在症状发作的第5天计算的一组易于使用的实验室/临床参数预测了COVID-19的进展，具有公平的区分能力。在症状发作的第5天评估这些特征可以帮助临床医生做出决策。该模型还可以作为一种工具，在住院患者的COVID-19治疗临床试验中提高人群的同质性。
A major limitation of current predictive prognostic models in patients with COVID-19 is the heterogeneity of population in terms of disease stage and duration. This study aims at identifying a panel of clinical and laboratory parameters that at day-5 of symptoms onset could predict disease progression in hospitalized patients with COVID-19. Prospective cohort study on hospitalized adult patients with COVID-19. Patient-level epidemiological, clinical, and laboratory data were collected at fixed time-points: day 5, 10, and 15 from symptoms onset. COVID-19 progression was defined as in-hospital death and/or transfer to ICU and/or respiratory failure (PaO2/FiO2 ratio < 200) within day-11 of symptoms onset. Multivariate regression was performed to identify predictors of COVID-19 progression. A model assessed at day-5 of symptoms onset including male sex, age > 65 years, dyspnoea, cardiovascular disease, and at least three abnormal laboratory parameters among CRP (> 80 U/L), ALT (> 40 U/L), NLR (> 4.5), LDH (> 250 U/L), and CK (> 80 U/L) was proposed. Discrimination power was assessed by computing area under the receiver operating characteristic (AUC) values. A total of 235 patients with COVID-19 were prospectively included in a 3-month period. The majority of patients were male (148, 63%) and the mean age was 71 (SD 15.9). One hundred and ninety patients (81%) suffered from at least one underlying illness, most frequently cardiovascular disease (47%), neurological/psychiatric disorders (35%), and diabetes (21%). Among them 88 (37%) experienced COVID-19 progression. The proposed model showed an AUC of 0.73 (95% CI 0.66–0.81) for predicting disease progression by day-11. An easy-to-use panel of laboratory/clinical parameters computed at day-5 of symptoms onset predicts, with fair discrimination ability, COVID-19 progression. Assessment of these features at day-5 of symptoms onset could facilitate clinicians’ decision making. The model can also play a role as a tool to increase homogeneity of population in clinical trials on COVID-19 treatment in hospitalized patients.