COVID-19 Pneumonia Research Articles

Detection of Covid-19 and chest pneumonia based on X-ray images using Deep-Transfer Learning

Numerous people have died as a result of the coronavirus outbreak in 2019 (COVID-19), which also affected millions of others worldwide. The infection spreads quickly. Therefore, technology that enables quick virus detection will offer healthcare professionals much-needed assistance. This study aims to identify COVID-19 disease from X-ray images of healthy and infected people with pneumonia by using a modified VGG16 model. The proposed model achieved better results than previous studies presented with an accuracy of 99.13%, a recall of 99%, and a precision of 98.70%.

Deep learning based COVID and Pneumonia detection using chest X-ray

<p class="Abstract">Since the outbreak, the novel coronavirus (COVID-19) has infected more than 180 million people and has taken a toll of 3.91 million lives globally as of June 2021. This virus causes symptoms like fever, cold, and fatigue, and can develop into Pneumonia which can be detected using chest X-rays (CXRs). Therefore, early detection of COVID-19 can help get early medical attention. However, a sudden rise in the number of cases in many countries caused by COVID waves increases the burden on their testing facilities. As a result, they sometimes fail to perform enough testing to contain the spread. This work proposes a deep learning model to detect COVID-19 and Pneumonia based on CXRs. The dataset for our COVID model contains a total of 3,400 CXRs images of COVID-19 patients and 3,400 normal CXRs. The dataset for our Pneumonia model contains 1,300 CXR images of Pneumonia patients and 1,300 normal CXRs. We use convolutional neural network provided by TensorFlow to build our model, which gave 94.17% and 93.55% accuracy for COVID model and Pneumonia model, respectively. Finally, we deployed our model on the web and added a web tracker, which gives us the cases, deaths, and recoveries state-wise and nationwide.</p>

Pneumomediastinum in COVID-19: Risk factors and outcomes from a multicentre case-control study

BackgroundAn increased incidence of pneumomediastinum has been observed among patients hospitalized with coronavirus disease 2019 (COVID-19) pneumonia. The study aimed to identify risk factors for COVID-19-associated pneumomediastinum and investigate the impact of pneumomediastinum on clinical outcomes. MethodsIn this multicentre retrospective case-control study, we included consecutive patients with COVID-19 pneumonia and pneumomediastinum hospitalized from March 2020 to July 2020 at ten centres; then, we identified a similarly sized control group of consecutive patients hospitalized with COVID-19 pneumonia and respiratory failure who did not develop pneumomediastinum during the same period. Clinical, laboratory, and radiological characteristics, as well as respiratory support and outcomes, were collected and compared between the two groups. Risk factors of pneumomediastinum were assessed by multivariable logistic analysis. ResultsOverall 139 patients with pneumomediastinum and 153 without pneumomediastinum were analysed. Lung involvement ≥75 %, consolidations, body mass index (BMI) < 22 kg/m2, C-reactive protein (CRP) > 150 mg/L, D-dimer >3000 ng/mL FEUs, and smoking exposure >20 pack-year were all independently correlated with the occurrence of pneumomediastinum. Patients with pneumomediastinum had a longer hospital stay (mean ± SD 31.2 ± 20.2 days vs 19.6 ± 14.2, p < 0.001), higher intubation rate (73/139, 52.5 % vs 27/153, 17.6 %, p < 0.001), and in-hospital mortality (68/139, 48.9 % vs 36/153, 23.5 %, p < 0.001) compared to controls. ConclusionsExtensive lung parenchyma involvement, consolidations, low BMI, high inflammatory markers, and tobacco exposure are associated with a greater risk of pneumomediastinum in COVID-19 pneumonia. This complication significantly worsens the outcomes.

Ventilatory efficiency in long-term dyspnoeic patients following COVID-19 pneumonia

BackgroundLong COVID is defined as persistency of symptoms, such as exertional dyspnea, twelve weeks after recovery from SARS-CoV-2 infection. ObjectivesTo investigate ventilatory efficiency by the use of cardiopulmonary exercise testing (CPET) in patients with exertional dyspnea despite normal basal spirometry after 18 (T18) and 36 months (T36) from COVID-19 pneumonia. MethodsOne hundred patients with moderate-critical COVID-19 were prospectively enrolled in our Long COVID program. Medical history, physical examination and lung high-resolution computed tomography (HRCT) were obtained at hospitalization (T0), 3 (T3) and 15 months (T15). All HRCTs were revised using a semi-quantitative CT severity score (CSS). Pulmonary function tests were obtained at T3 and T15. CPET was performed in a subset of patients with residual dyspnea (mMRC ≥ 1), at T18 and at T36. ResultsRemarkably, at CPET, ventilatory efficiency was reduced both at T18 (V’E/V’CO2 slope = 31.4±3.9 SD) and T36 (V’E/V’CO2 slope = 31.28±3.70 SD). Furthermore, we identified positive correlations between V’E/V’CO2 slope at T18 and T36 and both percentage of involvement and CSS at HRCT at T0, T3 and T15. Also, negative linear correlations were found between V’E/V’CO2 slope at T18 and T36 and DLCO at T3 and T15. ConclusionsAt eighteen months from COVID-19 pneumonia, 20 % of subjects still complains of exertional dyspnea. At CPET this may be explained by persistently reduced ventilatory efficiency, possibly related to the degree of lung parenchymal involvement in the acute phase of infection, likely reflecting a damage in the pulmonary circulation.

Post COVID-19 pneumonia lung fibrosis: A worrisome sequelae in surviving patients.

Post COVID-19 pneumonia lung fibrosis: A worrisome sequelae in surviving patients.

FOT Technique Applied for Monitoring of COVID-19 Pneumonia Reveals Small Airways Involvement.

The fact that some SARS-CoV-2 pneumonia patients benefit from changing body position, and some from continuous positive airways pressure (CPAP), indicates the functional character of hypoxia. We hypothesize that such effects could be explained by the closure of small airways. To prove the hypothesis, we evaluated the patency of small airways in 30 oxygen-dependent, spontaneously breathing patients with SARS-CoV-2 pneumonia during their hospital stay using the FOT method and then compared the results with data obtained three months later. During the acute period, total resistance (R5) and peripheral resistance (R5-20) rose above the upper limit of normal (ULN) in 28% and 50% of all patients, respectively. Reactance indices X5, AX and Fres exceeded ULN in 55%, 68% and 66% of cases. Significant correlations were observed between PaO2/FiO2, the time spent in the hospital and R5, X5, AX and Fres. After 3 months, 18 patients were re-examined. During the hospital stay, 11 of them had risen above the upper limit of normal (ULN), for both resistance (R5-20) and reactance (X5, AX) values. Three months later, ULN for R5-20 was exceeded in only four individuals, but ULN for X5 and AX was exceeded in five individuals. Lung function examination revealed a combined restrictive/obstructive ventilatory failure and reduced CO transfer factor. We interpret these changes as lung tissue remodeling due to the process of fibrosis. We conclude that during acute period of SARS-CoV-2 pneumonia, dilated pulmonary blood vessels and parenchymal oedema induce functional closure of small airways, which in turn induce atelectasis with pulmonary right-to-left shunting, followed by the resulting hypoxemia.

Artificial Intelligence-guided High-resolution Computer Tomography Assessment in Bilateral COVID-19 Pneumonia of Standalone Ayurveda Successful Case Study

Artificial Intelligence-guided High-resolution Computer Tomography Assessment in Bilateral COVID-19 Pneumonia of Standalone Ayurveda Successful Case Study

Rhabdomyolysis – A Rare Presentation of COVID-19

Abstract COVID-19 pandemic presented a great global health-care challenge. The spectrum of illness comprises pulmonary and extrapulmonary manifestations including hepatic, renal, and neurological complications. Our patient is a young male who presented with fever, severe myalgia, and respiratory distress. After a thorough clinical examination and laboratory investigations, the diagnosis of COVID-19 pneumonia and associated rhabdomyolysis was made. He developed acute renal failure for which intravenous hydration was given. He also required renal replacement therapy. He was successfully treated and discharged with complete remission of symptoms. We did a literature search for similar cases and have discussed the potential mechanisms implied for these complications.

Differential Anxiety Responses in Acute Myocardial Infarction vs. COVID-19 Pneumonia Patients.

Background and Objectives: Amidst the COVID-19 pandemic, concerns about the psychological impact of disease-related anxiety on public health have risen. This study aims to compare general and death anxiety levels between acute coronary artery syndrome and COVID-19 pneumonia patients. Materials and Methods: A cross-sectional study of 132 individuals, including acute myocardial infarction (MI), COVID-19 pneumonia patients, and healthy volunteers from Trakya University Hospital (Turkey), was analyzed. Validated scales like the Beck Anxiety Inventory (BAI), Coronavirus Anxiety Scale Short Form, and Thorson-Powell Death Anxiety Scale (TPDAS) were employed. Demographic data such as age, gender, income levels, employment status, presence of a close relative with COVID-19, and whether participants followed COVID-19-related news were collected and compared across groups with significance level of 0.05 set for all analyses. Results: Among 41 COVID-19, 41 MI, and 50 healthy subjects, the pneumonia group showed highest COVID-19 anxiety (p = 0.01) and BAI scores (p = 0.008). Both COVID-19 and MI patients had significantly higher BAI and TPDAS scores compared to healthy controls (p < 0.001). Factors like female gender (p = 0.004), low education (p = 0.003), current employment (p = 0.008), and low income (p = 0.002) correlated with higher BAI scores. Low income (p = 0.001) and COVID-19 news exposure (p = 0.002) correlated with higher TPDAS scores. Males and married patients had lower anxiety scores (p = 0.008). High income, education, and employment reduced anxiety levels (p = 0.008). TPDAS scores decreased with higher income (p = 0.001), but increased in the MI group (p = 0.002) with COVID-19 news exposure. The multivariate linear regression analysis found that MI and COVID-19 pneumonia were associated with TPDAS; female gender, university education, and COVID-19 pneumonia with the Beck scale; and COVID-19 pneumonia with anxiety scores on the COVID-19 Anxiety scale. Conclusions: This research showcases differing anxiety patterns between illnesses such as MI and COVID-19 pneumonia amidst the pandemic, emphasizing the amplifying influence of media coverage on death-related anxieties. It underscores the imperative of targeted interventions and socioeconomic considerations in managing psychological consequences and formulating responsive public health strategies.

COVID Pneumonia Severity Detection of Chest CT-Scan Images based on Robust Semantic Segmentation

Image segmentation has steadily grown especially for clinical usage and disease recognition in radiological research. This procedure, aimed at acquiring quantitative measurements, strives to distinguish regions or objects of interest from adjacent body tissues. To be more specific, it entails measuring the area and volume of segmented structures to extract more refined diagnostic information. The main hurdles encountered by segmentation algorithms originate from challenges like variations in intensity, artifacts, and the close juxtaposition of diverse soft tissues in the grayscale. In this paper, a robust semantic segmentation is proposed to specify the infected regions of lung images and consider the severity degree of the pneumonia caused by COVID-19 disease. The proposed model provides an accurate diagnosis of the chest CT scan image with satisfied performance with 93% accuracy and the second most important metric which is the Jaccard Index with 0.746±0.09 shows higher prediction performance than most existing systems in the literature.

In-hospital survival of critically ill COVID-19 patients treated with glucocorticoids: a multicenter real-world data study

The COVID-19 pandemic has posed a major challenge to healthcare systems globally. Millions of people have been infected, and millions of deaths have been reported worldwide. Glucocorticoids have attracted worldwide attention for their potential efficacy in the treatment of COVID-19. Various glucocorticoids with different dosages and treatment durations have been studied in patients with different severities, with a suitable dosage and treatment duration not yet defined. This study aimed to investigate whether in-hospital survival differs between critically ill patients treated with low-dose glucocorticoids, high-dose glucocorticoids or no glucocorticoids. All critically ill patients admitted to the intensive care unit of the Charité Hospital—Universitätsmedizin Berlin between February 2020 and December 2021 with COVID-19 pneumonia receiving supplemental oxygen were eligible to participate in this multicenter real-world data study. Patients were retrospectively assigned to one of three groups: the high corticosteroid dose (HighC) group (receiving 6 mg parenteral dexamethasone or an equivalent corticosteroid dosage for ten days), the low corticosteroid dose (LowC) group (receiving less than 6 mg parenteral dexamethasone or an equivalent corticosteroid dosage for ten days), or the no corticosteroid (NoC) group. Overall survival and risk effects were compared among groups within the total observation period, as well as at 35 days after the onset of COVID-19 symptoms. Adjusted multivariable Cox proportional hazard regression analysis was performed to compare the risk of death between the treatment groups. Out of 1561 critically ill COVID-19 patients, 1014 were included in the baseline analysis. In the survival study, 1009 patients were assigned to the NoC (n = 346), HighC (n = 552), or LowC group (n = 111). The baseline characteristics were balanced between groups, except for age, BMI, APACHE II score, SOFA and SAPS II. While the 35-day survival did not show any differences, a landmark analysis of the patients surviving beyond 35 days revealed differences between groups. The restricted mean survival time was 112 days in the LowC group [95% CI: 97 – 128], 133 days in the HighC group [95% CI: 124 – 141] and 144 days in the NoC group [95% CI: 121 – 167]. The multivariable-adjusted Cox proportional hazard analysis indicated that, regardless of age, sex, health status or invasive oxygenation, a low-dose treatment increased the hazard of death of critically ill COVID-19 patients by a factor of 2.09 ([95% CI: 0.99, 4.4], p = 0.05) and a high-dose corticosteroid treatment increased the risk by a factor of 1.07 ([95% CI: 0.53, 2.15], p = 0.85) compared to no treatment with glucocorticoids. The analysis reveals that corticosteroid treatment does not influence the survival of critically ill COVID-19 patients in the intensive care unit within 35 days. Our evaluations further suggest that regardless of ventilation status, the decision-making process for administering corticosteroid therapy should account for the individual severity of the illness.

Fog-based deep learning framework for real-time pandemic screening in smart cities from multi-site tomographies

The quick proliferation of pandemic diseases has been imposing many concerns on the international health infrastructure. To combat pandemic diseases in smart cities, Artificial Intelligence of Things (AIoT) technology, based on the integration of artificial intelligence (AI) with the Internet of Things (IoT), is commonly used to promote efficient control and diagnosis during the outbreak, thereby minimizing possible losses. However, the presence of multi-source institutional data remains one of the major challenges hindering the practical usage of AIoT solutions for pandemic disease diagnosis. This paper presents a novel framework that utilizes multi-site data fusion to boost the accurateness of pandemic disease diagnosis. In particular, we focus on a case study of COVID-19 lesion segmentation, a crucial task for understanding disease progression and optimizing treatment strategies. In this study, we propose a novel multi-decoder segmentation network for efficient segmentation of infections from cross-domain CT scans in smart cities. The multi-decoder segmentation network leverages data from heterogeneous domains and utilizes strong learning representations to accurately segment infections. Performance evaluation of the multi-decoder segmentation network was conducted on three publicly accessible datasets, demonstrating robust results with an average dice score of 89.9% and an average surface dice of 86.87%. To address scalability and latency issues associated with centralized cloud systems, fog computing (FC) emerges as a viable solution. FC brings resources closer to the operator, offering low latency and energy-efficient data management and processing. In this context, we propose a unique FC technique called PANDFOG to deploy the multi-decoder segmentation network on edge nodes for practical and clinical applications of automated COVID-19 pneumonia analysis. The results of this study highlight the efficacy of the multi-decoder segmentation network in accurately segmenting infections from cross-domain CT scans. Moreover, the proposed PANDFOG system demonstrates the practical deployment of the multi-decoder segmentation network on edge nodes, providing real-time access to COVID-19 segmentation findings for improved patient monitoring and clinical decision-making.

Use of defibrotide in COVID-19 pneumonia: comparison of a phase II study and a matched real-world cohort control.

The coronavirus disease 2019 (COVID-19) pandemic led to an unprecedented burden on healthcare systems around the world and a severe global socioeconomic crisis, with more than 750 million confirmed cases and at least 7 million deaths reported by December 31, 2023. The DEFI-VID19 study (clinicaltrials gov. Identifier: NCT04335201), a phase II, single-arm, multicenter, open-label trial was designed in mid-2020 to assess the safety and efficacy of defibrotide in treating patients with COVID-19 pneumonia. Defibrotide was administered at a dose of 25 mg/kg intravenously, divided into four daily doses over a planned 14-day period for patients with COVID-19 pneumonia receiving non-invasive ventilation. The primary endpoint was respiratory failure-free survival (RFFS). Overall survival (OS), the number of post-recovery days, and adverse events were the secondary endpoints. For comparison, a contemporaneous control cohort receiving standard of care only was retrospectively selected by applying the eligibility criteria of the DEFI-VID19 trial. To adjust for the imbalance between the two cohorts in terms of baseline variable distributions, an outcome regression analysis was conducted. In adjusted analysis, patients receiving defibrotide reported a trend towards higher RFFS (hazard ratio [HR]=0.71; 95% confidence interval [CI]: 0.34-1.29; P=0.138) and OS (HR=0.78; 95% CI: 0.33-1.53; P=0.248]) and showed a significantly increased number of post-recovery days (difference in means =3.61; 95% CI: 0.97-6.26; P=0.0037). Despite concomitant thromboprophylaxis with low molecular weight heparin, the safety profile of defibrotide proved to be favorable. Taken together, our findings suggest that defibrotide may represent a valuable addition to the COVID-19 therapeutic options.

Gender Differences in Psycho-Emotional State and Quality of Life in Patients 3 Months after Pneumonia COVID-19

Background: there is the different susceptibility to viral infections, course of the disease, reaction to stress and quality of life (QoL) in men and women. The aim of this study is to identify the psycho-emotional state and QoL characteristics of women and men in 3 months after COVID-19 pneumonia. Patients and methods: during the cross-sectional study within the framework of the prospective cohort study “Prospective follow-up of patients after COVID-19-associated pneumonia”, 133 patients (54.1% women; mean age 54 ± 9 years) were examined by experimental psychological method (PHQ-9, GAD-7, PSS-10, SF-36). The mental health was assessed by a psychiatrist, the cardiovascular system — by a cardiologist. Results: women were more likely to have psychoemotional disorders (p = 0.011) and symptoms of depression (p = 0.030). All indicators of QoL were higher among men. In women, a decrease in the scores on the vital activity scale increased the frequency of detecting signs of anxiety, depression (p = 0.004) and stress, an increase in the values on the social functioning scale showed an association with severe lung damage in the acute period of the disease (p = 0.024). In men, a decrease in pain intensity indicators is associated with the detection of mental disorders (p = 0.039) and the appointment of psychotropic therapy (p = 0.005). The severity of stress was observed with a decrease in values on all scales of the QoL questionnaire. The older age of the examined was determined with a decrease in the indicators of the physical component of health (p = 0.006) and other physical aspects of QoL. Conclusion: the mental state differs significantly in men and women 3 months after COVID-19 pneumonia. QoL of both sexes is associated with stress. In women, QoL depends on the mental state, in men depends on physical well-being. The results obtained can be applied in the planning of rehabilitation measures taking into account gender characteristics.

Pulmonary aspergillosis after COVID-19, a case report

COVID-19 is an infectious disease that spreads worldwide, can progress rapidly, affect individuals of all ages, and cause death, especially in the elderly and people with chronic diseases. It has predisposed a relatively high number of patients to acute respiratory distress syndrome, and co-infections are a frequent complication, especially during prolonged hospital stays. Bacterial or viral co-infections with SARS-CoV-2 have been reported in many studies, but knowledge of Aspergillus co-infection in patients with COVID-19 is limited. This study presents a 57-year-old male patient with COVID-19 who had had no lung disease before COVID-19 pneumonia. However, after COVID-19 pneumonia with sequels and treatments that include corticosteroids and IL-6 receptor antagonists, an invasive pulmonary aspergillus (IPA) cavity occurred immediately. In addition to the fact that COVID-19 infection progresses with destructive parenchymal damage and sequelae, the effectiveness of treatment is limited, and treatment-related side effects and complications can be examined. Therefore, clinical and radiological follow-up of patients whose symptoms persist after infection is essential.

Prevalence and risk factors of cytomegalovirus reactivation in critically Ill patients with COVID-19 pneumonia.

In critically ill patients with COVID-19, secondary infections are potentially life-threatening complications. This study aimed to determine the prevalence, clinical characteristics, and risk factors of CMV reactivation among critically ill immunocompetent patients with COVID-19 pneumonia. A retrospective cohort study was conducted among adult patients who were admitted to ICU and screened for quantitative real-time PCR for CMV viral load in a tertiary-care hospital during the third wave of the COVID-19 outbreak in Thailand. Cox regression models were used to identify significant risk factors for developing CMV reactivation. A total of 185 patients were studied; 133 patients (71.9%) in the non-CMV group and 52 patients (28.1%) in the CMV group. Of all, the mean age was 64.7±13.3 years and 101 patients (54.6%) were males. The CMV group had received a significantly higher median cumulative dose of corticosteroids than the non-CMV group (301 vs 177 mg of dexamethasone, p<0.001). Other modalities of treatments for COVID-19 including anti-viral drugs, anti-cytokine drugs and hemoperfusion were not different between the two groups (p>0.05). The 90-day mortality rate for all patients was 29.1%, with a significant difference between the CMV group and the non-CMV group (42.3% vs. 24.1%, p = 0.014). Median length of stay was longer in the CMV group than non-CMV group (43 vs 24 days, p<0.001). The CMV group has detectable CMV DNA load with a median [IQR] of 4,977 [1,365-14,742] IU/mL and 24,570 [3,703-106,642] in plasma and bronchoalveolar fluid, respectively. In multivariate analysis, only a cumulative corticosteroids dose of dexamethasone ≥250 mg (HR = 2.042; 95%CI, 1.130-3.688; p = 0.018) was associated with developing CMV reactivation. In critically ill COVID-19 patients, CMV reactivation is frequent and a high cumulative corticosteroids dose is a significant risk factor for CMV reactivation, which is associated with poor outcomes. Further prospective studies are warranted to determine optimal management.

Whole blood transcriptome signature predicts severe forms of COVID-19: Results from the COVIDeF cohort study

COVID-19 is associated with heterogeneous outcome. Early identification of a severe progression of the disease is essential to properly manage the patients and improve their outcome. Biomarkers reflecting an increased inflammatory response, as well as individual features including advanced age, male gender, and pre-existing comorbidities, are risk factors of severe COVID-19. Yet, these features show limited accuracy for outcome prediction. The aim was to evaluate the prognostic value of whole blood transcriptome at an early stage of the disease. Blood transcriptome of patients with mild pneumonia was profiled. Patients with subsequent severe COVID-19 were compared to those with favourable outcome, and a molecular predictor based on gene expression was built. Unsupervised classification discriminated patients who would later develop a COVID-19-related severe pneumonia. The corresponding gene expression signature reflected the immune response to the viral infection dominated by a prominent type I interferon, with IFI27 among the most over-expressed genes. A 48-genes transcriptome signature predicting the risk of severe COVID-19 was built on a training cohort, then validated on an external independent cohort, showing an accuracy of 81% for predicting severe outcome. These results identify an early transcriptome signature of severe COVID-19 pneumonia, with a possible relevance to improve COVID-19 patient management.

Identifying Mortality Predictors in Hospitalized COVID-19 Patients: Insights from a Single-Center Retrospective Study at a University Hospital.

The pandemic instigated by the SARS-CoV-2 virus has led to over 7 million deaths globally, primarily attributable to viral pneumonia. Identifying fundamental markers associated with an elevated risk of mortality can aid in the early identification of patients prone to disease progression to a severe state, enabling prompt intervention. This was a single-center, retrospective study. In this study, we examined 299 patients admitted to the Department of Infectology and Travel Medicine in Košice, Slovakia, with PCR-confirmed COVID-19 pneumonia. Patients were monitored from 1 January 2021 to 31 March 2021, with the endpoint being discharge from the hospital or death. All patient-related data were retrospectively collected from medical records. This study identified several risk factors significantly associated with an increased risk of mortality, including the requirement of HFNO (p < 0.001), age over 60 years (p < 0.001), Ne/Ly values of >6 (p < 0.001), as well as certain lymphocyte subtypes-CD4+ < 0.2 × 109/L (p = 0.035), CD8+ < 0.2 × 109/L (p < 0.001), and CD19+ < 0.1 × 109/L (p < 0.001)-alongside selected biochemical inflammatory markers-IL-6 > 50 ng/L (p < 0.001) and lactate > 3 mmol/L (p < 0.001). We confirmed that the mentioned risk factors were significantly associated with the death of patients from viral pneumonia in the hospital.

Vascular endothelial-derived SPARCL1 exacerbates viral pneumonia through pro-inflammatory macrophage activation

Inflammation induced by lung infection is a double-edged sword, moderating both anti-viral and immune pathogenesis effects; the mechanism of the latter is not fully understood. Previous studies suggest the vasculature is involved in tissue injury. Here, we report that expression of Sparcl1, a secreted matricellular protein, is upregulated in pulmonary capillary endothelial cells (EC) during influenza-induced lung injury. Endothelial overexpression of SPARCL1 promotes detrimental lung inflammation, with SPARCL1 inducing ‘M1-like’ macrophages and related pro-inflammatory cytokines, while SPARCL1 deletion alleviates these effects. Mechanistically, SPARCL1 functions through TLR4 on macrophages in vitro, while TLR4 inhibition in vivo ameliorates excessive inflammation caused by endothelial Sparcl1 overexpression. Finally, SPARCL1 expression is increased in lung ECs from COVID-19 patients when compared with healthy donors, while fatal COVID-19 correlates with higher circulating SPARCL1 protein levels in the plasma. Our results thus implicate SPARCL1 as a potential prognosis biomarker for deadly COVID-19 pneumonia and as a therapeutic target for taming hyperinflammation in pneumonia.

Electrolyte disturbances in patients hospitalized for COVID-19 infection: An observational study.

There are multiple mechanisms by which The Coronavirus-19 (COVID-19) infection can cause electrolyte abnormalities, which may not be the case for bacterial causes of pneumonia. This study aimed to assess the differences in electrolyte levels between patients suffering from COVID-19 and bacterial pneumonia. This is an original, retrospective study. Two cohorts of hospitalized patients were included, 1 suffering from COVID-19 and the other from bacterial pneumonia. Their day 1 and day 3 levels of sodium, potassium, magnesium, and phosphorus, as well as their outcomes, were extracted from the charts. Statistical analysis was subsequently performed. Mean admission levels of sodium, potassium, phosphorus, and magnesium were 135.64 ± 6.13, 4.38 ± 0.69, 3.53 ± 0.69, and 2.03 ± 0.51, respectively. The mean day 3 levels of these electrolytes were 138.3 ± 5.06, 4.18 ± 0.59, 3.578 ± 0.59, and 2.11 ± 0.64, respectively. Patients suffering from bacterial pneumonia were significantly older (N = 219, mean = 64.88 ± 15.99) than patients with COVID-19 pneumonia (N = 240, mean = 57.63 ± 17.87). Bacterial pneumonia group had significantly higher serum potassium (N = 211, mean = 4.51 ± 0.76), and magnesium (N = 115, mean = 2.12 ± 0.60) levels compared to COVID-19 group (N = 227, mean = 4.254 ± 0.60 for potassium and N = 118, mean = 1.933 ± 0.38 for magnesium). Only magnesium was significantly higher among day 3 electrolytes in the bacterial pneumonia group. No significant association between electrolyte levels and outcomes was seen. We found that COVID-19 patients had lower potassium and magnesium levels on admission, possibly due to the effect of COVID-19 on the renin-angiotensin-aldosterone system as well as patient characteristics and management. We did not find enough evidence to recommend using electrolyte levels as a determinator of prognosis, but more research is needed.