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炎症标志物预测 COVID-19 患者 ICU 收治风险的预后准确性:时间依赖性受试者工作特征曲线的应用。

Prognostic accuracy of inflammatory markers in predicting risk of ICU admission for COVID-19: application of time-dependent receiver operating characteristic curves.

机构信息

Social Determinants of Health Research Center, Health Research Institute, Babol University of Medical Sciences, Babol, Iran.

Department of Biostatistics and Epidemiology, School of Public Health, Babol University of Medical Sciences, Babol, Iran.

出版信息

J Int Med Res. 2022 Jun;50(6):3000605221102217. doi: 10.1177/03000605221102217.

Abstract

OBJECTIVE

Intensive care unit (ICU) admission occurs at different times during hospitalization among patients with COVID-19. We aimed to evaluate the time-dependent receive operating characteristic (ROC) curve and area under the ROC curve, AUC(t), and accuracy of baseline levels of inflammatory markers C-reactive protein (CRP) and neutrophil-to-lymphocyte ratio (NLR) in predicting time to an ICU admission event in patients with severe COVID-19 infection.

METHODS

In this observational study, we evaluated 724 patients with confirmed severe COVID-19 referred to Ayatollah Rohani Hospital, affiliated with Babol University of Medical Sciences, Iran.

RESULTS

The AUC(t) of CRP and NLR reached 0.741 (95% confidence interval [CI]: 0.661-0.820) and 0.690 (95% CI: 0.607-0.772), respectively, in the first 3 days after hospital admission. The optimal cutoff values of CRP and NLR for stratification of ICU admission outcomes in patients with severe COVID-19 were 78 mg/L and 5.13, respectively. The risk of ICU admission was significantly greater for patients with these cutoff values (CRP hazard ratio = 2.98; 95% CI: 1.58-5.62; NLR hazard ratio = 2.90; 95% CI: 1.45-5.77).

CONCLUSIONS

Using time-dependent ROC curves, CRP and NLR values at hospital admission were important predictors of ICU admission. This approach is more efficient than using standard ROC curves.

摘要

目的

COVID-19 患者的 ICU 入院时间在住院期间有所不同。我们旨在评估时间依赖性接收者操作特征(ROC)曲线和 ROC 曲线下面积(AUC(t))以及炎症标志物 C 反应蛋白(CRP)和中性粒细胞与淋巴细胞比值(NLR)基线水平在预测严重 COVID-19 感染患者 ICU 入院事件时间的准确性。

方法

在这项观察性研究中,我们评估了来自伊朗巴博尔医科大学阿亚图拉罗哈尼医院的 724 名确诊为严重 COVID-19 的患者。

结果

CRP 和 NLR 的 AUC(t) 在入院后 3 天内分别达到 0.741(95%置信区间 [CI]:0.661-0.820)和 0.690(95% CI:0.607-0.772)。CRP 和 NLR 用于分层严重 COVID-19 患者 ICU 入院结局的最佳截断值分别为 78mg/L 和 5.13。对于这些截断值的患者,ICU 入院的风险显著增加(CRP 风险比=2.98;95%CI:1.58-5.62;NLR 风险比=2.90;95%CI:1.45-5.77)。

结论

使用时间依赖性 ROC 曲线,入院时 CRP 和 NLR 值是 ICU 入院的重要预测因素。这种方法比使用标准 ROC 曲线更有效。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0b59/9208048/e65ca0022429/10.1177_03000605221102217-fig1.jpg

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