PDF(Pubmed)
Abstract：
UNASSIGNED: COVID-19 modulates many serological biomarkers during the progress of disease severity. The study aimed to determine COVID-19 severity-associated perturbance in the serum profile.
UNASSIGNED: A retrospective study including COVID-19-positive individuals (n = 405) was accomplished. The serum profile of COVID-19 participants was mined from laboratory records. Severity-associated alteration in the serum profile was evaluated using Pearson correlation, regression, VCramer, Bayesian posterior VCramer, and bias factor using R-base-RStudio-version-3.3.0 with a significant cut-off of p < 0.05.
UNASSIGNED: Significantly different mean ± standard deviation (SD) (highly versus moderately severe) of C-reactive protein (CRP), ferritin, neutrophil-lymphocyte ratio (NLR), D-dimer, platelets, prothrombin time (PT), partial prothrombin time (PTT), troponin 1, lactate dehydrogenase (LDH), aspartate-aminotransferase (AST), alanine aminotransferase (ALT), and AST/ALT ratio was observed (p < 0.001). Highly severe COVID-19 associated with CRP, ferritin, NLR, in D-dimer, PT, PTT, troponin 1, AST/ALT ratio, AST and ALT (adjusted odds ratio (AOR): 1.346, 1.05, 1.46, 1.33, 1.42, 1.23, 4.07, 3.9, 1.24, 1.45, p < 0.001). CRP with ferritin (r = 0.743), NLR (r = 0.77), white blood cells (WBC) (r = 0.8), troponin1 with LDH (r = 0.757), and D-dimer with platelets (r = -0.81) were highly correlated. X2pearson (p < 0.001), VCramer (0.71), Bayesian-VCramer (0.7), and bias-factor (-125) for troponin 1 indicate the strong association of troponin 1 level and with COVID-19 severity. X2pearson (p < 0.001), VCramer (1), Bayesian-VCramer (0.98), and bias-factor (-266.3) for NLR exhibited a very strong association of pathologic conditions with the high severity of the disease.
UNASSIGNED: These biomarkers of inflammation (CRP, Ferritin, NLR), coagulation disorders (D-dimer, PT, and PTT) cardiac abnormality (troponin 1), and liver injury (AST/ALT) could be crucial in low-medical resource settings as potential prognosticator/predictors of the COVID-19 severity and clinical outcomes. Moreover, the outcome of this study could be leveraged for the early prediction of disease severity during SARS-CoV or Middle East Respiratory Coronavirus (MERS-CoV) infection.
UNASSIGNED: A retrospective study including COVID-19-positive individuals (n = 405) was accomplished. The serum profile of COVID-19 participants was mined from laboratory records. Severity-associated alteration in the serum profile was evaluated using Pearson correlation, regression, VCramer, Bayesian posterior VCramer, and bias factor using R-base-RStudio-version-3.3.0 with a significant cut-off of p < 0.05.
UNASSIGNED: Significantly different mean ± standard deviation (SD) (highly versus moderately severe) of C-reactive protein (CRP), ferritin, neutrophil-lymphocyte ratio (NLR), D-dimer, platelets, prothrombin time (PT), partial prothrombin time (PTT), troponin 1, lactate dehydrogenase (LDH), aspartate-aminotransferase (AST), alanine aminotransferase (ALT), and AST/ALT ratio was observed (p < 0.001). Highly severe COVID-19 associated with CRP, ferritin, NLR, in D-dimer, PT, PTT, troponin 1, AST/ALT ratio, AST and ALT (adjusted odds ratio (AOR): 1.346, 1.05, 1.46, 1.33, 1.42, 1.23, 4.07, 3.9, 1.24, 1.45, p < 0.001). CRP with ferritin (r = 0.743), NLR (r = 0.77), white blood cells (WBC) (r = 0.8), troponin1 with LDH (r = 0.757), and D-dimer with platelets (r = -0.81) were highly correlated. X2pearson (p < 0.001), VCramer (0.71), Bayesian-VCramer (0.7), and bias-factor (-125) for troponin 1 indicate the strong association of troponin 1 level and with COVID-19 severity. X2pearson (p < 0.001), VCramer (1), Bayesian-VCramer (0.98), and bias-factor (-266.3) for NLR exhibited a very strong association of pathologic conditions with the high severity of the disease.
UNASSIGNED: These biomarkers of inflammation (CRP, Ferritin, NLR), coagulation disorders (D-dimer, PT, and PTT) cardiac abnormality (troponin 1), and liver injury (AST/ALT) could be crucial in low-medical resource settings as potential prognosticator/predictors of the COVID-19 severity and clinical outcomes. Moreover, the outcome of this study could be leveraged for the early prediction of disease severity during SARS-CoV or Middle East Respiratory Coronavirus (MERS-CoV) infection.
摘要：
■COVID-19在疾病严重程度的进展过程中调节许多血清学生物标志物。该研究旨在确定血清谱中与COVID-19严重程度相关的扰动。
■完成了一项包括COVID-19阳性个体（n=405）的回顾性研究。COVID-19参与者的血清谱是从实验室记录中提取的。使用Pearson相关性评估血清谱中的严重程度相关改变，回归，VCramer,贝叶斯后验VCramer，和偏倚因子使用R-base-RStudio-version-3.3.0，显著截止p<0.05。
■C反应蛋白（CRP）的平均值±标准偏差（SD）（高度与中度重度）显着不同，铁蛋白,中性粒细胞-淋巴细胞比率（NLR），D-二聚体,血小板,凝血酶原时间（PT），部分凝血酶原时间(PTT),肌钙蛋白1，乳酸脱氢酶（LDH），天冬氨酸转氨酶（AST），丙氨酸氨基转移酶（ALT），和AST/ALT比值观察（p<0.001）。高度严重的COVID-19与CRP相关，铁蛋白,NLR,在D-二聚体中，PT,PTT,肌钙蛋白1，AST/ALT比值，AST和ALT（调整比值比（AOR）：1.346，1.05，1.46，1.33，1.42，1.23，4.07，3.9，1.24，1.45，p<0.001）。CRP与铁蛋白（r=0.743），NLR（r=0.77），白细胞（WBC）（r=0.8），肌钙蛋白1与LDH（r=0.757），D-二聚体与血小板高度相关(r=-0.81)。X2pearson(p<0.001)，VCramer(0.71),贝叶斯-VCramer(0.7)，肌钙蛋白1的偏倚因子（-125）表明肌钙蛋白1水平与COVID-19严重程度密切相关。X2pearson(p<0.001)，VCramer(1),贝叶斯-VCramer(0.98)，NLR的偏倚因子(-266.3)显示出病理状况与疾病严重程度非常强的关联。
■这些炎症生物标志物（CRP，铁蛋白,NLR),凝血障碍（D-二聚体，PT,和PTT）心脏异常（肌钙蛋白1），在低医疗资源环境中，肝损伤（AST/ALT）可能是COVID-19严重程度和临床结局的潜在预测因子。此外，这项研究的结果可用于SARS-CoV或中东呼吸道冠状病毒(MERS-CoV)感染期间疾病严重程度的早期预测.
■完成了一项包括COVID-19阳性个体（n=405）的回顾性研究。COVID-19参与者的血清谱是从实验室记录中提取的。使用Pearson相关性评估血清谱中的严重程度相关改变，回归，VCramer,贝叶斯后验VCramer，和偏倚因子使用R-base-RStudio-version-3.3.0，显著截止p<0.05。
■C反应蛋白（CRP）的平均值±标准偏差（SD）（高度与中度重度）显着不同，铁蛋白,中性粒细胞-淋巴细胞比率（NLR），D-二聚体,血小板,凝血酶原时间（PT），部分凝血酶原时间(PTT),肌钙蛋白1，乳酸脱氢酶（LDH），天冬氨酸转氨酶（AST），丙氨酸氨基转移酶（ALT），和AST/ALT比值观察（p<0.001）。高度严重的COVID-19与CRP相关，铁蛋白,NLR,在D-二聚体中，PT,PTT,肌钙蛋白1，AST/ALT比值，AST和ALT（调整比值比（AOR）：1.346，1.05，1.46，1.33，1.42，1.23，4.07，3.9，1.24，1.45，p<0.001）。CRP与铁蛋白（r=0.743），NLR（r=0.77），白细胞（WBC）（r=0.8），肌钙蛋白1与LDH（r=0.757），D-二聚体与血小板高度相关(r=-0.81)。X2pearson(p<0.001)，VCramer(0.71),贝叶斯-VCramer(0.7)，肌钙蛋白1的偏倚因子（-125）表明肌钙蛋白1水平与COVID-19严重程度密切相关。X2pearson(p<0.001)，VCramer(1),贝叶斯-VCramer(0.98)，NLR的偏倚因子(-266.3)显示出病理状况与疾病严重程度非常强的关联。
■这些炎症生物标志物（CRP，铁蛋白,NLR),凝血障碍（D-二聚体，PT,和PTT）心脏异常（肌钙蛋白1），在低医疗资源环境中，肝损伤（AST/ALT）可能是COVID-19严重程度和临床结局的潜在预测因子。此外，这项研究的结果可用于SARS-CoV或中东呼吸道冠状病毒(MERS-CoV)感染期间疾病严重程度的早期预测.
