ABSTRACT
Background: Cell population data (CPD) are reported as part of leukocyte differentials by Mindray BC 6800Plus analyzer, give information of the size (Neu Z, Lym Z, Mon Z) nucleic acid content (Neu Y, Lym Y, Mon Y) and internal structure (Neu X, Lym X, Mon X) of leukocytes. We evaluated the potential utility of the leukocyte differential and CPD as laboratory indicators for the detection of coronavirus disease 2019 (COVID-19) in patients when admitted to the Emergency Department. Methods: A total of 672 patients with suspected infection were recruited at admission to the Hospital. The study group included 237 (151 COVID-19, 33 other virus, 53 bacterial infections). We applied the unsupervised K-means clustering method and principal component analysis (PCA). A validation group of 435 patients, 268 COVID-19 and 167 non-COVID-19 was used to verify the reliability of our model. Results: The COVID-19 cases presented the typical neutrophilia and lymphopenia, high Mon Z, and intermediate values of Neu X and Neu Y. The study group was classified into two clusters. This model was applied to the validation set;PCA analysis showed that almost 45.71% of the data variability could be explained by the two clusters. Cluster 1 had higher neutrophil counts, Neutrophil Lymphocyte ratio, Neu X, Neu Y and Mon Z, and Cluster 2, higher lymphocyte counts (P<0.05). Cluster 1 which included 91.4% of the COVID-19 patients and 60.5% of non-COVID-19 patients were assigned to Cluster 2, notably 100% of other viral infections. Conclusions: Leukocyte count (WBC) differential and CPD seem reliable parameters for the initial evaluation of patients with fever of unknown origin. By means of K analysis, the patients can be classified into distinct groups according to the etiology of the infection. © Journal of Laboratory and Precision Medicine. All rights reserved.
ABSTRACT
Introduction: Leukocyte differential, present certain features in SARS-CoV2 infected patients neutrophilia, lymphopenia and morphology alterations, which could be useful for screening. Cell population data (CPD) are reported as part of leukocyte differentials by Sysmex XN analyze;they are morphometric parameters that characterize neutrophils, lymphocytes and monocytes and classify them according to their volume, granularity and their content in nucleic acids. CPD reflects in numbers the changes in morphology and activation status triggered by infections. We aimed to evaluate the predictive power of CPDs for the differential diagnosis of COVID19 versus non-COVID19 pneumonia. Method(s): The prospective, observational, multicenter study was conducted in 3 hospitals, including patients > 18 years admitted with the diagnosis community-acquired pneumonia in the period November 2019 - October 2020. Complete blood count were analyzed using Sysmex XN counters. Diagnosis of SARS-CoV-2 infection was done using real-time reverse transcriptionpolymerase chain reaction. Patients were divided into two groups: (1) referral cohort in a hospital for the development of the model (2) the sample of two other hospitals for its validation. Multivariate logistic regression model has been developed for the detection of COVID patients. Robustness of the model has been evaluated by means of the area under the ROC curve and the calibration of the model. Statisticalsignificance p < 0.05. Result(s): 598 patients were recruited, 322 in the referral cohort and 276 in the validation group. The average age was 67.0 years (Standard Deviation 14.59 years ) and 61.49 % male. Neutrophil lymphocyte ratio, NE-WZ, LYY, LY-Z, LY-WX, LY- WY, MO- WY, MO-Z were included in the multivariate analysis, and presented a significant association for the differential diagnosis of SARS-CoV-2 infection with AUC of 0.84 (95% CI 0.82-0.92) in the referral cohort and 0.77 (0.69-0.85) in the validation cohort Conclusion(s): Leukocyte differential and CPDs could be very useful in the differential diagnosis of SARS-CoV-2 pneumonia and lead to a cheap and early diagnosis of the disease.