EVALUATION OF THE RELATIONSHIP OF MPV, RDW AND PVI PARAMETERS WITH DISEASE SEVERITY IN COVID-19 PATIENTS

Correlation of Sysmex-XN9000 and CellaVision Advanced RBC software on anisocytosis

OBJECTIVE

This study aims to evaluate the consistency of heterogeneity degree of erythrocyte volume parameters between the blood automated analyzer Sysmex-XN9000 and the advanced red blood cell software CellaVisionDI-60.

METHOD

500 blood samples of volunteers were analyzed by Sysmex-XN9000 and CellaVision-DI60. The sensitivity, specificity, positive predictive value, negative predictive value, false positive rate, and false negative rate were evaluated. The consistency of all parameters was tested.

RESULT

Taking the standard RBC group as the control group, the RBC parameters of the macrocytic and the microcytic group were compared. There was a statistical difference between the groups. ROC curve analysis showed that the best cutoff value of microcytic and of macrocytic affecting MCV were 4.1% and 5.7%, respectively. The best cutoff value of anisocytosis was 15.0%. The correlation coefficient between anisocytosis and red blood cell distribution width (RDW-CV) was 0.756. The sensitivity, specificity, positive predictive value and coincidence rate of anisocytosis were high. The false negative rate was 10.0%, and the false positive rate was 7.4%.

CONCLUSION

All parameters of the degree of heterogeneity have good accuracy and consistency in the two instruments. Anisocytosis is with higher coincidence rate and positive predictive value. MIC and MAC have a good prediction on the increase or decrease of MCV. Although advanced RBC software's false negative and false positive rates are high, the red blood cell image system is more intuitive and time-saving in observing cells. Consequently, CellaVision-DI60 is suggested to combine with XN-9000 for judging the anisocytosis in daily work comprehensively.

Variant-derived SARS-CoV-2 spike protein does not directly cause platelet activation or hypercoagulability

Thrombosis has been associated with severity and mortality in COVID-19. SARS-CoV-2 infects the host via its spike protein. However, direct effects of spike proteins from SARS-CoV-2 variants on platelet activity and coagulability have not been examined. An ethically approved ex vivo study was performed under a preplanned power analysis. Venous blood was collected from 6 healthy subjects who gave prior written consent. The samples were divided into 5 groups: without spike proteins (group N) and with spike proteins derived from alpha, beta, gamma, and delta SARS-CoV-2 variants (groups A, B, C, and D, respectively). Platelet aggregability, P-selectin expression, platelet-associated complement-1 (PAC-1) binding, platelet count, and mean platelet volume (MPV) were measured in all 5 groups, and thromboelastography (TEG) parameters were measured in groups N and D. The % change in each parameter in groups A to D was calculated relative to the value in group N. Data were analyzed by Friedman test, except for TEG parameters, which were evaluated by Wilcoxon matched pairs test. P < 0.05 was considered significant. This study included 6 participants based on a power analysis. There were no significant differences in platelet aggregability under stimulation with adenosine diphosphate 5 µg/ml, collagen 0.2 or 0.5 µg/ml, and Ser-Phe-Leu-Leu-Arg-Asn-amide trifluoroacetate salt (SFLLRN) 0.5 or 1 µM in groups A-D compared to group N. There were also no significant differences in P-selectin expression and PAC-1 binding under basal conditions or SFLLRN stimulation, and no significant differences in platelet count, MPV and TEG parameters. Platelet hyperactivity and blood hypercoagulability have been reported in COVID-19 patients, but spike proteins at 5 µg/ml from SARS-CoV-2 variants (alpha, beta, gamma, delta) did not directly cause these effects in an ex vivo study. This study was approved by the Ethics Committee of Kyoto University Hospital (R0978-1) on March 06, 2020.

Parameters and Morphological Changes of Erythrocytes and Platelets of COVID-19 Subjects: A Longitudinal Cohort Study

Purpose

Information about dynamic changes occurring in the parameters and morphology of erythrocytes and platelets during the coronavirus disease 2019 (COVID-19) infection and convalescence is scarce. To explore potential associations between dynamic erythrocyte and platelet parameters, morphological changes, and the course or severity of the disease is essential.

Patients and Methods

From January 17th, 2020, to February 20th, 2022, we followed up on 35 patients with non-severe and 11 patients with severe COVID-19 following their discharge. We collected clinical features, dynamic complete blood count (CBC), and peripheral blood smears (PBS) and analyzed parameter and morphological changes of erythrocytes and platelets depending on the course or severity of the disease. The course of the disease included four periods, namely onset (T1), discharge (T2), 1-year follow-up (T3), and 2-year follow-up (T4).

Results

Red blood cell (RBC) counts and hemoglobin were the lowest in T2, followed by T1, and lower in T1 and T2 than in T3 and T4. Inversely, the red blood cell distribution width (RDW) was the highest in T2, followed by T1, and higher than in T3 and T4. Compared to non-severe patients, the platelet of severe patients was lower in T1 and T2. In contrast, the mean platelet volume (MPV) and platelet distribution width (PDW) tended to be higher in severe patients. Similarly, anisocytosis was more common in peripheral blood smears at early stages and in severe patients. Finally, large platelets were more common in severe patients.

Conclusion

Anisocytosis of erythrocytes and large platelets are found in patients with severe COVID-19, these changes may help primary hospitals to identify patients with a high risk of severe COVID-19 at an early stage.

Early predicting 30-day mortality in sepsis in MIMIC-III by an artificial neural networks model

OBJECTIVE

Early identifying sepsis patients who had higher risk of poor prognosis was extremely important. The aim of this study was to develop an artificial neural networks (ANN) model for early predicting clinical outcomes in sepsis.

METHODS

This study was a retrospective design. Sepsis patients from the Medical Information Mart for Intensive Care-III (MIMIC-III) database were enrolled. A predictive model for predicting 30-day morality in sepsis was performed based on the ANN approach.

RESULTS

A total of 2874 patients with sepsis were included and 30-day mortality was 29.8%. The study population was categorized into the training set (n = 1698) and validation set (n = 1176) based on the ratio of 6:4. 11 variables which showed significant differences between survivor group and nonsurvivor group in training set were selected for constructing the ANN model. In training set, the predictive performance based on the area under the receiver-operating characteristic curve (AUC) were 0.873 for ANN model, 0.720 for logistic regression, 0.629 for APACHEII score and 0.619 for SOFA score. In validation set, the AUCs of ANN, logistic regression, APAHCEII score, and SOFA score were 0.811, 0.752, 0.607, and 0.628, respectively.

CONCLUSION

An ANN model for predicting 30-day mortality in sepsis was performed. Our predictive model can be beneficial for early detection of patients with higher risk of poor prognosis.

PENTRAXIN 3 LEVELS CORRELATE WELL WITH DISEASE SEVERITY AT ADMISSION IN COVID-19 PATIENTS

Pentraxin 3 (PTX3), a long pentraxin, is not only released from dendritic cells and neutrophils but also from epithelial and endothelial cells such as alveolar epithelium. Severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2) initially activates the innate immune system, causing a complex immune response. Clinical and experimental studies suggest that PTX3, a locally and systemically secreted marker, can be used as a predictor of the severity and mortality in respiratory infections. In the current study, serum PTX3 levels in patients hospitalized with COVID-19 were found to be significantly increased at admission and showed significant association with the disease severity.

COVID-19, Cation Dysmetabolism, Sialic Acid, CD147, ACE2, Viroporins, Hepcidin and Ferroptosis: A Possible Unifying Hypothesis

Background: iron and calcium dysmetabolism, with hyperferritinemia, hypoferremia, hypocalcemia and anemia have been documented in the majority of COVID-19 patients at later/worse stages. Furthermore, complementary to ACE2, both sialic acid (SA) molecules and CD147 proved relevant host receptors for SARS-CoV-2 entry, which explains the viral attack to multiple types of cells, including erythrocytes, endothelium and neural tissue. Several authors advocated that cell ferroptosis may be the core and final cell degenerative mechanism.

Methods: a literature research was performed in several scientific search engines, such as PubMed Central, Cochrane Library, Chemical Abstract Service. More than 500 articles were retrieved until mid-December 2021, to highlight the available evidence about the investigated issues.

Results: based on COVID-19 literature data, we have highlighted a few pathophysiological mechanisms, associated with virus-based cation dysmetabolism, multi-organ attack, mitochondria degeneration and ferroptosis. Our suggested elucidated pathological sequence is: a) spike protein subunit S1 docking with sialylated membrane glycoproteins/receptors (ACE2, CD147), and S2 subunit fusion with the lipid layer; b) cell membrane morpho-functional changes due to the consequent electro-chemical variations and viroporin action, which induce an altered ion channel function and intracellular cation accumulation; c) additional intracellular iron concentration due to a deregulated hepcidin-ferroportin axis, with higher hepcidin levels. Viral invasion may also affect erythrocytes/erythroid precursors, endothelial cells and macrophages, through SA and CD147 receptors, with relative hemoglobin and iron/calcium dysmetabolism. AB0 blood group, hemochromatosis, or environmental elements may represent possible factors which affect individual susceptibility to COVID-19.    

Conclusions: our literature analysis confirms the combined role of SA molecules, ACE2, CD147, viroporins and hepcidin in determining the cation dysmetabolism and final ferroptosis in the cells infected by SARS-CoV-2. The altered ion channels and electrochemical gradients of the cell membrane have a pivotal role in the virus entry and cell dysmetabolism, with subsequent multi-organ immune-inflammatory degeneration and erythrocyte/hemoglobin alterations.