Cardiology Department, Hospital Universitario de Santiago de Compostela, Choupana S/N, C.P. 15706, A Coruña, Spain.
CIBERCV, Madrid, Spain.
Sci Rep. 2021 Apr 30;11(1):9361. doi: 10.1038/s41598-021-88679-6.
Deterioration is sometimes unexpected in SARS-CoV2 infection. The aim of our study is to establish laboratory predictors of mortality in COVID-19 disease which can help to identify high risk patients. All patients admitted to hospital due to Covid-19 disease were included. Laboratory biomarkers that contributed with significant predictive value for predicting mortality to the clinical model were included. Cut-off points were established, and finally a risk score was built. 893 patients were included. Median age was 68.2 ± 15.2 years. 87(9.7%) were admitted to Intensive Care Unit (ICU) and 72(8.1%) needed mechanical ventilation support. 171(19.1%) patients died. A Covid-19 Lab score ranging from 0 to 30 points was calculated on the basis of a multivariate logistic regression model in order to predict mortality with a weighted score that included haemoglobin, erythrocytes, leukocytes, neutrophils, lymphocytes, creatinine, C-reactive protein, interleukin-6, procalcitonin, lactate dehydrogenase (LDH), and D-dimer. Three groups were established. Low mortality risk group under 12 points, 12 to 18 were included as moderate risk, and high risk group were those with 19 or more points. Low risk group as reference, moderate and high patients showed mortality OR 4.75(CI95% 2.60-8.68) and 23.86(CI 95% 13.61-41.84), respectively. C-statistic was 0-85(0.82-0.88) and Hosmer-Lemeshow p-value 0.63. Covid-19 Lab score can very easily predict mortality in patients at any moment during admission secondary to SARS-CoV2 infection. It is a simple and dynamic score, and it can be very easily replicated. It could help physicians to identify high risk patients to foresee clinical deterioration.
在 SARS-CoV2 感染中，病情恶化有时是出乎意料的。我们的研究目的是确定 COVID-19 疾病死亡的实验室预测指标，以帮助识别高危患者。所有因 COVID-19 疾病住院的患者均被纳入研究。纳入对死亡率有显著预测价值的实验室生物标志物，并建立预测模型。确定截断值，最终构建风险评分。共纳入 893 例患者。中位年龄为 68.2±15.2 岁。87 例（9.7%）患者被收入重症监护病房（ICU），72 例（8.1%）需要机械通气支持。171 例（19.1%）患者死亡。根据多变量逻辑回归模型计算出一个范围为 0 至 30 分的 COVID-19 实验室评分，以加权评分的形式预测死亡率，评分包含血红蛋白、红细胞、白细胞、中性粒细胞、淋巴细胞、肌酐、C 反应蛋白、白细胞介素-6、降钙素原、乳酸脱氢酶（LDH）和 D-二聚体。将患者分为三组：低死亡风险组评分<12 分，中危组评分 12-18 分，高危组评分≥19 分。以低危组为参照，中危和高危患者的死亡率比值比（OR）分别为 4.75（95%置信区间[CI] 2.60-8.68）和 23.86（95%CI 13.61-41.84）。C 统计量为 0-85（0.82-0.88），Hosmer-Lemeshow 检验 p 值为 0.63。COVID-19 实验室评分可在 SARS-CoV2 感染患者住院期间的任何时间轻松预测死亡率。它是一个简单且动态的评分，可以很容易地复制。它可以帮助医生识别高危患者，预测临床恶化。
