Characteristics of hematological parameters on admission in COVID-19 Omicron variant infected in Chinese population: a large-scale retrospective study

Abstract

Abstract Background The Omicron variant of SARS-CoV-2, currently the most prevalent strain, has rapidly spread in Jingzhou, China, due to changes in the country’s epidemic prevention policy, resulting in an unprecedented increase in cases. Previous studies reported hematological parameters’ predictive value in COVID-19 severity and prognosis, but their relevance for early diagnosis in patients infected by the Omicron variant, particularly in high-risk pneumonia cases, remains unclear. Our study aimed to evaluate these parameters as early warning indicators for Omicron-infected patients in fever clinics and those with pulmonary infections (PI). Methods A total of 2,021 COVID-19 patients admitted to the fever clinic and infectious disease department of Jingzhou Hospital Affiliated to Yangtze University from November 1, 2022, to December 31, 2022, were retrospectively recruited. Demographic and hematological parameters were obtained from the electronic medical records of eligible patients. These hematological parameters were analyzed by receiver operating characteristic (ROC) curves to determine whether they can be used for early diagnosis of COVID-19 patients in fever clinics and the presence of PI in COVID-19 patients. Results Statistical differences in hematological parameters were observed between COVID-19 patients with fever and PI and control groups (P < 0.01). The ROC curve further demonstrated that lymphocyte (LYM) counts, neutrophil (NEU) counts, monocyte-to-lymphocyte ratios (MLR), platelet-to-lymphocyte ratios (PLR), white blood cell counts (WBC), and mean corpuscular hemoglobin concentration (MCHC) were the top 6 indicators in diagnosing Omicron infection with fever, with area under the curve (AUC) values of 0.738, 0.718, 0.713, 0.702, 0.700, and 0.687, respectively (P < 0.01). Furthermore, the mean platelet volume (MPV) with an AUC of 0.764, red blood cell count (RBC) with 0.753, hematocrit (HCT) with 0.698, MLR with 0.694, mean corpuscular hemoglobin (MCH) with 0.676, and systemic inflammation response indexes (SIRI) with 0.673 were the top 6 indicators for the diagnosis of COVID-19 patients with PI (P < 0.01). Conclusions LYM, NEU, MLR, PLR, WBC, and MCHC can serve as potential prescreening indicators for Omicron infection in fever clinics. Additionally, MPV, RBC, HCT, MLR, MCH, and SIRI can predict the presence of PI in COVID-19 patients infected by the Omicron variant.