Lamichhane Anit, Pokhrel Sushant, Thapa Tika Bahadur, Shrestha Ojaswee, Kadel Anuradha, Joshi Govardhan, Khanal Sudip
Department of Laboratory Medicine, Manmohan Memorial Institute of Health Sciences, Kathmandu, Nepal.
Department of Pathology, Sumeru Hospital Pvt Ltd., Lalitpur, Nepal.
Adv Med. 2023 Oct 19;2023:6216528. doi: 10.1155/2023/6216528. eCollection 2023.
The global threat of COVID-19 has created the need for researchers to investigate the disease's progression, especially through the use of biomarkers to inform interventions. This study aims to assess the correlations of laboratory parameters to determine the severity of COVID-19 infection.
This study was conducted among 191 COVID-19 patients in Sumeru Hospital, Lalitpur, Nepal. According to their clinical outcomes, these patients were divided into severe and nonsevere groups. Inflammatory markers such as LDH, D-dimer, CRP, ferritin, complete blood cell count, liver function tests, and renal function tests were performed. Binary logistic regression analysis determined relative risk factors associated with severe COVID-19. The area under the curve (AUC) was calculated with ROC curves to assess the potential predictive value of risk factors.
Out of 191 patients, 38 (19.8%) subjects died due to COVID-19 complications, while 156 (81.7%) survived and were discharged from hospital. The COVID-19 severity was found in patients with older age and comorbidities such as CKD, HTN, DM, COPD, and pneumonia. Parameters such as d-dimer, CRP, LDH, SGPT, neutrophil, lymphocyte count, and LMR were significant independent risk factors for the severity of the disease. The AUC was highest for d-dimer (AUC = 0.874) with a sensitivity of 82.2% and specificity of 81.2%. Similarly, the cut-off values for other factors were age >54.5 years, D-dimer >0.91 ng/ml, CRP >82.4 mg/dl, neutrophil >78.5%, LDH >600 U/L, and SGPT >35.5 U/L, respectively.
Endorsement of biochemical and hematological parameters with their cut-off values also aids in predicting COVID-19 severity. The biomarkers such as D-dimer, CRP levels, LDH, ALT, and neutrophil count could be used to predict disease severity. So, timely analysis of these markers might allow early prediction of disease progression.
新型冠状病毒肺炎（COVID-19）的全球威胁促使研究人员对该疾病的进展进行调查，特别是通过使用生物标志物来为干预措施提供依据。本研究旨在评估实验室参数之间的相关性，以确定COVID-19感染的严重程度。
本研究在尼泊尔拉利特布尔须弥医院的191例COVID-19患者中进行。根据临床结果，这些患者被分为重症组和非重症组。检测了乳酸脱氢酶（LDH）、D-二聚体、C反应蛋白（CRP）、铁蛋白、全血细胞计数、肝功能检查和肾功能检查等炎症标志物。二元逻辑回归分析确定了与重症COVID-19相关的相对危险因素。通过ROC曲线计算曲线下面积（AUC），以评估危险因素的潜在预测价值。
191例患者中，38例（19.8%）因COVID-19并发症死亡，156例（81.7%）存活并出院。在年龄较大以及患有慢性肾脏病（CKD）、高血压（HTN）、糖尿病（DM）、慢性阻塞性肺疾病（COPD）和肺炎等合并症的患者中发现了COVID-19的严重程度。D-二聚体、CRP、LDH、谷丙转氨酶（SGPT）、中性粒细胞、淋巴细胞计数和淋巴细胞与单核细胞比值（LMR）等参数是该疾病严重程度的显著独立危险因素。D-二聚体的AUC最高（AUC = 0.874），敏感性为82.2%，特异性为81.2%。同样，其他因素的临界值分别为年龄>54.5岁、D-二聚体>0.91 ng/ml、CRP>82.4 mg/dl、中性粒细胞>78.5%、LDH>600 U/L和SGPT>35.5 U/L。
认可生化和血液学参数及其临界值也有助于预测COVID-19的严重程度。D-二聚体、CRP水平、LDH、谷丙转氨酶（ALT）和中性粒细胞计数等生物标志物可用于预测疾病严重程度。因此，及时分析这些标志物可能有助于早期预测疾病进展。
