Leukocyte differential and reactive lymphocyte counts from Sysmex XN analyzer in the evaluation of SARS-CoV-2 infection.

BACKGROUND: Leukocyte differential present certain features in COVID 19 patients. RE-LYMP (reactive lymphocytes) is an extended inflammation parameter (EIP) reported by XN analyzer (Sysmex Corporation, Kobe, Japan) reflect the activation of lymphocytes triggered by infections. We aimed to assess the clinical utility of these parameters as biomarkers for the rapid detection of COVID 19. METHODS: The study group included 200 COVID 19 and 167 patients with other infections at admission. Differences of leukocyte differential, neutrophil/lymphocyte ratio (NLR) and EIP among groups were assessed with the Kruskal-Wallis test; parameters statiscally different in the groups were tested with Receiver operating characteristic (ROC) curve analysis to assess their diagnostic performance in distinguishing SARS-CoV-2 infections. The reliability of the selected parameters was evaluated in a validation group of 347 patients (160 COVID 19 and 187 other infections). RESULTS: NLR performed well to discard viral infections, area under curve (AUC) 0.988 (95%CI 0.973 - 0.991) and RE-LYMP was useful to distinguish COVID 19 and bacterial infections AUC 0.920 (95%CI 0.884 - 0.948); the two conditions NLR> 3.3 RE-LYMP> 0.6% was applied to the validation group and 153 out of 160 COVID 19 patients were correctly distinguished (95.6%). CONCLUSIONS: Early diagnosis of SARS-CoV-2 infection is critical for better caring of patients and to reduce the threat of nosocomial infection for professionals. Leukocyte differential and RE-LYMPH could assist in a preliminary differential diagnosis of the disease.

COVID-19 and hematology findings based on the current evidences: A puzzle with many missing pieces.

In December 2019, a new type of coronavirus was detected for the first time in Wuhan, Hubei Province, China. According to the reported data, the emerging coronavirus has spread worldwide, infecting more than fifty-seven million individuals, leading to more than one million deaths. The current study aimed to review and discuss the hematological findings of COVID-19. Laboratory changes and hematologic abnormalities have been reported repeatedly in COVID-19 patients. WBC count and peripheral blood lymphocytes are normal or slightly reduced while these indicators may change with the progression of the disease. In addition, several studies demonstrated that decreased hemoglobin levels in COVID-19 patients were associated with the severity of the disease. Moreover, thrombocytopenia, which is reported in 5%-40% of patients, is known to be associated with poor prognosis of the disease. COVID-19 can present with various hematologic manifestations. In this regard, accurate evaluation of laboratory indicators at the beginning and during COVID-19 can help physicians to adjust appropriate treatment and provide special and prompt care for those in need.

The hematology laboratory's response to the COVID-19 pandemic: A scoping review.

The ongoing COVID-19 pandemic has had a profound worldwide impact on the laboratory hematology community. Nevertheless, the pace of COVID-19 hematology-related research has continued to accelerate and has established the role of laboratory hematology data for many purposes including disease prognosis and outcome. The purpose of this scoping review was to assess the current state of COVID-19 laboratory hematology research. A comprehensive search of the literature published between December 1, 2019, and July 3, 2020, was performed, and we analyzed the sources, publication dates, study types, and topics of the retrieved studies. Overall, 402 studies were included in this scoping review. Approximately half of these studies (n = 202, 50.37%) originated in China. Retrospective cohort studies comprised the largest study type (n = 176, 43.89%). Prognosis/ risk factors, epidemiology, and coagulation were the most common topics. The number of studies published per day has increased through the end of May. The studies were heavily biased in favor of papers originating in China and on retrospective clinical studies with limited use of and reporting of laboratory data. Despite the major improvements in our understanding of the role of coagulation, automated hematology, and cell morphology in COVID-19, there are gaps in the literature, including biosafety and the laboratory role in screening and prevention of COVID-19. There is a gap in the publication of papers focused on guidelines for the laboratory. Our findings suggest that, despite the large number of publications related to laboratory data and their use in COVID-19 disease, many areas remain unexplored or under-reported.

A meta-analysis of SARS-CoV-2 patients identifies the combinatorial significance of D-dimer, C-reactive protein, lymphocyte, and neutrophil values as a predictor of disease severity.

BACKGROUND: Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), known to be the causative agent of COVID-19, has led to a worldwide pandemic. At presentation, individual clinical laboratory blood values, such as lymphocyte counts or C-reactive protein (CRP) levels, may be abnormal and associated with disease severity. However, combinatorial interpretation of these laboratory blood values, in the context of COVID-19, remains a challenge. METHODS: To assess the significance of multiple laboratory blood values in patients with SARS-CoV-2 and develop a COVID-19 predictive equation, we conducted a literature search using PubMed to seek articles that included defined laboratory data points along with clinical disease progression. We identified 9846 papers, selecting primary studies with at least 20 patients for univariate analysis to identify clinical variables predicting nonsevere and severe COVID-19 cases. Multiple regression analysis was performed on a training set of patient studies to generate severity predictor equations, and subsequently tested on a validation cohort of 151 patients who had a median duration of observation of 14 days. RESULTS: Two COVID-19 predictive equations were generated: one using four variables (CRP, D-dimer levels, lymphocyte count, and neutrophil count), and another using three variables (CRP, lymphocyte count, and neutrophil count). In adult and pediatric populations, the predictive equations exhibited high specificity, sensitivity, positive predictive values, and negative predictive values. CONCLUSION: Using the generated equations, the outcomes of COVID-19 patients can be predicted using commonly obtained clinical laboratory data. These predictive equations may inform future studies evaluating the long-term follow-up of COVID-19 patients.