Temporal changes in laboratory markers of survivors and non-survivors of adult inpatients with COVID-19

SARS-CoV-2 and dialysis: humoral response, clinical and laboratory impacts before vaccination

BACKGROUND

Patients with kidney disease on Hemodialysis (HD) are susceptible to Coronavirus Disease (COVID-19) due to multiple risk factors.

AIM

This study aims to report the prevalence of antibodies against SARS-CoV-2 among patients on hemodialysis before vaccination in Brazil and to compare with clinical, demographic, and laboratory data.

METHODS

Blood samples from 398 Chronic Kidney Disease (CKD) patients treated in three different private institutions in Rio de Janeiro State, Brazil were submitted to the total anti-SARS-CoV-2 testing. Kidney, liver, and hematological markers were also determined. Respiratory samples were tested by real-time PCR for SARS-CoV-2 RNA and positive samples were subjected to high-throughput sequencing on the MinION device.

RESULTS

Overall, anti-SARS-CoV-2 prevalence was 54.5 % (217/398) and two individuals had SARS-CoV-2 RNA with variant B.1.1. High anti-SARS-CoV-2 seroprevalence was found in male gender and those with hospital admission in the last 3-months before the inclusion in the study. Lower red blood cell count was observed in the anti-SARS-CoV-2 seropositive group. High levels of anti-SARS-CoV-2 were found in those who reported symptoms, had low levels of eosinophils and low hematocrit, and who practiced physical activity.

CONCLUSION

High prevalence of anti-SARS-CoV-2 was found in CKD patients before the universal immunization in Brazil suggesting that dialysis patients were highly exposed to SARS-CoV-2.

Platelet distribution width (PDW) as a significant correlate of COVID-19 infection severity and mortality

SARS-CoV-2 infection may cause a wide spectrum of symptoms, from asymptomatic, to mild respiratory symptoms and life-threatening sepsis. Among the clinical laboratory biomarkers analyzed during COVID-19 pandemic, platelet indices have raised great interest, due to the critical involvement of platelets in COVID-19-related thromboinflammation. Through an electronic literature search on MEDLINE, CINAHL, PubMed, EMBASE, Web of Science, and preprint servers we performed and updated a systematic review aimed at providing a detailed analysis of studies addressing the potential clinical utility of platelet distribution width, platelet distribution width (PDW), in laboratory medicine, exploring the possible association between increased PDW levels, disease severity, and mortality in COVID-19. Our systematic review revealed a wide heterogeneity of COVID-19 cohorts examined and a lack of homogenous expression of platelet indices. We found that 75 % of studies reported significantly elevated PDW values in COVID-19 infected cohorts compared to healthy/non-COVID-19 controls, and 40 % of studies reported that patients with severe COVID-19 showed increased PDW values than those with less-than-severe illness. Interestingly, 71.4 % of studies demonstrated significant increased PDW values in non survivors vs. survivors. Overall, these results suggest that platelets are critically involved as major players in the process of immunothrombosis in COVID-19, and platelet reactivity and morphofunctional alterations are mirrored by PDW, as indicator of platelet heterogeneity. Our results confirm that the use of PDW as prognostic biomarkers of COVID-19 sepsis still remains debated due to the limited number of studies to draw a conclusion, but new opportunities to investigate the crucial role of platelets in thrombo-inflammation are warranted.

Nucleated red blood cells are a late biomarker in predicting intensive care unit mortality in patients with COVID-19 acute respiratory distress syndrome: an observational cohort study

Background

Nucleated red blood cells (nRBC) are precursor cells of the erythropoiesis that are absent from the peripheral blood under physiological conditions. Their presence is associated with adverse outcomes in critically ill patients. This study aimed to evaluate the predictive value of nRBC on mortality in intensive care unit (ICU) patients with COVID-19 acute respiratory distress syndrome (ARDS).

Material and methods

This retrospective, observational cohort study analyzed data on 206 ICU patients diagnosed with COVID-19 ARDS between March 2020 and March 2022. The primary endpoint was ICU mortality, and secondary endpoints included ICU and hospital stay lengths, ventilation hours, and the time courses of disease severity scores and clinical and laboratory parameters.

Results

Among the included patients, 68.9% tested positive for nRBC at least once during their ICU stay. A maximum nRBC of 105 µl-1 had the highest accuracy in predicting ICU mortality (area under the curve of the receiver operating characteristic [AUCROC] 0.780, p < 0.001, sensitivity 69.0%, specificity 75.5%). Mortality was significantly higher among patients with nRBC >105 µl-1 than ≤105 µl-1 (86.5% vs. 51.3%, p = 0.008). Compared to patients negative for nRBC in their peripheral blood, those positive for nRBC required longer mechanical ventilation (127 [44 - 289] h vs. 517 [255 - 950] h, p < 0.001), ICU stays (12 [8 - 19] vs. 27 [13 - 51] d, p < 0.001), and hospital stays (19 [12 - 29] d vs. 31 [16 - 58] d, p < 0.001). Peak Sepsis-related Organ Failure Assessment (SOFA), Simplified Acute Physiology Score, PaO2/FiO2, interleukin-6, and procalcitonin values were reached before the peak nRBC level. However, the predictive performance of the SOFA (AUCROC 0.842, p < 0.001) was considerably improved when a maximum SOFA score >8 and nRBC >105 µl-1 were combined.

Discussion

nRBC predict ICU mortality and indicate disease severity among patients with COVID-19 ARDS, and they should be considered a clinical alarm signal for a worse outcome. nRBC are a late predictor of ICU mortality compared to other established clinical scoring systems and laboratory parameters but improve the prediction accuracy when combined with the SOFA score.

Temporal trends in laboratory parameters in survivors and non‑survivors of critical COVID‑19 illness and the effect of dexamethasone treatment

Although coronavirus disease 2019 (COVID-19)-induced changes in laboratory parameters in patients upon admission have been well-documented, information on their temporal changes is limited. The present study describes the laboratory trends and the effect of dexamethasone treatment on these parameters, in patients with COVID-19 in the intensive care unit (ICU). Routine laboratory parameters, namely white blood cell (WBC), neutrophil, lymphocyte and platelet (PLT) counts, fibrinogen, C-reactive protein (CRP), lactate dehydrogenase (LDH) and albumin concentrations, were recorded upon admission to the ICU and, thereafter, on days 3, 5, 10, 15 and 21; these values were compared between survivors and non-survivors, as well as between those who were treated with dexamethasone and those who were not. Among the 733 patients in the ICU, (mean age, 65±13 years; 68% males; ICU mortality rate 45%; 76% of patients treated with dexamethasone), the WBC and neutrophil counts were persistently high in all patients, without significant differences over the first 15 days. Initially, low lymphocyte counts exhibited increasing trends, but remained higher in survivors compared to non-survivors (P=0.01). The neutrophil-to-lymphocyte ratio (NLR) was persistently elevated in all patients, although it was significantly higher in non-survivors compared to survivors (P<0.001). The PLT count was initially increased in all patients, although it was significantly decreased in non-survivors over time. The fibrinogen and LDH values remained similarly elevated in all patients. However, the increased levels of CRP, which did not differ between patients upon admission, further increased in non-survivors compared to survivors after day 10 (P=0.001). Declining trends in albumin levels over time, overall, with a significant decrease in non-survivors compared to survivors, were observed. Dexamethasone treatment significantly affected the temporal progression of fibrinogen and CRP in survivors and that of NLR in non-survivors. On the whole, the present study demonstrates that patients in the ICU with COVID-19 present persistently abnormal laboratory findings and significant differences in laboratory trends of NLR, CRP, PLT and albumin, but not in WBC and neutrophil count, and fibrinogen and LDH levels, between survivors and non-survivors. The temporal progression of fibrinogen, CRP and NLR is affected by dexamethasone treatment.

Carbon dioxide and MAPK signalling: towards therapy for inflammation

Inflammation, although necessary to fight infections, becomes a threat when it exceeds the capability of the immune system to control it. In addition, inflammation is a cause and/or symptom of many different disorders, including metabolic, neurodegenerative, autoimmune and cardiovascular diseases. Comorbidities and advanced age are typical predictors of more severe cases of seasonal viral infection, with COVID-19 a clear example. The primary importance of mitogen-activated protein kinases (MAPKs) in the course of COVID-19 is evident in the mechanisms by which cells are infected with SARS-CoV-2; the cytokine storm that profoundly worsens a patient's condition; the pathogenesis of diseases, such as diabetes, obesity, and hypertension, that contribute to a worsened prognosis; and post-COVID-19 complications, such as brain fog and thrombosis. An increasing number of reports have revealed that MAPKs are regulated by carbon dioxide (CO2); hence, we reviewed the literature to identify associations between CO2 and MAPKs and possible therapeutic benefits resulting from the elevation of CO2 levels. CO2 regulates key processes leading to and resulting from inflammation, and the therapeutic effects of CO2 (or bicarbonate, HCO3-) have been documented in all of the abovementioned comorbidities and complications of COVID-19 in which MAPKs play roles. The overlapping MAPK and CO2 signalling pathways in the contexts of allergy, apoptosis and cell survival, pulmonary oedema (alveolar fluid resorption), and mechanical ventilation-induced responses in lungs and related to mitochondria are also discussed. Video Abstract.

Temporal evolution of laboratory characteristics in patients critically ill with COVID‑19 admitted to the intensive care unit (Review)

In the context of coronavirus disease 2019 (COVID-19), laboratory medicine has played a crucial role in both diagnosis and severity assessment. Although the importance of baseline laboratory findings has been extensively reported, data regarding their evolution over the clinical course are limited. The aim of the present narrative review was to provide the dynamic changes of the routine laboratory variables reported in patients with severe COVID-19 over the course of their critical illness. A search was made of the literature for articles providing data on the time-course of routine laboratory tests in patients with severe COVID-19 during their stay in the intensive care unit (ICU). White blood cell, neutrophil and lymphocyte counts, neutrophil to lymphocyte ratio, platelet counts, as well as D-dimer, fibrinogen, C-reactive protein, lactate dehydrogenase and serum albumin levels were selected as disease characteristics and routine laboratory parameters. A total of 25 research articles reporting dynamic trends in the aforementioned laboratory parameters over the clinical course of severe COVID-19 were identified. During the follow-up period provided by each study, the majority of the laboratory values remained persistently abnormal in both survivors and non-survivors. Furthermore, in the majority of studies, the temporal trends of laboratory values distinctly differentiated patients between survivors and non-survivors. In conclusion, there are distinct temporal trends in selected routine laboratory parameters between survivors and non-survivors with severe COVID-19 admitted to the ICU, indicating their importance in the prognosis of clinical outcome.

The bidirectional interaction of COVID-19 infections and lipoproteins

COVID-19 infections decrease total cholesterol, LDL-C, HDL-C, and apolipoprotein A-I, A-II, and B levels while triglyceride levels may be increased or inappropriately normal for the poor nutritional status. The degree of reduction in total cholesterol, LDL-C, HDL-C, and apolipoprotein A-I are predictive of mortality. With recovery lipid/lipoprotein levels return towards pre-infection levels and studies have even suggested an increased risk of dyslipidemia post-COVID-19 infection. The potential mechanisms for these changes in lipid and lipoprotein levels are discussed. Decreased HDL-C and apolipoprotein A-I levels measured many years prior to COVID-19 infections are associated with an increased risk of severe COVID-19 infections while LDL-C, apolipoprotein B, Lp (a), and triglyceride levels were not consistently associated with an increased risk. Finally, data suggest that omega-3-fatty acids and PCSK9 inhibitors may reduce the severity of COVID-19 infections. Thus, COVID-19 infections alter lipid/lipoprotein levels and HDL-C levels may affect the risk of developing COVID-19 infections.

Predicting omicron pneumonia severity and outcome: a single-center study in Hangzhou, China

Background

In December 2022, there was a large Omicron epidemic in Hangzhou, China. Many people were diagnosed with Omicron pneumonia with variable symptom severity and outcome. Computed tomography (CT) imaging has been proven to be an important tool for COVID-19 pneumonia screening and quantification. We hypothesized that CT-based machine learning algorithms can predict disease severity and outcome in Omicron pneumonia, and we compared its performance with the pneumonia severity index (PSI)-related clinical and biological features.

Methods

Our study included 238 patients with the Omicron variant who have been admitted to our hospital in China from 15 December 2022 to 16 January 2023 (the first wave after the dynamic zero-COVID strategy stopped). All patients had a positive real-time polymerase chain reaction (PCR) or lateral flow antigen test for SARS-CoV-2 after vaccination and no previous SARS-CoV-2 infections. We recorded patient baseline information pertaining to demographics, comorbid conditions, vital signs, and available laboratory data. All CT images were processed with a commercial artificial intelligence (AI) algorithm to obtain the volume and percentage of consolidation and infiltration related to Omicron pneumonia. The support vector machine (SVM) model was used to predict the disease severity and outcome.

Results

The receiver operating characteristic (ROC) area under the curve (AUC) of the machine learning classifier using PSI-related features was 0.85 (accuracy = 87.40%, p < 0.001) for predicting severity while that using CT-based features was only 0.70 (accuracy = 76.47%, p = 0.014). If combined, the AUC was not increased, showing 0.84 (accuracy = 84.03%, p < 0.001). Trained on outcome prediction, the classifier reached the AUC of 0.85 using PSI-related features (accuracy = 85.29%, p < 0.001), which was higher than using CT-based features (AUC = 0.67, accuracy = 75.21%, p < 0.001). If combined, the integrated model showed a slightly higher AUC of 0.86 (accuracy = 86.13%, p < 0.001). Oxygen saturation, IL-6, and CT infiltration showed great importance in both predicting severity and outcome.

Conclusion

Our study provided a comprehensive analysis and comparison between baseline chest CT and clinical assessment in disease severity and outcome prediction in Omicron pneumonia. The predictive model accurately predicts the severity and outcome of Omicron infection. Oxygen saturation, IL-6, and infiltration in chest CT were found to be important biomarkers. This approach has the potential to provide frontline physicians with an objective tool to manage Omicron patients more effectively in time-sensitive, stressful, and potentially resource-constrained environments.

Superimposed Pulmonary Tuberculosis (PTB) in a 26-Year-Old Female with No Underlying Co-Morbidities Recovering from COVID-19-Case Report

Tuberculosis before the COVID-19 pandemic is said to have killed more people globally than any other communicable disease and is ranked the 13th cause of death, according to the WHO. Tuberculosis also still remains highly endemic, especially in LIMCs with a high burden of people living with HIV/AIDS, in which it is the leading cause of mortality. Given the risk factors associated with COVID-19, the cross similarities between tuberculosis and COVID-19 symptoms, and the paucity of data on how both diseases impact each other, there is a need to generate more information on COVID-19-TB co-infection. In this case report, we present a young female patient of reproductive age with no underlying comorbidities recovering from COVID-19, who later presented with pulmonary tuberculosis. It describes the series of investigations performed and treatments given during the follow-up. There is a need for more surveillance for possible COVID-19-TB co-infection cases and further research to understand the impact of COVID-19 on tuberculosis and vice versa, especially in LMICs.

Machine learning prediction for COVID-19 disease severity at hospital admission

IMPORTANCE

Early prognostication of patients hospitalized with COVID-19 who may require mechanical ventilation and have worse outcomes within 30 days of admission is useful for delivering appropriate clinical care and optimizing resource allocation.

OBJECTIVE

To develop machine learning models to predict COVID-19 severity at the time of the hospital admission based on a single institution data.

DESIGN, SETTING, AND PARTICIPANTS

We established a retrospective cohort of patients with COVID-19 from University of Texas Southwestern Medical Center from May 2020 to March 2022. Easily accessible objective markers including basic laboratory variables and initial respiratory status were assessed using Random Forest's feature importance score to create a predictive risk score. Twenty-five significant variables were identified to be used in classification models. The best predictive models were selected with repeated tenfold cross-validation methods.

MAIN OUTCOMES AND MEASURES

Among patients with COVID-19 admitted to the hospital, severity was defined by 30-day mortality (30DM) rates and need for mechanical ventilation.

RESULTS

This was a large, single institution COVID-19 cohort including total of 1795 patients. The average age was 59.7 years old with diverse heterogeneity. 236 (13%) required mechanical ventilation and 156 patients (8.6%) died within 30 days of hospitalization. Predictive accuracy of each predictive model was validated with the 10-CV method. Random Forest classifier for 30DM model had 192 sub-trees, and obtained 0.72 sensitivity and 0.78 specificity, and 0.82 AUC. The model used to predict MV has 64 sub-trees and returned obtained 0.75 sensitivity and 0.75 specificity, and 0.81 AUC. Our scoring tool can be accessed at https://faculty.tamuc.edu/mmete/covid-risk.html .

CONCLUSIONS AND RELEVANCE

In this study, we developed a risk score based on objective variables of COVID-19 patients within six hours of admission to the hospital, therefore helping predict a patient's risk of developing critical illness secondary to COVID-19.

Impact of the seventh day nucleated red blood cell count on mortality in COVID-19 intensive care unit patients: A retrospective case-control study

Background

COVID-19 covers a broad clinical spectrum, threatening global health. Although several studies have investigated various prognostic biochemical and hematological parameters, they generally lack specificity and are insufficient for decision-making. Beyond the neonatal period, NRBCs (nucleated red blood cells) in peripheral blood is rare and often associated with malignant neoplasms, bone marrow diseases, and other severe disorders such as sepsis and hypoxia. Therefore, we investigated if NRBCs can predict mortality in hypoxic ICU (Intensive Care Unit) patients of COVID-19.

Methods

Seventy-one unvaccinated RT-PCR confirmed COVID-19 ICU patients was divided into those who survived (n=35, mean age=58) and died (n=36, mean age=75). Venous blood samples were collected in K3 EDTA tubes and analyzed on a Sysmex XN-1000 hematology analyzer with semiconductor laser flow cytometry and nucleic acid fluorescence staining method for NRBC analysis. NRBC numbers and percentages of the patients were compared on the first and seventh days of admission to the ICU. Results are reported as a proportion of NRBCs per 100 WBCs NRBCs/100 WBC (NRBC% and as absolute NRBC count (NRBC #, × 109/L).

Results

NRBC 7th-day count and % values were statistically higher in non-survival ones. The sensitivity for 7th day NRBC value <0.01 (negative) was 86.11%, the specificity was 48.57%, for <0.02; 75.00%, and 77.14%, for <0.03; 61.11%, and 94.60%.

Conclusions

In conclusion, our results indicate that NRBC elevation (>0.01) significantly predicts mortality in ICU hospitalized patients due to COVID-19. Worse, a high mortality rate is expected, especially with NRBC values of >0.03.

Immunity against Delta and Omicron variants elicited by homologous inactivated vaccine booster in kidney transplant recipients

Background

A third mRNA vaccine booster is recommended to improve immunity against SARS-CoV-2 in kidney transplant recipients (KTRs). However, the immunity against SARS-CoV-2 Ancestral strain and Delta and Omicron variants elicited by the third dose of inactivated booster vaccine in KTRs remains unknown.

Methods

The blood parameters related to blood cells count, hepatic function, kidney function, heart injury and immunity were explored clinically from laboratory examinations. SARS-CoV-2 specific antibody IgG titer was detected using an enzyme-linked immunosorbent assay. Cellular immunity was analyzed using interferon-γ enzyme-linked immunospot assay.

Results

The results showed that there were no severe adverse effects and apparent changes of clinical laboratory biomarkers in KTRs and healthy volunteers (HVs) after homologous inactivated vaccine booster. A third dose of inactivated vaccine booster significantly increased anti-Ancestral-spike-trimer-IgG and anti-Ancestral-receptor binding domain (RBD)-IgG titers in KTRs and HVs compared with the second vaccination. However, the anti-Delta-RBD-IgG and anti-Omicron-RBD-IgG titers were significantly lower than anti-Ancestral-RBD-IgG titer in KTRs and HVs after the third dose. Notably, only 25.6% (10/39) and 10.3% (4/39) of KTRs had seropositivity for anti-Delta-RBD-IgG and anti-Omicron-RBD-IgG after booster, which were significantly lower than HVs (anti-Delta-RBD-IgG: 100%, anti-Omicron-RBD-IgG: 77.8%). Ancestral strain nucleocapsid protein and spike specific T cell frequency after booster was not significantly increased in KTRs compared with the second dose, significantly lower than that in HVs. Moreover, 33.3% (12/36), 14.3% (3/21) and 14.3% (3/21) of KTRs were positive for the Ancestral strain and Delta and Omicron spike-specific T cells, which were significantly lower than HVs (Ancestral: 80.8%, Delta: 53.8%, and Omicron: 57.7%).

Conclusions

A third dose of inactivated booster vaccine may significantly increase humoral immunity against the Ancestral strain in KTRs, while humoral and cellular immunity against the Delta and Omicron variants were still poor in KTRs.

A proteome-scale map of the SARS-CoV-2-human contactome

Understanding the mechanisms of coronavirus disease 2019 (COVID-19) disease severity to efficiently design therapies for emerging virus variants remains an urgent challenge of the ongoing pandemic. Infection and immune reactions are mediated by direct contacts between viral molecules and the host proteome, and the vast majority of these virus-host contacts (the 'contactome') have not been identified. Here, we present a systematic contactome map of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) with the human host encompassing more than 200 binary virus-host and intraviral protein-protein interactions. We find that host proteins genetically associated with comorbidities of severe illness and long COVID are enriched in SARS-CoV-2 targeted network communities. Evaluating contactome-derived hypotheses, we demonstrate that viral NSP14 activates nuclear factor κB (NF-κB)-dependent transcription, even in the presence of cytokine signaling. Moreover, for several tested host proteins, genetic knock-down substantially reduces viral replication. Additionally, we show for USP25 that this effect is phenocopied by the small-molecule inhibitor AZ1. Our results connect viral proteins to human genetic architecture for COVID-19 severity and offer potential therapeutic targets.

Pyridostigmine reduces mortality of patients with severe SARS-CoV-2 infection: A phase 2/3 randomized controlled trial

Background:

Respiratory failure in severe coronavirus disease 2019 (COVID-19) is associated with a severe inflammatory response. Acetylcholine (ACh) reduces systemic inflammation in experimental bacterial and viral infections. Pyridostigmine increases the half-life of endogenous ACh, potentially reducing systemic inflammation. We aimed to determine if pyridostigmine decreases a composite outcome of invasive mechanical ventilation (IMV) and death in adult patients with severe COVID-19.

Methods:

We performed a double-blinded, placebo-controlled, phase 2/3 randomized controlled trial of oral pyridostigmine (60 mg/day) or placebo as add-on therapy in adult patients admitted due to confirmed severe COVID-19 not requiring IMV at enrollment. The primary outcome was a composite of IMV or death by day 28. Secondary outcomes included reduction of inflammatory markers and circulating cytokines, and 90-day mortality. Adverse events (AEs) related to study treatment were documented and described.

Results:

We recruited 188 participants (94 per group); 112 (59.6%) were men; the median (IQR) age was 52 (44–64) years. The study was terminated early due to a significant reduction in the primary outcome in the treatment arm and increased difficulty with recruitment. The primary outcome occurred in 22 (23.4%) participants in the placebo group vs. 11 (11.7%) in the pyridostigmine group (hazard ratio, 0.47, 95% confidence interval 0.24–0.9; P = 0.03). This effect was driven by a reduction in mortality (19 vs. 8 deaths, respectively).

Conclusion:

Our data indicate that adding pyridostigmine to standard care reduces mortality among patients hospitalized for severe COVID-19.

Predictor factors for non-invasive mechanical ventilation failure in severe COVID-19 patients in the intensive care unit: a single-center retrospective study

Background

During the COVID-19 pandemia, non-invasive mechanical ventilation (NIV) has been largely applied. Few data are available about predictors of NIV failure in critical COVID-19 patients admitted to ICU. The aim of this study is to analyze clinical and laboratory features able to predict non-invasive ventilation success in avoiding endotracheal intubation.

Methods

A retrospective observational study was performed in our COVID-19 ICU during a 6-month period. Demographic, clinical, laboratory, imaging, and outcome data were extracted from electronic and paper medical records and anonymously collected.

Results

Eighty-two severe COVID-19 patients were supported by NIV at ICU admission. The median PaO₂/FiO₂ ratio was 125 [98.5–177.7]. NIV failed in 44 cases (53%). Patients who experienced NIV failure had a higher Charlson Comorbidity Index (median value 4) compared to those who were dismissed without endotracheal intubation (median 2, p < 0.0001). At Cox regression analysis, the Charlson Comorbidity Index represented a predictive factor related to NIV failure. PaO₂/FiO₂, CPK, INR, and AT III at ICU admission showed a significant relationship with the outcome, when single variables were adjusted for the Charlson Comorbidity Index.

Conclusion

The Charlson Comorbidity Index may be helpful to stratify patients’ risk of NIV failure in a severe COVID-19 population; even if this study, retrospective design does not allow definitive conclusions.

Supplementary Information

The online version contains supplementary material available at 10.1186/s44158-022-00038-7.

The machine learning model based on trajectory analysis of ribonucleic acid test results predicts the necessity of quarantine in recurrently positive patients with SARS-CoV-2 infection

Background

SARS-CoV-2 patients re-experiencing positive nucleic acid test results after recovery is a concerning phenomenon. Current pandemic prevention strategy demands the quarantine of all recurrently positive patients. This study provided evidence on whether quarantine is required in those patients, and predictive algorithms to detect subjects with infectious possibility.

Methods

This observational study recruited recurrently positive patients who were admitted to our shelter hospital between May 12 and June 10, 2022. The demographic and epidemiologic data was collected, and nucleic acid tests were performed daily. virus isolation was done in randomly selected cases. The group-based trajectory model was developed based on the cycle threshold (Ct) value variations. Machine learning models were validated for prediction accuracy.

Results

Among the 494 subjects, 72.04% were asymptomatic, and 23.08% had a Ct value under 30 at recurrence. Two trajectories were identified with either rapid (92.24%) or delayed (7.76%) recovery of Ct values. The latter had significantly higher incidence of comorbidities; lower Ct value at recurrence; more persistent cough; and more frequently reported close contacts infection compared with those recovered rapidly. However, negative virus isolation was reported in all selected samples. Our predictive model can efficiently discriminate those with delayed Ct value recovery and infectious potentials.

Conclusion

Quarantine seems to be unnecessary for the majority of re-positive patients who may have low transmission risks. Our predictive algorithm can screen out the suspiciously infectious individuals for quarantine. These findings may assist the enaction of SARS-CoV-2 pandemic prevention strategies regarding recurrently positive patients in the future.

Analysis of Mortality in Unvaccinated Patients with COVID-19 and Cardiovascular Risk

COVID-19 is a contagious disease that has spread globally, killing millions of people around the world. In order to reduce the likelihood of in-hospital death due to COVID-19, it is reasonable to select a group of patients with a low probability of survival and to implement measures in advance to minimize the risk of death. One way to do this is to establish cut-off values for the most commonly performed blood laboratory tests, above or below which the likelihood of death increases significantly. The aim of the study was to determine the basic laboratory parameters among unvaccinated patients hospitalized for COVID-19 with concomitant cardiovascular disease, which are the predictors of in-hospital death. Out of 1234 patients, 446 people who met the specific inclusion criteria were enrolled in the study. The multivariate regression analysis has shown that the independent predictors of death are: troponin levels of at least 0.033 μg/L (OR = 2.04 [1.10; 3.79]), creatinine of at least 1.88 mg/dL (OR = 2.88 [1.57; 5.30]), D-dimers of at least 0.97 g/L (OR = 2.04 [1.02; 4.07]), and C-reactive protein minimum of 0.89 mg/L (OR = 2.28 [1.24; 4.18]).

High-density lipoproteins may play a crucial role in COVID-19

Background

Lipids play a central role in the virus life cycle and are a crucial target to develop antiviral therapeutics. Importantly, among the other lipoproteins, the ‘good cholesterol’ high-density lipoprotein (HDL) has been widely studied for its role in not only cardiovascular but several infectious diseases as well. Studies have suggested a role of serum lipids and lipoproteins including HDL, total cholesterol (TC), triglycerides (TG), and low-density lipoproteins (LDL) in several viral infections including COVID-19. This disease is currently a major public health problem and there is a need to explore the role of these host lipids/lipoproteins in virus pathogenesis.

Methodology

A total of 75 retrospective COVID-19 positive serum samples and 10 COVID-19 negative controls were studied for their lipid profiles including TC, HDL, LDL, and very-low-density lipoproteins (VLDL), and TG.

Results

Systematic literature search on dyslipidemia status in India shows that low HDL is the most common dyslipidemia. In this cohort, 65% (49) of COVID-19 patients had severely low HDL levels whereas 35% (26) had moderately low HDL and none had normal HDL levels. On the other hand, ~ 96% of samples had normal TC (72) and LDL (72) levels. VLDL and TG levels were also variable. In the controls, 100% of samples had moderately low HDL but none severely low HDL levels.

Conclusion

HDL likely plays a crucial role in COVID-19 infection and outcomes. The causal relationships between HDL levels and COVID-19 need to be studied extensively for an understanding of disease pathogenesis and management.

Supplementary Information

The online version contains supplementary material available at 10.1186/s12985-022-01865-4.

Infection Rate of Respiratory Viruses in the Pandemic SARS-CoV-2 Period Considering Symptomatic Patients: Two Years of Ongoing Observations

BACKGROUND

In the last two years, the SARS-CoV-2 pandemic has determined radical changes in human behaviors and lifestyles, with a drastic reduction in socialization due to physical distancing and self-isolation. These changes have also been reflected in the epidemiological patterns of common respiratory viruses. For this reason, early discrimination of respiratory viruses is important as new variants emerge.

METHODS

Nasopharyngeal swabs of 2554 patients, with clinically suspected Acute Respiratory Infections (ARIs) from October 2019 to November 2021, were collected to detect 1 or more of the 23 common respiratory pathogens, especially viruses, via BioFilmArray RP2.1plus, including SARS-CoV-2. Demographical characteristics and epidemiological analyses were performed as well as a laboratory features profile of positive patients.

RESULTS

An observational study on 2300 patients (254 patients were excluded because of missing data) including 1560 men and 760 women, median age of 64.5 years, was carried out. Considering the respiratory virus research request, most of the patients were admitted to the Emergency Medicine Department (41.2%, of patients), whereas 29.5% were admitted to the Infectious Diseases Department. The most frequently detected pathogens included SARS-CoV-2 (31.06%, 707/2300, from March 2020 to November 2021), InfA-B (1.86%, 43/2300), HCoV (2.17% 50/2300), and HSRV (1.65%, 38/2300). Interestingly, coinfection rates decreased dramatically in the SARS-CoV-2 pandemic period. The significative decrease in positive rate of SARS-CoV-2 was associated with the massive vaccination.

CONCLUSION

This study represents a dynamic picture of the epidemiological curve of common respiratory viruses during the two years of pandemic, with a disregarded trend for additional viruses. Our results showed that SARS-CoV-2 had a preferential tropism for the respiratory tract without co-existing with other viruses. The possible causes were attributable either to the use of masks, social isolation, or to specific respiratory receptors mostly available for this virus, external and internal lifestyle factors, vaccination campaigns, and emergence of new SARS-CoV-2 variants.

Bicarbonate concentration as a predictor of prognosis in moderately severe COVID-19 patients: A multicenter retrospective study

Background

Coronavirus disease 2019 (COVID-19) patients reportedly have high bicarbonate concentration. However, its relationship to the disease progression are obscure.

Methods

In this two-center retrospective study, we included COVID-19 patients with moderate severity between March 2020 and May 2021. We classified patients into three groups according to bicarbonate concentrations: high (>27 mEq/L), normal (21 to 27 mEq/L), and low (<21 mEq/L). The primary outcome was the time to clinical worsening defined by the requirement of intubation or death during 90 days. We evaluated high or low bicarbonate concentration during the clinical course related to the primary outcome using multivariable Cox proportional hazard models.

Results

Of the 60 participants (median age 72 years), 60% were men. Participants were classified into high (13 patients), normal (30 patients), and low (17 patients) groups. Clinical worsening occurred in 54% of patients in the high group, 23% in the normal group, and 65% in the low group. Both high and low groups were associated with a higher clinical worsening rate: HR, 3.02 (95% CI, 1.05 to 8.63) in the high group; 3.49 (95% CI: 1.33 to 9.12) in the low group.

Conclusion

Monitoring of bicarbonate concentrations may be useful to predict the prognosis.

C-Reactive Protein and Serum Albumin Ratio: A Feasible Prognostic Marker in Hospitalized Patients with COVID-19

(1) Background: C-reactive protein (CRP) and albumin are inflammatory markers. We analyzed the prognostic capacity of serum albumin (SA) and CRP for an outcome comprising mortality, length of stay, ICU admission, and non-invasive mechanical ventilation in hospitalized COVID-19 patients. (2) Methods: We conducted a retrospective cohort study based on the Spanish national SEMI-COVID-19 Registry. Two multivariate logistic models were adjusted for SA, CRP, and their combination. Training and testing samples were used to validate the models. (3) Results: The outcome was present in 41.1% of the 3471 participants, who had lower SA (mean [SD], 3.5 [0.6] g/dL vs. 3.8 [0.5] g/dL; p < 0.001) and higher CRP (108.9 [96.5] mg/L vs. 70.6 [70.3] mg/L; p < 0.001). In the adjusted multivariate model, both were associated with poorer evolution: SA, OR 0.674 (95% CI, 0.551−0.826; p < 0.001); CRP, OR 1.002 (95% CI, 1.001−1.004; p = 0.003). The CRP/SA model had a similar predictive capacity (honest AUC, 0.8135 [0.7865−0.8405]), with a continuously increasing risk and cutoff value of 25 showing the highest predictive capacity (OR, 1.470; 95% CI, 1.188−1.819; p < 0.001). (4) Conclusions: SA and CRP are good independent predictors of patients hospitalized with COVID-19. For the CRP/SA ratio value, 25 is the cutoff for poor clinical course.

Machine learning-based model for prediction of clinical deterioration in hospitalized patients by COVID 19

Despite the publication of great number of tools to aid decisions in COVID-19 patients, there is a lack of good instruments to predict clinical deterioration. COVID19-Osakidetza is a prospective cohort study recruiting COVID-19 patients. We collected information from baseline to discharge on: sociodemographic characteristics, comorbidities and associated medications, vital signs, treatment received and lab test results. Outcome was need for intensive ventilatory support (with at least standard high-flow oxygen face mask with a reservoir bag for at least 6 h and need for more intensive therapy afterwards or Optiflow high-flow nasal cannula or noninvasive or invasive mechanical ventilation) and/or admission to a critical care unit and/or death during hospitalization. We developed a Catboost model summarizing the findings using Shapley Additive Explanations. Performance of the model was assessed using area under the receiver operating characteristic and prediction recall curves (AUROC and AUPRC respectively) and calibrated using the Hosmer–Lemeshow test. Overall, 1568 patients were included in the derivation cohort and 956 in the (external) validation cohort. The percentages of patients who reached the composite endpoint were 23.3% vs 20% respectively. The strongest predictors of clinical deterioration were arterial blood oxygen pressure, followed by age, levels of several markers of inflammation (procalcitonin, LDH, CRP) and alterations in blood count and coagulation. Some medications, namely, ATC AO2 (antiacids) and N05 (neuroleptics) were also among the group of main predictors, together with C03 (diuretics). In the validation set, the CatBoost AUROC was 0.79, AUPRC 0.21 and Hosmer–Lemeshow test statistic 0.36. We present a machine learning-based prediction model with excellent performance properties to implement in EHRs. Our main goal was to predict progression to a score of 5 or higher on the WHO Clinical Progression Scale before patients required mechanical ventilation. Future steps are to externally validate the model in other settings and in a cohort from a different period and to apply the algorithm in clinical practice.

Registration: ClinicalTrials.gov Identifier: NCT04463706.

Mean Platelet Volume as a Predictor of COVID-19 Severity: A Prospective Cohort Study in the Highlands of Peru

Introduction: Although 80% of symptomatic individuals with COVID-19 develop mild forms, it is the severe (15%) and critical (5%) forms that have the greatest impact in the hospital setting. Recognizing markers that can predict severe forms is essential, especially in high-altitude populations. Methods: We conducted a prospective cohort study at 3200 masl (meters above sea level) in a city in Peru to determine if MPV (mean platelet volume) level is a predictor of COVID-19 severity. Patients with mild/moderate disease were enrolled and followed for 21 days or until the development of severe disease (primary outcome). A bivariate analysis was used to identify variables associated with severe disease. A ROC analysis determined the best MPV (mean platelet count) cut-off to predict COVID-19 severity, and then, a multiple regression analysis was performed. Results: 64 patients were enrolled. The median age was 48.5 years (IQT 39–64.5) and the proportion of women was 51.6%, the most frequent symptoms were chest pain (73%), fever (71%), and dyspnea (67%). The median time to develop a severe form from the onset of symptoms was 11 days (IQT 10.5–13). The most common radiographic phase on CT scan (computed tomography) was progressive (60.38%). We observed that an MPV of more than 10.15 fL in the first week of disease predicted severity regardless of age and sex at high altitudes. Conclusions: MPV in the first week of the disease may predict severity in patients diagnosed with COVID-19 at high altitudes; however, we need prospective studies with a larger population and at a different altitude, levels to confirm these findings.

Longitudinal Plasma Proteomics Analysis Reveals Novel Candidate Biomarkers in Acute COVID-19

The host response to COVID-19 pathophysiology over the first few days of infection remains largely unclear, especially the mechanisms in the blood compartment. We report on a longitudinal proteomic analysis of acute-phase COVID-19 patients, for which we used blood plasma, multiple reaction monitoring with internal standards, and data-independent acquisition. We measured samples on admission for 49 patients, of which 21 had additional samples on days 2, 4, 7, and 14 after admission. We also measured 30 externally obtained samples from healthy individuals for comparison at baseline. The 31 proteins differentiated in abundance between acute COVID-19 patients and healthy controls belonged to acute inflammatory response, complement activation, regulation of inflammatory response, and regulation of protein activation cascade. The longitudinal analysis showed distinct profiles revealing increased levels of multiple lipid-associated functions, a rapid decrease followed by recovery for complement activation, humoral immune response, and acute inflammatory response-related proteins, and level fluctuation in the regulation of smooth muscle cell proliferation, secretory mechanisms, and platelet degranulation. Three proteins were differentiated between survivors and nonsurvivors. Finally, increased levels of fructose-bisphosphate aldolase B were determined in patients with exposure to angiotensin receptor blockers versus decreased levels in those exposed to angiotensin-converting enzyme inhibitors. Data are available via ProteomeXchange PXD029437.

Plasma proteomic and metabolomic characterization of COVID-19 survivors 6 months after discharge

Coronavirus disease 2019 (COVID-19) has gained prominence as a global pandemic. Studies have suggested that systemic alterations persist in a considerable proportion of COVID-19 patients after hospital discharge. We used proteomic and metabolomic approaches to analyze plasma samples obtained from 30 healthy subjects and 54 COVID-19 survivors 6 months after discharge from the hospital, including 30 non-severe and 24 severe patients. Through this analysis, we identified 1019 proteins and 1091 metabolites. The differentially expressed proteins and metabolites were then subjected to Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway enrichment analysis. Among the patients evaluated, 41% of COVID-19 survivors reported at least one clinical symptom and 26.5% showed lung imaging abnormalities at 6 months after discharge. Plasma proteomics and metabolomics analysis showed that COVID-19 survivors differed from healthy control subjects in terms of the extracellular matrix, immune response, and hemostasis pathways. COVID-19 survivors also exhibited abnormal lipid metabolism, disordered immune response, and changes in pulmonary fibrosis-related proteins. COVID-19 survivors show persistent proteomic and metabolomic abnormalities 6 months after discharge from the hospital. Hence, the recovery period for COVID-19 survivors may be longer.

Can Peripheral Perfusion Index (PPI) Predict Disease Severity in COVID-19 Patients in the Emergency Department?

Background Coronavirus disease 2019 (COVID-19) causes significant mortality and morbidity in severe patients.

Objective In this study, we aimed to examine the relationship between COVID-19 disease severity and peripheral perfusion index (PPI).

Patients and Methods This prospective observational study included COVID-19 patients admitted to the tertiary hospital emergency department. Basal clinical and demographic data of the patients and PPI values at the time of admission were recorded. The patients were categorized to severe and nonsevere groups according to clinical severity. The relationship between COVID-19 severity and PPI was examined in comparison with the control group.

Results A total of 324 patients who met the inclusion criteria were analyzed. COVID-19 (+) was detected in 180 of these patients. Ninety-two of the COVID-19 (+) patients were in the severe group, and 88 of them were in the non severe group. Note that 164 COVID-19 (–) patients were in the control group. PPI average was found to be 1.44 ± 1.12 in the severe group, and 3.69 ± 2.51 in the nonsevere group. PPI average was found to be significantly lower in the severe group than the nonsevere group (p< 0.01) As for the nonsevere group and control group, PPI averages were found to be 3.69 ± 2.51 and3.54 ± 2.32, respectively, and a significant difference was determined between the two groups (p< 0.05). PPI COVID-19 severity predicting activity was calculated as area under the curve: 0.833, sensitivity:70.4%, andspecificity:71%(p = 0.025) at 2.2 cutoff value.

Conclusion The results of our study showed that PPI is an easy-to-apply and useful parameter in the emergency department in determining the severity of COVID-19 patients.

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.

Current and novel biomarkers of thrombotic risk in COVID-19: a Consensus Statement from the International COVID-19 Thrombosis Biomarkers Colloquium

Coronavirus disease 2019 (COVID-19) predisposes patients to thrombotic and thromboembolic events, owing to excessive inflammation, endothelial cell activation and injury, platelet activation and hypercoagulability. Patients with COVID-19 have a prothrombotic or thrombophilic state, with elevations in the levels of several biomarkers of thrombosis, which are associated with disease severity and prognosis. Although some biomarkers of COVID-19-associated coagulopathy, including high levels of fibrinogen and D-dimer, were recognized early during the pandemic, many new biomarkers of thrombotic risk in COVID-19 have emerged. In this Consensus Statement, we delineate the thrombotic signature of COVID-19 and present the latest biomarkers and platforms to assess the risk of thrombosis in these patients, including markers of platelet activation, platelet aggregation, endothelial cell activation or injury, coagulation and fibrinolysis as well as biomarkers of the newly recognized post-vaccine thrombosis with thrombocytopenia syndrome. We then make consensus recommendations for the clinical use of these biomarkers to inform prognosis, assess disease acuity, and predict thrombotic risk and in-hospital mortality. A thorough understanding of these biomarkers might aid risk stratification and prognostication, guide interventions and provide a platform for future research.

Are platelet volume indices of clinical use in COVID-19? A systematic review

Background

The incidence of thrombotic complications is high in COVID-19 patients with severe disease. As key regulators of thrombus formation, platelets likely play a crucial role as mediators of severe acute respiratory syndrome coronavirus 2 associated pathogenesis. Studies have reported that parameters reflecting platelet size, known as platelet volume indices (PVI), are raised in patients with thrombosis and can predict poor outcomes. This systematic review evaluates the potential for PVI to be used as a predictor of COVID-19 morbidity and mortality.

Methods

English and Chinese databases were searched electronically to identify studies reporting data on mean platelet volume, platelet distribution width or platelet-large cell ratio in COVID-19 patients. Included articles underwent a quality rating and descriptive narrative analysis.

Results

Thirty-two studies were included in the systematic review. The results show a general trend for PVI to be raised in severe COVID-19 patients and non-survivors, with 14 studies reporting significant differences of baseline PVI between severe and mild disease. Nonetheless, longitudinal studies showed varying PVI trends over the course of the disease and evidence for PVI to be associated with disease progression was limited. The quality rating of 12 studies was poor, 16 were rated fair and four were good. Most studies were retrospective in design, used small study populations and did not consider confounding factors that influence platelet volume. Studies also contained technical flaws in PVI measurement, limiting the reliability of the results.

Conclusion

The evidence on the clinical usefulness of PVI is greatly limited by the lack of prospective evaluation, together with technical problems in measuring PVI. Carefully designed prospective studies are warranted.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?RecordID=304305, identifier CRD42022304305.

Complete Blood Count Peculiarities in Pregnant SARS-CoV-2-Infected Patients at Term: A Cohort Study

Background: During viral outbreaks, pregnancy poses an increased risk of infection for women. Methods: In a prospective study, all patients admitted for delivery at term to Elena Doamna Obstetrics and Gynecology University Hospital in Iasi, Romania, between 1 April 2020 and 31 December 2020 were included. There were 457 patients, divided into two groups: group 1, SARS-CoV-2-positive patients (n = 46) and group 2, SARS-CoV-2-negative patients (n = 411). Among other tests, complete blood count was determined upon admittance, and the following values were studied: white blood cell count, lymphocytes, neutrophils, red blood cell count, hemoglobin, mean corpuscular hemoglobin concentration, mean corpuscular hemoglobin, mean corpuscular volume, red blood cell distribution width, hematocrit, platelet count, mean platelet volume, platelet distribution width, plateletcrit, and platelet large cell ratio. Results: in pregnant SARS-CoV-2-infected patients at term, there was a significant decrease in white blood cell, neutrophil, and lymphocyte count, and an increase in mean corpuscular hemoglobin concentration, compared to healthy pregnant women at term, although all still within normal limits. None of the other components of the complete blood count or fetal outcomes studied was significantly influenced by SARS-CoV-2 infection in pregnant patients at term.

Plasma Fibrinogen Independently Predicts Hypofibrinolysis in Severe COVID-19

High rates of thrombosis are present in patients with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Deeper insight into the prothrombotic state is essential to provide the best thromboprophylaxis care. Here, we aimed to explore associations among platelet indices, conventional hemostasis parameters, and viscoelastometry data. This pilot study included patients with severe COVID-19 (n = 21) and age-matched controls (n = 21). Each patient received 100 mg aspirin therapy at the time of blood sampling. Total platelet count, high immature platelet fraction (H-IPF), fibrinogen, D-dimer, Activated Partial Thromboplastin Time, von Willebrand factor antigen and von Willebrand factor ristocetin cofactor activity, plasminogen, and alpha2-antiplasmin were measured. To monitor the aspirin therapy, a platelet function test from hirudin anticoagulated whole blood was performed using the ASPI test by Multiplate analyser. High on-aspirin platelet reactivity (n = 8) was defined with an AUC > 40 cut-off value by ASPI tests. In addition, in vitro viscoelastometric tests were carried out using a ClotPro analyser in COVID-associated thromboembolic events (n = 8) (p = 0.071) nor the survival rate (p = 0.854) showed associations with high on-aspirin platelet reactivity status. The platelet count (p = 0.03), all subjects. COVID-19 patients presented with higher levels of inflammatory markers, compared with the controls, along with evidence of hypercoagulability by ClotPro. H-IPF (%) was significantly higher among non-survivors (n = 18) compared to survivors (p = 0.011), and a negative correlation (p = 0.002) was found between H-IPF and plasminogen level in the total population. The platelet count was significantly higher among patients with high on-aspirin platelet reactivity (p = 0.03). Neither the ECA-A10 (p = 0.008), and ECA-MCF (p = 0.016) were significantly higher, while the tPA-CFT (p < 0.001) was significantly lower among patients with high on-aspirin platelet reactivity. However, only fibrinogen proved to be an independent predictor of hypofibrinolysis in severe COVID-19 patients. In conclusion, a faster developing, more solid clot formation was observed in aspirin ‘non-responder’ COVID-19 patients. Therefore, an individually tailored thromboprophylaxis is needed to prevent thrombotic complications, particularly in the hypofibrinolytic cluster.

Long-Chain Acylcholines Link Butyrylcholinesterase to Regulation of Non-neuronal Cholinergic Signaling

Acylcholines are comprised of an acyl chain esterified to a choline moiety; acetylcholine is the best-characterized member of this class, functioning as a neurotransmitter in the central and peripheral nervous systems as well as an inhibitor of cytokine production by macrophages and other innate immune cells. Acylcholines are metabolized by a class of cholinesterases, including acetylcholinesterase (a specific regulator of acetylcholine levels) and butyrylcholinesterase (BChE, an enigmatic enzyme whose function has not been resolved by genetic knockout models). BChE provides reserve capacity to hydrolyze acetylcholine, but its importance is arguable given acetylcholinesterase is the most catalytically efficient enzyme characterized to date. While known to be substrates of BChE in vitro, endogenous production of long-chain acylcholines is a recent discovery enabled by untargeted metabolomics. Compared to acetylcholine, long-chain acylcholines show greater stability in circulation with homeostatic levels-dictated by synthesis and clearance-suggested to impact cholinergic receptor sensitivity of acetylcholine with varying levels of antagonism. Acylcholines then provide a link between BChE and non-neuronal acetylcholine signaling, filling a gap in understanding around how imbalances between acylcholines and BChE could modulate inflammatory disease, such as the "cytokine storm" identified in severe COVID-19. Areas for further research, development, and clinical testing are outlined.

High-density lipoprotein cholesterol: A marker of COVID-19 infection severity?

BACKGROUND AND AIMS

To systematically address all the relevant evidence of the association between high-density lipoprotein cholesterol (HDL-C) and COVID-19 infection.

METHODS

We searched PubMed, PubMed Central and medRxiv databases (up to May 2021) for studies related to HDL-C and COVID-19 infection. A qualitative synthesis of published prospective and retrospective studies for the role of low HDL-C levels on COVID-19 infection severity was performed.

RESULTS

Thirty-three studies (6 prospective, 27 retrospective) including 11,918 COVID-19 patients were eligible for the systematic review. Twelve studies compared HDL-C levels on admission in COVID-19 patients with healthy controls. In these 12 studies, COVID-19 patients had significantly lower HDL-C levels on admission compared with that of healthy controls. Twenty-eight studies observed the HDL-C levels among COVID-19 diagnosed patients, to establish the role of low HDL-C values in the prognosis of the infection. Twenty-four studies showed a correlation between low HDL-C levels with disease severity, while only 4 studies showed no association.

CONCLUSIONS

Low HDL-C levels should be added in the list of the others well-known risk factors for COVID-19 severity.

Immature platelets as a biomarker for disease severity and mortality in COVID-19 patients

COVID-19, caused by SARS-CoV-2, is a contagious life-threatening viral disease that has killed more than three million people worldwide to date. Attempts have been made to identify biomarker(s) to stratify disease severity and improve treatment and resource allocation. Patients with SARS-COV-2 infection manifest with a higher inflammatory response and platelet hyperreactivity; this raises the question of the role of thrombopoiesis in COVID-19 infection. Immature platelet fraction (IPF, %) and immature platelet counts (IPC, ×109 /l) can be used to assess thrombopoiesis. This study investigates whether the level of thrombopoiesis correlates with COVID-19 severity. A large cohort of 678 well-characterized COVID-19 patients was analyzed, including 658 (97%) hospitalized and 139 (21%) admitted to the intensive care unit (ICU). Elevated percentage IPF at presentation was predictive of length of hospitalization (P < 0·01) and ICU admission (P < 0·05). Additionally, percentage IPF at the peak was significantly higher among ICU patients than non-ICU patients (6·9 ± 5·1 vs 5·3 ± 8·4, P < 0·01) and among deceased patients than recovered patients (7·9 ± 6·3 vs 5·4 ± 7·8, P < 0·01). Furthermore, IPC at the peak was significantly higher among ICU patients than non-ICU patients (18·5 ± 16·2 vs. 13·2 ± 8·3, P < 0·05) and among patients on a ventilator than those not (22·1 ± 20·1 vs.13·4 ± 8·4, P < 0·05). Our study demonstrated that elevated initial and peak values of percentage IPF and IPC might serve as prognostic biomarkers for COVID-19 progression to severe conditions.

Increased Mortality Associated with Hypermagnesemia in Severe COVID-19 Illness

Background

Although electrolyte abnormalities are common among patients with COVID-19, very little has been reported on magnesium homeostasis in these patients. Here we report the incidence of hypermagnesemia, and its association with outcomes among patients admitted with COVID-19.

Methods

We retrospectively identified all patients with a positive test result for SARS-CoV-2 who were admitted to a large quaternary care center in New York City in spring 2020. Details of the patients' demographics and hospital course were obtained retrospectively from medical records. Patients were defined as having hypermagnesemia if their median magnesium over the course of their hospitalization was >2.4 mg/dl.

Results

A total of 1685 patients hospitalized with COVID-19 had their magnesium levels checked during their hospitalization, and were included in the final study cohort, among whom 355 (21%) had hypermagnesemia. Patients who were hypermagnesemic had a higher incidence of shock requiring pressors (35% vs 27%, P<0.01), respiratory failure requiring mechanical ventilation (28% vs 21%, P=0.01), AKI (65% vs 50%, P<0.001), and AKI severe enough to require renal replacement therapy (18% vs 5%, P<0.001). In an adjusted multivariable model, hypermagnesemia was observed more commonly with increasing age, male sex, AKI requiring RRT, hyperkalemia, and higher CPK. Survival probability at 30 days was 34% for the patients with hypermagnesemia, compared with 65% for patients without hypermagnesemia. An adjusted multivariable time to event analysis identified an increased risk of mortality with older age, need for vasopressors, higher C-reactive protein levels, and hypermagnesemia (HR, 2.03; 95% CI, 1.63 to 2.54, P<0.001).

Conclusions

In conclusion, we identified an association between hypermagnesemia among patients hospitalized with COVID-19 and increased mortality. Although the exact mechanism of this relationship remains unclear, hypermagnesemia potentially represents increased cell turnover and higher severity of illness, which is frequently associated with more severe forms of AKI.

The Role of High-Density Lipoprotein in COVID-19

The current Coronavirus disease 2019 (COVID-19) pandemic has become a global challenge. Managing a large number of acutely ill patients in a short time, whilst reducing the fatality rate and dealing with complications, brings unique difficulties. The most striking pathophysiological features of patients with severe COVID-19 are dysregulated immune responses and abnormal coagulation function, which can result in multiple-organ failure and death. Normally metabolized high-density lipoprotein (HDL) performs several functions, including reverse cholesterol transport, direct binding to lipopolysaccharide (LPS) to neutralize LPS activity, regulation of inflammatory response, anti-thrombotic effects, antioxidant, and anti-apoptotic properties. Clinical data shows that significantly decreased HDL levels in patients with COVID-19 are correlated with both disease severity and mortality. However, the role of HDL in COVID-19 and its specific mechanism remain unclear. In this analysis, we review current evidence mainly in the following areas: firstly, the pathophysiological characteristics of COVID-19, secondly, the pleiotropic properties of HDL, thirdly, the changes and clinical significance of HDL in COVID-19, and fourthly the prospect of HDL-targeting therapy in COVID-19 to clarify the role of HDL in the pathogenesis of COVID-19 and discuss the potential of HDL therapy in COVID-19.

Serum triglyceride levels and related factors as prognostic indicators in COVID-19 patients: A retrospective study

The role of triglycerides (TG) in coronavirus disease (COVID‐19) is controversial. The objective of this study was to explore the relationship between TG levels and prognosis in COVID‐19 patients and investigate the factors that affect TG. COVID‐19 patients were divided into normal or high TG level groups. Their demographic data, medical history, signs and symptoms, laboratory results, and final clinical results were analyzed retrospectively. A total of 174 patients were included. TG level was 1.6 (interquartile range [IQR]: 1.1‒2.1) mmol/L for all patients; 2.2 (IQR: 1.8‒2.7) mmol/L and 1.1 (IQR: 1.0–1.3) mmol/L in the high TG and control groups, respectively. Overall, 29 patients (16.7%) died during hospitalization, including 19 (23.1%) in the high TG group and 10 (11.5%) in the control group (absolute survival difference, 2.5% (95% confidence interval [CI], 1.2%‐5.1%), log‐rank χ² = 5.7, and p = .017). Serum ferritin, C‐reactive protein (CRP), lactate dehydrogenase (LDH), and interleukin‐10 (IL‐10) levels were significantly higher in the high TG group compared to the control group. Pearson correlation analysis showed that TG was positively correlated with fasting blood glucose, leukocyte, serum ferritin, LDH, CRP, and IL‐10 levels. Multiple regression showed that serum ferritin and IL‐10 levels affected the TG level (R² = .095). The TG level in COVID‐19 patients is correlated to serum ferritin and IL‐10 levels, which reflects the activation of macrophages. It is suggested that COVID‐19 patients be monitored for elevated TG as both a prognostic indicator and potential therapeutic target for COVID‐19.

Evidence of the pathogenic HERV-W envelope expression in T lymphocytes in association with the respiratory outcome of COVID-19 patients

Background

Despite an impressive effort in clinical research, no standard therapeutic approach for coronavirus disease 2019 (COVID-19) patients has been established, highlighting the need to identify early biomarkers for predicting disease progression and new therapeutic interventions for patient management. The present study aimed to evaluate the involvement of the human endogenous retrovirus -W envelope (HERV-W ENV) in severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection considering recent findings that HERVs are activated in response to infectious agents and lead to various immunopathological effects. We analysed HERV-W ENV expression in blood cells of COVID-19 patients in correlation with clinical characteristics and have discussed its potential role in the outcome of the disease.

Methods

We analysed HERV-W ENV expression in blood samples of COVID-19 patients and healthy donors by flow cytometry and quantitative reverse transcriptase PCR analysis, and evaluated its correlation with clinical signs, inflammatory markers, cytokine expression, and disease progression.

Findings

HERV-W ENV was highly expressed in the leukocytes of COVID-19 patients but not in those of healthy donors. Its expression correlated with the markers of T-cell differentiation and exhaustion and blood cytokine levels. The percentage of HERV-W ENV-positive lymphocytes correlated with inflammatory markers and pneumonia severity in COVID-19 patients. Notably, HERV-W ENV expression reflects the respiratory outcome of patients during hospitalization.

Interpretation

Given the known immuno- and neuro-pathogenicity of HERV-W ENV protein, it could promote certain pathogenic features of COVID-19 and therefore serve as a biomarker to predict clinical progression of disease and open to further studies for therapeutic intervention.

Funding

Information available at the end of the manuscript.