Suppr超能文献

生物标志物在预测 2019 年冠状病毒病严重程度中的作用。

Usefulness of biological markers in the early prediction of corona virus disease-2019 severity.

机构信息

Central Laboratory of Clinical Biology, University Hospital Center of Blida, Blida, Algeria.

Department of Internal Medicine and Cardiology, University Hospital Center of Blida, Blida, Algeria.

出版信息

Scand J Clin Lab Invest. 2020 Dec;80(8):611-618. doi: 10.1080/00365513.2020.1821396. Epub 2020 Sep 18.

Abstract

Coronavirus Disease 2019 is a very fast-spreading infectious disease. Severe forms are marked by a high mortality rate. The objective of this study is to identify routine biomarkers that can serve as early predictors of the disease progression. This is a prospective, single-center, cohort study involving 330 SARS-CoV-2 infected patients who were admitted at the University Hospital of Blida, Algeria in the period between the 27th of March and 22nd of April 2020. The ROC curve was used to evaluate the predictive performance of biomarkers, assessed at admission, in the early warning of progression toward severity. Multivariate logistic regression was used to quantify the independent risk for each marker. After an average follow-up period of 13.9 ± 3.5 days, 143 patients (43.3%) were classified as severe cases. Six biological abnormalities were identified as potential risk markers independently related to the severity: elevated urea nitrogen (>8.0 mmol/L, OR = 9.3 [2.7-31.7],  < .00001), elevated CRP (>42mg/L, OR = 7.5 [2.4-23.3],  = .001), decreased natremia (<133. 6 mmol/L, OR = 6.0 [2.0-17.4],  = .001), decreased albumin (<33.5 g/L, OR = 5.2 [1.7-16.6],  = .003), elevated LDH (>367 IU/L, OR = 4.9 [1.7-14.2],  = .003) and elevated neutrophil to lymphocyte ratio (>7.99, OR = 4.2, [1.4-12.2],  = .009). These easy-to-measure, time-saving and very low-cost parameters have been shown to be effective in the early prediction of the COVID-19 severity. Their use at the early admission stage can improve the risk stratification and management of medical care resources in order to reduce the mortality rate.

摘要

新型冠状病毒肺炎是一种传播速度非常快的传染病。严重的形式以高死亡率为特征。本研究的目的是确定常规生物标志物,作为疾病进展的早期预测指标。这是一项前瞻性、单中心、队列研究,共纳入 330 名于 2020 年 3 月 27 日至 4 月 22 日期间在阿尔及利亚布莱达大学医院住院的 SARS-CoV-2 感染患者。ROC 曲线用于评估入院时生物标志物的预测性能,以预警严重程度的进展。多变量逻辑回归用于量化每个标志物的独立风险。平均随访 13.9 ± 3.5 天后,143 例患者(43.3%)被归类为严重病例。确定了 6 种生物异常作为与严重程度独立相关的潜在风险标志物:尿素氮升高(>8.0mmol/L,OR=9.3[2.7-31.7],<0.00001)、CRP 升高(>42mg/L,OR=7.5[2.4-23.3],=0.001)、低钠血症(<133.6mmol/L,OR=6.0[2.0-17.4],=0.001)、白蛋白降低(<33.5g/L,OR=5.2[1.7-16.6],=0.003)、乳酸脱氢酶升高(>367IU/L,OR=4.9[1.7-14.2],=0.003)和中性粒细胞与淋巴细胞比值升高(>7.99,OR=4.2,[1.4-12.2],=0.009)。这些易于测量、节省时间且成本非常低的参数已被证明可有效预测 COVID-19 的严重程度。在早期入院阶段使用这些参数可以改善风险分层和医疗资源管理,以降低死亡率。

文献检索

告别复杂PubMed语法,用中文像聊天一样搜索,搜遍4000万医学文献。AI智能推荐,让科研检索更轻松。

立即免费搜索

文件翻译

保留排版,准确专业,支持PDF/Word/PPT等文件格式,支持 12+语言互译。

免费翻译文档

深度研究

AI帮你快速写综述,25分钟生成高质量综述,智能提取关键信息,辅助科研写作。

立即免费体验