From acute SARS-CoV-2 infection to pulmonary hypertension.

As the world progressively recovers from the acute stages of the coronavirus disease 2019 (COVID-19) pandemic, we may be facing new challenges regarding the long-term consequences of COVID-19. Accumulating evidence suggests that pulmonary vascular thickening may be specifically associated with COVID-19, implying a potential tropism of severe acute respiratory syndrome coronavirus 2 (SARS-COV-2) virus for the pulmonary vasculature. Genetic alterations that may influence the severity of COVID-19 are similar to genetic drivers of pulmonary arterial hypertension. The pathobiology of the COVID-19-induced pulmonary vasculopathy shares many features (such as medial hypertrophy and smooth muscle cell proliferation) with that of pulmonary arterial hypertension. In addition, the presence of microthrombi in the lung vessels of individuals with COVID-19 during the acute phase, may predispose these subjects to the development of chronic thromboembolic pulmonary hypertension. These similarities raise the intriguing question of whether pulmonary hypertension (PH) may be a long-term sequela of SARS-COV-2 infection. Accumulating evidence indeed support the notion that SARS-COV-2 infection is indeed a risk factor for persistent pulmonary vascular defects and subsequent PH development, and this could become a major public health issue in the future given the large number of individuals infected by SARS-COV-2 worldwide. Long-term studies assessing the risk of developing chronic pulmonary vascular lesions following COVID-19 infection is of great interest for both basic and clinical research and may inform on the best long-term management of survivors.

Hematological ratios in coronavirus disease 2019 patients with and without invasive mechanical ventilation.

Patients with the most severe form of coronavirus disease 2019 (COVID-19) often require invasive ventilation. Determining the best moment to intubate a COVID-19 patient is complex decision and can result in important consequences for the patient. Therefore, markers that could aid in clinical decision-making such as hematological indices are highly useful. These markers are easy to calculate, do not generate extra costs for the laboratory, and are readily implemented in routine practice. Thus, this study aimed to investigate differences in the ratios calculated from the hemogram between patients with and without the need for invasive mechanical ventilation (IMV) and a control group. This was an observational retrospective analysis of 212 patients with COVID-19 that were hospitalized between April 1, 2020 and March 31, 2021 who were stratified as IMV (n = 129) or did not require invasive mechanical ventilation (NIMV) (n = 83). A control group of 198 healthy individuals was also included. From the first hemogram of each patient performed after admission, the neutrophil-to-lymphocyte ratio (NLR), the derived NLR (d-NLR), the lymphocyte-to-monocyte ratio, the platelet-to-lymphocyte ratio, the neutrophil-to-platelet ratio (NPR), and the systemic immune-inflammation index (SII) were calculated. All hematological ratios exhibited significant differences between the control group and COVID-19 patients. NLR, d-NLR, SII, and NPR were higher in the IMV group than they were in the NIMV group. The hematological indices addressed in this study demonstrated high potential for use as auxiliaries in clinical decision-making regarding the need for IMV.

Hemograms and serial hemogram-derived ratios in survivors and non-survivors of COVID-19 in Campinas, Brazil.

Introduction: The hemogram and hemogram-derivative ratios (HDRs) are becoming markers of the severity and mortality of COVID-19. We evaluated the hemograms and serial weekly HDRs [neutrophil-lymphocyte ratio (NLR), monocyte-lymphocyte ratio (MLR), platelet-lymphocyte ratio (PLR), neutrophil-platelet ratio (NPR) and systemic immune-inflammatory index (SII)] in the survivors and non-survivors of COVID-19. Methods: We retrospectively reviewed the medical notes and serial hemograms of real-time reverse-transcription polymerase chain reaction (RT-PCR)-confirmed COVID-19 adults hospitalized from April 2020 to March 2021 from the time of diagnosis to the 3rd week of diagnosis. Results: Of the 320 adults, 257 (80.3%) were survivors and had a lower mean age than the non-survivors (57.73 vs. 64.65 years, p < 0.001). At diagnosis, the non-survivors had lower lymphocyte (p = 0.002) and basophil (p = 0.049) counts and the hematocrit showed a p-value (Is this what you meant???) of 0.021); higher NLR (p < 0.001), PLR (p = 0.047), NPR (p = 0.022) and SII (p = 0.022). Using general linear models, the survivors and non-survivors showed significant variations with weekly lymphocyte count (p < 0.001), neutrophil count (p = 0.005), NLR (p = 0.009), MLR (p = 0.010) and PLR (p = 0.035). All HDRs remained higher in the non-survivors in the 2nd week and 3rd week of diagnosis and the HDRs were higher in the intubated patients than in the non-intubated patients. The NLR and SII were more efficient predictors of mortality in COVID-19 patients. Conclusions: This study shows that serial lymphocyte and neutrophil counts, NLR, PLR, MLR, NPR and SII could serve as good and easily accessible markers of severity and predictors of outcomes in COVID-19 patients and should be used for the monitoring of treatment response.

Host cell entry mediators implicated in the cellular tropism of SARS­CoV­2, the pathophysiology of COVID­19 and the identification of microRNAs that can modulate the expression of these mediators (Review).

The pathophysiology of coronavirus disease 2019 (COVID­19) is mainly dependent on the underlying mechanisms that mediate the entry of severe acute respiratory syndrome coronavirus 2 (SARS­CoV­2) into the host cells of the various human tissues/organs. Recent studies have indicated a higher order of complexity of the mechanisms of infectivity, given that there is a wide­repertoire of possible cell entry mediators that appear to co­localise in a cell­ and tissue­specific manner. The present study provides an overview of the 'canonical' SARS­CoV­2 mediators, namely angiotensin converting enzyme 2, transmembrane protease serine 2 and 4, and neuropilin­1, expanding on the involvement of novel candidates, including glucose­regulated protein 78, basigin, kidney injury molecule­1, metabotropic glutamate receptor subtype 2, ADAM metallopeptidase domain 17 (also termed tumour necrosis factor­α convertase) and Toll­like receptor 4. Furthermore, emerging data indicate that changes in microRNA (miRNA/miR) expression levels in patients with COVID­19 are suggestive of further complexity in the regulation of these viral mediators. An in silico analysis revealed 160 candidate miRNAs with potential strong binding capacity in the aforementioned genes. Future studies should concentrate on elucidating the association between the cellular tropism of the SARS­CoV­2 cell entry mediators and the mechanisms through which they might affect the clinical outcome. Finally, the clinical utility as a biomarker or therapeutic target of miRNAs in the context of COVID­19 warrants further investigation.

Risk Score for Predicting In-Hospital Mortality in COVID-19 (RIM Score).

Infection by SARS-CoV2 has devastating consequences on health care systems. It is a global health priority to identify patients at risk of fatal outcomes. 1955 patients admitted to HM-Hospitales from 1 March to 10 June 2020 due to COVID-19, were were divided into two groups, 1310 belonged to the training cohort and 645 to validation cohort. Four different models were generated to predict in-hospital mortality. Following variables were included: age, sex, oxygen saturation, level of C-reactive-protein, neutrophil-to-platelet-ratio (NPR), neutrophil-to-lymphocyte-ratio (NLR) and the rate of changes of both hemogram ratios (VNLR and VNPR) during the first week after admission. The accuracy of the models in predicting in-hospital mortality were evaluated using the area under the receiver-operator-characteristic curve (AUC). AUC for models including NLR and NPR performed similarly in both cohorts: NLR 0.873 (95% CI: 0.849-0.898), NPR 0.875 (95% CI: 0.851-0.899) in training cohort and NLR 0.856 (95% CI: 0.818-0.895), NPR 0.863 (95% CI: 0.826-0.901) in validation cohort. AUC was 0.885 (95% CI: 0.885-0.919) for VNLR and 0.891 (95% CI: 0.861-0.922) for VNPR in the validation cohort. According to our results, models are useful in predicting in-hospital mortality risk due to COVID-19. The RIM Score proposed is a simple, widely available tool that can help identify patients at risk of fatal outcomes.