Critical Care Medicine Department, Beijing Ditan Hospital, Capital Medical University, No. 8 Jing Shun East Street, Beijing, 100015, China.
Center of Integrative Medicine, Beijing Ditan Hospital, Capital Medical University, No. 8 Jing Shun East Street, Beijing, 100015, China.
J Transl Med. 2020 May 20;18(1):206. doi: 10.1186/s12967-020-02374-0.
Patients with critical illness due to infection with the 2019 coronavirus disease (COVID-19) show rapid disease progression to acute respiratory failure. The study aimed to screen the most useful predictive factor for critical illness caused by COVID-19.
The study prospectively involved 61 patients with COVID-19 infection as a derivation cohort, and 54 patients as a validation cohort. The predictive factor for critical illness was selected using LASSO regression analysis. A nomogram based on non-specific laboratory indicators was built to predict the probability of critical illness.
The neutrophil-to-lymphocyte ratio (NLR) was identified as an independent risk factor for critical illness in patients with COVID-19 infection. The NLR had an area under receiver operating characteristic of 0.849 (95% confidence interval [CI], 0.707 to 0.991) in the derivation cohort and 0.867 (95% CI 0.747 to 0.944) in the validation cohort, the calibration curves fitted well, and the decision and clinical impact curves showed that the NLR had high standardized net benefit. In addition, the incidence of critical illness was 9.1% (1/11) for patients aged ≥ 50 and having an NLR < 3.13, and 50% (7/14) patients with age ≥ 50 and NLR ≥ 3.13 were predicted to develop critical illness. Based on the risk stratification of NLR according to age, this study has developed a COVID-19 pneumonia management process.
We found that NLR is a predictive factor for early-stage prediction of patients infected with COVID-19 who are likely to develop critical illness. Patients aged ≥ 50 and having an NLR ≥ 3.13 are predicted to develop critical illness, and they should thus have rapid access to an intensive care unit if necessary.
感染 2019 年冠状病毒病(COVID-19)的重症患者会迅速发展为急性呼吸衰竭。本研究旨在筛选 COVID-19 导致重症的最有用的预测因素。
本研究前瞻性纳入 61 例 COVID-19 感染患者作为推导队列,54 例患者作为验证队列。使用 LASSO 回归分析筛选重症预测因素。建立基于非特异性实验室指标的列线图预测重症的概率。
中性粒细胞与淋巴细胞比值(NLR)被确定为 COVID-19 感染患者发生重症的独立危险因素。在推导队列中,NLR 的受试者工作特征曲线下面积为 0.849(95%置信区间,0.707 至 0.991),在验证队列中为 0.867(95%置信区间,0.747 至 0.944),校准曲线拟合良好,决策和临床影响曲线表明 NLR 具有较高的标准化净效益。此外,年龄≥50 岁且 NLR<3.13 的患者重症发生率为 9.1%(1/11),年龄≥50 岁且 NLR≥3.13 的患者有 50%(7/14)被预测发生重症。基于 NLR 根据年龄的风险分层,本研究制定了 COVID-19 肺炎管理流程。
我们发现 NLR 是预测 COVID-19 感染患者发生重症的早期预测因素。年龄≥50 岁且 NLR≥3.13 的患者有发生重症的风险,必要时应迅速转入重症监护病房。