Non-severe Coronavirus Disease 2019 Patients Research Articles

Urinary cadmium concentration is associated with the severity and clinical outcomes of COVID-19: a bicenter observational cohort study

BackgroundCadmium and nickel exposure can cause oxidative stress, induce inflammation, inhibit immune function, and therefore has significant impacts on the pathogenesis and severity of many diseases. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection can also provoke oxidative stress and the dysregulation of inflammatory and immune responses. This study aimed to assess the potential associations of cadmium and nickel exposure with the severity and clinical outcomes of patients with coronavirus disease 2019 (COVID-19).MethodsWe performed a retrospective, observational, bicenter cohort analysis of patients with SARS-CoV-2 infection in Taiwan between June 2022 and July 2023. Cadmium and nickel concentrations in blood and urine were measured within 3 days of the diagnosis of acute SARS-CoV-2 infection, and the severity and clinical outcomes of patients with COVID-19 were analyzed.ResultsA total of 574 patients were analyzed and divided into a severe COVID-19 group (hospitalized patients) (n = 252; 43.9%), and non-severe COVID-19 group (n = 322; 56.1%). The overall in-hospital mortality rate was 11.8% (n = 68). The severe COVID-19 patients were older, had significantly more comorbidities, and significantly higher neutrophil/lymphocyte ratio, C-reactive protein, and interleukin-6 than the non-severe COVID-19 patients (all p < 0.05). Blood and urine cadmium and urine nickel concentrations were significantly higher in the severe COVID-19 patients than in the non-severe COVID-19 patients. Among the severe COVID-19 patients, those in higher urine cadmium/creatinine quartiles had a significantly higher risk of organ failure (i.e., higher APACHE II and SOFA scores), higher neutrophil/lymphocyte ratio, lower PaO2/FiO2 requiring higher invasive mechanical ventilation support, higher risk of acute respiratory distress syndrome, and higher 60-, 90-day, and all-cause hospital mortality (all p < 0.05). Multivariable logistic regression models revealed that urine cadmium/creatinine was independently associated with severe COVID-19 (adjusted OR 1.643 [95% CI 1.060–2.547], p = 0.026), and that a urine cadmium/creatinine value > 2.05 μg/g had the highest predictive value (adjusted OR 5.349, [95% CI 1.118–25.580], p = 0.036).ConclusionsUrine cadmium concentration in the early course of COVID-19 could predict the severity and clinical outcomes of patients and was independently associated with the risk of severe COVID-19.

Evaluation of the Relationship Between Serum miR-200b-3p and miR-214-3p Expression Levels with Soluble ACE2 and TMPRSS2 in COVID-19 Patients.

The emergence and rapid global spread of the coronavirus disease 2019 (COVID-19) has presented a significant global health challenge. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infects human host cells through the interaction of angiotensin-converting enzyme 2 (ACE2) and transmembrane serine protease 2 (TMPRSS2), which serve as main regulators for viral entry. Specifically, ACE2 and TMPRSS2 genes are influenced by two microRNAs: miR-200b-3p and miR-214-3p, respectively. The objective of this study was to explore the association between the serum levels of miR-200b-3p and miR-214-3p and the presence of circulating ACE2 and TMPRSS2 in severe and non-severe cases of COVID-19. This study sought to examine the potential utility of microRNAs as biomarkers for assessing disease severity and progression. Additionally, the study aimed to elucidate the interplay between microRNAs and the ACE2 and TMPRSS2 proteins, which play crucial roles in facilitating SARS-CoV-2 viral entry and infection. This practical-foundational study involved the collection of samples from 61 hospitalized patients with confirmed COVID-19 and 31 healthy individuals. Subsequently, the enzyme-linked immunosorbent assay (ELISA) technique was utilized to measure the concentrations of ACE2 and TMPRSS2 in the blood samples. Additionally, the expression levels of serum miR-200b-3p and miR-214-3p were analyzed using real-time polymerase chain reaction (PCR). The statistical analysis of the data was conducted using GraphPad Prism software (version 8.02) and SPSS software (version 19.0), ensuring the accurate interpretation of results. The findings revealed significant increases in the peripheral blood concentrations of ACE2 and TMPRSS2 in patients with non-severe COVID-19, compared to healthy individuals (P < 0.001 and P < 0.01, respectively). Similarly, patients with severe COVID-19 exhibited higher serum levels of ACE2 and TMPRSS2 than healthy subjects (P < 0.0001). Additionally, the serum levels of miR-200b-3p and miR-214-3p were decreased in both non-severe and severe COVID-19 patients, compared to healthy individuals (P < 0.01 and P < 0.0001, respectively). Moreover, a decrease in the serum levels of both miR-200b-3p and miR-214-3p was observed in patients with severe COVID-19, compared to those with non-severe cases (P < 0.001). Furthermore, this study identified a negative correlation between miR-200b-3p and ACE2 serum levels and between miR-214-3p and TMPRSS2 peripheral blood levels. The above-mentioned findings suggest that miR-200b-3p and miR-214-3p might be potential biomarkers for disease severity and prognosis in COVID-19 patients.

Analysis of Leukocyte Subpopulations by Flow Cytometry during Hospitalization Depending on the Severity of COVID-19 Course.

The mechanisms underlying the immune response to coronavirus disease 2019 (COVID-19) and the recovery process have not been fully elucidated. The aim of the study was to analyze leukocyte subpopulations in patients at significant time points (at diagnosis, and 3 and 6 months after infection) selected according to the analysis of changes in the lungs by the CT classification system, considering the severity of the disease. The study groups consisted of severe and non-severe COVID-19 patients. There was a significant decrease in CD8+ T cells, NK and eosinophils, with an increasing percentage of neutrophils during hospitalization. We noticed lower levels of CD4 and CD8 T lymphocytes, eosinophils, basophils, and CD16+ monocytes and elevated neutrophil levels in severe patients relative to non-severe patients. Three months after infection, we observed higher levels of basophils, and after 6 months, higher CD4/CD8 ratios and T cell levels in the severe compared to non-severe group. Non-severe patients showed significant changes in the leukocyte populations studied at time of hospitalization and both within 3 months and 6 months of onset. The CT CSS classification with parameters of the flow cytometry method used for COVID-19 patients determined changes that proved useful in the initial evaluation of patients.

Traditional Vietnamese Medicine Containing Garlic Extract for Patients With Non-severe COVID-19: A Phase-II, Double-Blind, Randomized Controlled Trial.

Background Coronavirus disease 2019 (COVID-19) is still ongoing with the omicron variant. Low-cost, effective treatments are still needed, particularly in low-to-middle-income countries. This study assessed the safety and efficacy of TD0068, an herbal medicine developed from mainly garlic, for patients with non-severe COVID-19. Methods This is a phase-II, double-blind, randomized controlled trial to compare oral capsule TD0068 and placebo in adults aged 18-65 years with non-severe COVID-19 between September and October 2021. The efficacy outcomes measured included daily cycle threshold (Ct) value from the time of the initial reverse transcription-polymerase chain reaction (RT-PCR) test, time to viral clearance, daily symptom severity score from 15 symptoms of interest, time to symptom resolution, and progression to severe/critical COVID-19. Safety outcomes included adverse events (AEs) and serious adverse events (SAEs). Results Sixty patients were randomized (31 received TD0068, and 29 received a placebo). The two groups were balanced in baseline characteristics: mean age was 39 years, and female was predominant (66%). Daily Ct value (median on days 3, 5, 7, and 9 was 25.7, 30.8, 35.4, and 37.6 in the TD0068 group, and 26.4, 31.2, 36.0, and 37.4 in the placebo group, respectively) and time to viral clearance (median: 10 vs. 11 days in TD0068 and placebo groups) were similar between groups. Daily symptom severity score (median on days 3, 5, 7, and 9 was 2, 2, 1, and 0 in the TD0068 group, and 3, 2, 1, and 1 in the placebo group), and time to symptom resolution (median: seven vs. nine days, respectively) were also comparable between groups. No SAE occurred in the study. Conclusions TD0068 is safe but does not show an effect for non-severe COVID-19 patients. Further research is needed to explore the potential benefits of garlic in other forms or dosages for the treatment of COVID-19.

Predicting the negative conversion time of nonsevere COVID-19 patients using machine learning methods.

Based on the patient's clinical characteristics and laboratory indicators, different machine-learning methods were used to develop models for predicting the negative conversion time of nonsevere coronavirus disease 2019 (COVID-19) patients. A retrospective analysis was performed on 376 nonsevere COVID-19 patients admitted to Wuxi Fifth People's Hospital from May 2, 2022, to May 14, 2022. The patients were divided into training set (n = 309) and test set (n = 67). The clinical features and laboratory parameters of the patients were collected. In the training set, the least absolute shrinkage and selection operator (LASSO) was used to select predictive features and train six machine learning models: multiple linear regression (MLR), K-Nearest Neighbors Regression (KNNR), random forest regression (RFR), support vector machine regression (SVR), XGBoost regression (XGBR), and multilayer perceptron regression (MLPR). Seven best predictive features selected by LASSO included: age, gender, vaccination status, IgG, lymphocyte ratio, monocyte ratio, and lymphocyte count. The predictive performance of the models in the test set was MLPR > SVR > MLR > KNNR > XGBR > RFR, and MLPR had the strongest generalization performance, which is significantly better than SVR and MLR. In the MLPR model, vaccination status, IgG, lymphocyte count, and lymphocyte ratio were protective factors for negative conversion time; male gender, age, and monocyte ratio were risk factors. The top three features with the highest weights were vaccination status, gender, and IgG. Machine learning methods (especially MLPR) can effectively predict the negative conversion time of non-severe COVID-19 patients. It can help to rationally allocate limited medical resources and prevent disease transmission, especially during the Omicron pandemic.

The detectable anti-interferon-γ autoantibodies in COVID-19 patients may be associated with disease severity

BackgroundNeutralizing anti-interferon (IFN)-γ autoantibodies are linked to adult-onset immunodeficiency and opportunistic infections.MethodsTo explore whether anti-IFN-γ autoantibodies are associated with disease severity of coronavirus disease 2019 (COVID-19), we examined the titers and functional neutralization of anti-IFN-γ autoantibodies in COVID-19 patients. In 127 COVID-19 patients and 22 healthy controls, serum titers of anti-IFN-γ autoantibodies were quantified using enzyme-linked immunosorbent assay, and the presence of autoantibodies was verified with immunoblotting assay. The neutralizing capacity against IFN-γ was evaluated with flow cytometry analysis and immunoblotting, and serum cytokines levels were determined using the MULTIPLEX platform.ResultsA higher proportion of severe/critical COVID-19 patients had positivity for anti-IFN-γ autoantibodies (18.0%) compared with non-severe patients (3.4%, p < 0.01) or healthy control (HC) (0.0%, p < 0.05). Severe/critical COVID-19 patients also had higher median titers of anti-IFN-γ autoantibodies (5.01) compared with non-severe patients (1.33) or HC (0.44). The immunoblotting assay could verify the detectable anti-IFN-γ autoantibodies and revealed more effective inhibition of signal transducer and activator of transcription (STAT1) phosphorylation on THP-1 cells treated with serum samples from anti-IFN-γ autoantibodies-positive patients compared with those from HC (2.21 ± 0.33 versus 4.47 ± 1.64, p < 0.05). In flow-cytometry analysis, sera from autoantibodies-positive patients could also significantly more effectively suppress the STAT1 phosphorylation (median,67.28%, interquartile range [IQR] 55.2–78.0%) compared with serum from HC (median,106.7%, IQR 100.0–117.8%, p < 0.05) or autoantibodies-negative patients (median,105.9%, IQR 85.5–116.3%, p < 0.05). Multivariate analysis revealed that the positivity and titers of anti-IFN-γ autoantibodies were significant predictors of severe/critical COVID-19. Compared with non-severe COVID-19 patients, we reveal that a significantly higher proportion of severe/critical COVID-19 patients are positive for anti-IFN-γ autoantibodies with neutralizing capacity.ConclusionOur results would add COVID-19 to the list of diseases with the presence of neutralizing anti-IFN-γ autoAbs. Anti-IFN-γ autoantibodies positivity is a potential predictor of severe/critical COVID-19.

Elevated monocyte distribution width in patients with active adult-onset Still's disease: a novel activity indicator.

Monocyte distribution width (MDW) correlates with volume modifications of circulating monocytes upon activation. Given the crucial role of monocyte activation in the pathogenesis of adult-onset Still's disease (AOSD), we aimed to examine the associations between MDW and disease activity or inflammatory parameters in this disease. In 58 AOSD patients and 95 other patients with coronavirus disease 2019 (COVID-19) as disease control, MDW and complete blood count were determined using a UniCel DxH800 analyser. C-reactive protein (CRP) levels were measured by nephelometry, and ferritin levels by chemiluminescent immunoassay. AOSD activity was assessed using a modified Pouchot score. MDW was significantly higher in active AOSD patients (median 28.3, interquartile range [IQR] 23.3-32.1) compared with inactive AOSD (19.2, IQR 18.0-20.6, p<0.001) or non-severe COVID-19 patients (23.2, IQR 21.0-25.2, p<0.01). MDW was positively correlated with AOSD activity scores, CRP, and ferritin levels (all p<0.001). Longitudinal follow-up evaluation revealed that median MDW significantly declined (28.3 versus 18.5, p<0.001) along with disease activity, paralleling a decrease in CRP and ferritin levels. Severe COVID-19 and sepsis patients had elevated MDW, which were not different from active AOSD patients. Multivariate analysis revealed MDW as a significant predictor of active AOSD, and MDW threshold at 21.7 could predict an active status with a high sensitivity of 91.3% and specificity of 94.3%. Elevated MDW and its positive correlation with inflammatory parameters in AOSD patients indicate MDW as a novel activity indicator, with a high MDW value above 21.7 linked to a high probability of active AOSD.

Machine learning-driven blood transcriptome-based discovery of SARS-CoV-2 specific severity biomarkers.

The Coronavirus disease 2019 (COVID-19)pandemic, caused by rapidly evolving variants ofsevere acute respiratory syndrome coronavirus (SARS-CoV-2),continues to be a global health threat. SARS-CoV-2 infection symptoms often intersect with other nonsevere respiratory infections, making early diagnosis challenging. There is an urgent need for early diagnostic and prognostic biomarkers to predict severity and reduce mortality when a sudden outbreak occurs. This study implemented a novel approach of integrating bioinformatics and machine learning algorithms over publicly available clinical COVID-19 transcriptome data sets. The robust 7-gene biomarker identified through this analysis can not only discriminate SARS-CoV-2 associated acute respiratory illness (ARI) from other types of ARIs but also can discriminate severe COVID-19 patients from nonsevere COVID-19 patients. Validation of the 7-gene biomarker in an independent blood transcriptome data set of longitudinal analysis of COVID-19 patients across various stages of the disease showed that the dysregulation of the identified biomarkers during severe disease is restored during recovery, showing their prognostic potential. The blood biomarkers identified in this study can serve as potential diagnostic candidates and help reduce COVID-19-associated mortality.

Development and external validation of a prognostic tool for nonsevere COVID-19 inpatients.

To develop a machine learning model and nomogram to predict the probability of persistent virus shedding (PVS) in hospitalized patients with coronavirus disease 2019 (COVID-19), the clinical symptoms and signs, laboratory parameters, cytokines, and immune cell data of 429 patients with nonsevere COVID-19 were retrospectively reviewed. Two models were developed using the Akaike information criterion (AIC). The performance of these two models was analyzed and compared by the receiver operating characteristic (ROC) curve, calibration curve, net reclassification index (NRI), and integrated discrimination improvement (IDI). The final model included the following independent predictors of PVS: sex, C-reactive protein (CRP) level, interleukin-6 (IL-6) level, the neutrophil-lymphocyte ratio (NLR), monocyte count (MC), albumin (ALB) level, and serum potassium level. The model performed well in both the internal validation (corrected C-statistic=0.748, corrected Brier score=0.201) and external validation datasets (corrected C-statistic=0.793, corrected Brier score=0.190). The internal calibration was very good (corrected slope=0.910). The model developed in this study showed high discriminant performance in predicting PVS in nonsevere COVID-19 patients. Because of the availability and accessibility of the model, the nomogram designed in this study could provide a useful prognostic tool for clinicians and medical decision-makers.

Serum Krebs von den Lungen-6 for Predicting the Severity of COVID-19: A Systematic Review, Meta-Analysis, and Trial Sequence Analysis.

This systematic review and meta-analysis aimed to find the association between serum Krebs von den Lungen-6 (KL-6) and the severity of Coronavirus disease 2019 (COVID-19) infection. Databases of Embase, PubMed, Web of Science, Science Direct, and Google Scholar were searched for studies reporting KL-6 levels in COVID-19 patients, published between January 2020 and September 30 2022. For comparison between the groups, standard mean difference (SMD) and 95% confidence intervals (CI) were computed as the effect sizes. Sensitivity, specificity, positive likelihood ratio (PLR), and negative likelihood ratio (NLR) were measured to assess the diagnostic power of KL-6. In addition, the summary receiver operating characteristics curve (sROC) was constructed to summarize the true positive (TP), and false positive (FP) rates. To validate the findings of meta-analysis, Trial Sequential Analysis (TSA) was conducted. Altogether 497 severe COVID-19 patients and 934 non-severe (mild to moderate) COVID-19 patients were included. Pooling of 12 studies indicated that the serum KL-6 level had significant association with severity of COVID-19 infection: standard mean difference = 1.18 (95% CI: 0.93-1.43), p = 0.01; I2: 58.56%]. Pooled diagnostic parameters calculated from eight studies were: sensitivity 0.53 (95% CI: 0.47-0.59); specificity 0.90 (95% CI: 0.88-0.93); positive likelihood ratio 4.80 (95% CI: 3.53-6.53); negative likelihood ratio 0.46 (95% CI: 0.32-0.68); and area under curve: 0.8841. Additionally, TSA verified the adequacy of sample size and robustness of the meta-analysis. Serum KL-6 level has a moderate degree of correlation with the severity of COVID-19 infection but has low sensitivity. So, it is not recommended as a screening test for severe COVID-19 infection.

Pulmonary Recovery 12 Months after Non-Severe and Severe COVID-19: The Prospective Swiss COVID-19 Lung Study

Background: Lung function impairment persists in some patients for months after acute coronavirus disease 2019 (COVID-19). Long-term lung function, radiological features, and their association remain to be clarified. Objectives: We aimed to prospectively investigate lung function and radiological abnormalities over 12 months after severe and non-severe COVID-19. Methods: 584 patients were included in the Swiss COVID-19 lung study. We assessed lung function at 3, 6, and 12 months after acute COVID-19 and compared chest computed tomography (CT) imaging to lung functional abnormalities. Results: At 12 months, diffusion capacity for carbon monoxide (DLCO_corr) was lower after severe COVID-19 compared to non-severe COVID-19 (74.9% vs. 85.2% predicted, p < 0.001). Similarly, minimal oxygen saturation on 6-min walk test and total lung capacity were lower after severe COVID-19 (89.6% vs. 92.2%, p = 0.004, respectively, 88.2% vs. 95.1% predicted, p = 0.011). The difference for forced vital capacity (91.6% vs. 96.3% predicted, p = 0.082) was not statistically significant. Between 3 and 12 months, lung function improved in both groups and differences in DLCO between non-severe and severe COVID-19 patients decreased. In patients with chest CT scans at 12 months, we observed a correlation between radiological abnormalities and reduced lung function. While the overall extent of radiological abnormalities diminished over time, the frequency of mosaic attenuation and curvilinear patterns increased. Conclusions: In this prospective cohort study, patients who had severe COVID-19 had diminished lung function over the first year compared to those after non-severe COVID-19, albeit with a greater extent of recovery in the severe disease group.

Effectiveness of corticosteroids to treat coronavirus disease 2019 symptoms: A meta-analysis

ObjectiveCurrently, corticosteroids are widely used to treat coronavirus disease 2019 (COVID-19) symptoms. However, the therapeutic role of corticosteroids remains highly controversial. To that end, we aimed to assess the efficacy of corticosteroids in treating COVID-19 patients. MethodWe searched PubMed, Embase, and Cochrane Library to select suitable studies. Our primary study endpoint was all-cause mortality. The secondary study endpoint was the length of hospital stay. ResultsA total of 9 randomized controlled trials (RCTs) with 7907 patients were assessed. The pooled result indicated that corticosteroids treatment could significantly reduce all-cause mortality in patients with COVID-19 (RR=0.88, 95% CI [0.82, 0.95], P=0.002). When subgroup analyses were performed, we found that corticosteroids were associated with decreased all-cause mortality in severe COVID-19 patients (RR=0.77, 95% CI [0.68, 0.88], P<0.0001), however no obvious difference was observed in all-cause mortality of non-severe COVID-19 patients between the corticosteroid and control group (RR=0.96, 95% CI [0.86, 1.06], P=0.41), meanwhile, a low dose (RR=0.89, 95% CI [0.82, 0.97], P=0.007) of dexamethasone (RR=0.9, 95% CI [0.83, 0.98], P=0.01) with a long treatment course (RR=0.89, 95% CI [0.82, 0.98], P=0.02) was beneficial for all-cause mortality in COVID-19 patients. Additionally, we found that corticosteroids might be associated with a longer length of hospital stay in non-severe COVID-19 patients (MD=3.83, 95% CI [1.11, 6.56], P=0.006). ConclusionOur results showed that corticosteroid therapy was related to a reduction in all-cause mortality in severe COVID-19 patients. However, in patients with non-severe COVID-19, the use of corticosteroids did not decrease all-cause mortality and may prolong the duration of hospital stay. In addition, we revealed that a low dose of dexamethasone with a long treatment course could reduce all-cause mortality in COVID-19 patients.

Clinical characteristics and short-term recovery of hyposmia in hospitalized non-severe COVID-19 patients with Omicron variant in Shanghai, China.

Olfactory dysfunction is a common neurological symptom of Corona Virus Disease 2019(COVID-19). Little is known about hyposmia after COVID-19 infection with Omicron variant in Chinese population. To investigate the incidence, clinical characteristics and recovery of hyposmia in hospitalized non-severe COVID-19 patients with Omicron variant in Shanghai, China. Three hundred and forty-nine Chinese non-severe COVID-19 patients with Omicron variant were consecutively enrolled in a designated hospital to investigate the incidence of hyposmia in hospitalization and the recovery rate 1 month later. The visual assessment scale (VAS) was used to evaluate the severity of hyposmia. We compared the demographic, clinical features and treatment outcomes, as well as laboratory parameters between patients with and without hyposmia. The cross-sectional survey showed that 22 (6.3%) hospitalized patients with non-severe COVID-19 had hyposmia. Patients with hyposmia were younger (61.5 vs. 72.0, p = 0.002), had more related clinical symptoms (sore throat, cough, poor appetite, diarrhea, myalgia and taste impairment, etc.), a higher proportion of moderate clinical type (31.8 vs. 13.5%, p = 0.028) and longer duration of hospitalization (11 vs. 8 days, p = 0.027) than those without hyposmia. Whereas, there were no significant differences regarding gender, comorbidity and nucleic acid conversion time between the two groups. Laboratory subgroup analyses demonstrated that patients with hyposmia had slightly low serum IL-6 and TNF-α levels. However, both of the levels were not associated with hyposmia occurrence in multivariate regression analyses. Further follow-up study disclosed that 16 of 22 (72.7%) hyposmia patients had recovered olfaction 1 month later. Serum IL-6 and TNF-α levels were similar between hyposmia recovered patients and those with persistent hyposmia. Although the incidence of hyposmia after Omicron variant infection is relatively low and the short-term recovery rate is quite high, patients with hyposmia are prone to have a higher proportion of both upper and lower respiratory tract involvements, gastrointestinal and neurological symptoms, contributing to a longer duration of hospitalization.

Use of low molecular weight heparin and hemoglobin fall in COVID-19 patients: A STROBE-compliant study

In patients with coronavirus disease 2019 (COVID-19), anticoagulation was suggested as a mitigating strategy. However, little research has been conducted on the adverse consequences of anticoagulant medication. This study aimed to investigate the adverse effect of low molecular weight heparin (LMWH) on hemoglobin fall in COVID-19 treatment. The electronic medical records of COVID-19 patients with pneumonia were collected (including clinical characteristics, vaccination status, complete blood count, coagulation profile, inflammatory cytokines, serum biochemical indicators, and computerized tomography imaging score). Whether they received LMWH, patients were divided into the LMWH group and the control group. Count data were represented as frequency distribution, and a 2-tailed test was used to compare the 2 groups. Spearman rank correlation was used to evaluate the interrelation between changes in hemoglobin and LMWH. The confounding factors were excluded by logistic regression analysis. A total of 179 COVID-19 pneumonia patients were enrolled (81 in the LMWH group and 98 in the control group). The change in hemoglobin was −6.0g/L (IQR −10.8 to 1.0) in the LMWH group and −2.0g/L (IQR −7.0 to 4.0) in the control group (P < .001, between-group difference, −5.0 g/L; 95% confidence interval, −7.0 to −3.0, calculated with the use of the Mann–Whitney U test and the Hodges–Lehmann estimate of confidence intervals for pseudo-medians). The results of multivariate regression analysis showed that after adjusting for confounding factors, LMWH use was not associated with a decrease in hemoglobin (P > .05). In nonsevere COVID-19 patients with pneumonia, the preventive use of LMWH did not lower hemoglobin.

Clinical characteristics and outcomes of COVID-19 patients in Bali, Indonesia.

IntroductionThe spectrum of illness and outcomes of coronavirus disease 2019 (COVID-19) patients may vary. This study reports the characteristics of COVID-19 patients in Bali, Indonesia, and evaluates the diagnostic value of their clinical symptoms.MethodThis observational study was conducted in eight hospitals. The patients were classified as non-severe COVID-19, severe COVID-19, and non-COVID-19. Demographics, clinical, laboratory, and radiologic characteristics, and outcomes of COVID-19 patients were collected. Factors associated with the severity and outcomes were assessed using the chi-squared test or ANOVA when appropriate. We also compared the clinical features of non-severe COVID-19 and non-COVID-19 patients to evaluate the diagnostic accuracy.ResultsThis study included 92 patients: 41 non-COVID-19 and 51 COVID-19 patients, comprising 45 non-severe and six severe cases. The most common symptoms of COVID-19 were cough (47.1%), fever (31.0%), and dyspnea (25.3%). Cough, fatigue, and anosmia have high accuracy, and combining these complaints in clinical diagnostics offered a higher accuracy in predicting COVID-19 patients (60.1%). We found lower lymphocyte counts and interleukin-1R levels and higher levels of C-reactive protein, interleukin-6, and interleukin-8 in severe compared than in non-severe COVID-19 patients. Lactate dehydrogenase was associated with intensive care unit admission and ventilator use, while other markers such as neutrophil-lymphocyte ratio, C-reactive protein, and interleukin-6 were not.ConclusionA battery of symptoms, including cough, fatigue, and anosmia, is likely associated with COVID-19 in Bali. Clinicians should be aware of these symptoms to ensure a prompt diagnostic test for COVID-19, beyond other causes of acute febrile illnesses.

Effectiveness of corticosteroids to treat coronavirus disease 2019 symptoms: A meta-analysis

ObjectiveCurrently, corticosteroids are widely used to treat coronavirus disease 2019 (COVID-19) symptoms. However, the therapeutic role of corticosteroids remains highly controversial. To that end, we aimed to assess the efficacy of corticosteroids in treating COVID-19 patients. MethodWe searched PubMed, Embase, and Cochrane Library to select suitable studies. Our primary study endpoint was all-cause mortality. The secondary study endpoint was the length of hospital stay. ResultsA total of 9 randomized controlled trials (RCTs) with 7907 patients were assessed. The pooled result indicated that corticosteroids treatment could significantly reduce all-cause mortality in patients with COVID-19 (RR=0.88, 95% CI [0.82, 0.95], P=0.002). When subgroup analyses were performed, we found that corticosteroids were associated with decreased all-cause mortality in severe COVID-19 patients (RR=0.77, 95% CI [0.68, 0.88], P<0.0001), however no obvious difference was observed in all-cause mortality of non-severe COVID-19 patients between the corticosteroid and control group (RR=0.96, 95% CI [0.86, 1.06], P=0.41), meanwhile, a low dose (RR=0.89, 95% CI [0.82, 0.97], P=0.007) of dexamethasone (RR=0.9, 95% CI [0.83, 0.98], P=0.01) with a long treatment course (RR=0.89, 95% CI [0.82, 0.98], P=0.02) was beneficial for all-cause mortality in COVID-19 patients. Additionally, we found that corticosteroids might be associated with a longer length of hospital stay in non-severe COVID-19 patients (MD=3.83, 95% CI [1.11, 6.56], P=0.006). ConclusionOur results showed that corticosteroid therapy was related to a reduction in all-cause mortality in severe COVID-19 patients. However, in patients with non-severe COVID-19, the use of corticosteroids did not decrease all-cause mortality and may prolong the duration of hospital stay. In addition, we revealed that a low dose of dexamethasone with a long treatment course could reduce all-cause mortality in COVID-19 patients.

MO113: Estimation of Hypocalcaemia, Hypoalbuminemia and Hypomagnesaemia Prevalence in Patients with COVID-19 and its Relationship with Clinical Manifestations and Disease Progression

Abstract BACKGROUND AND AIMS Electrolyte abnormalities are common among patients with coronavirus disease 2019 (COVID-19). This study aims to investigate the electrolyte changes in severe and non-severe COVID-19 patients. Hypocalcaemia, hypomagnesaemia and hypoalbuminemia and their relationship with the severity of symptoms and prognosis will also be determined. METHOD We enrolled 270 COVID-19 patients. Serum tests were taken from each patient on the day of admission to check the level of variables. Thereon, calcium, magnesium and phosphorus levels were measured twice a week and albumin levels were measured once a week. Variables such as PTH and 25 (OH) D were measured once at the beginning of the study. Other laboratory results like complete blood count, C-reactive protein and clinical data such as arterial blood oxygen levels, length of stay in the ICU and the treatment regimen were extracted from patients' medical records and history. Finally, patients were categorized as mild, moderate, severe and critical group based on the severity of the disease. The data analyses were carried out via SPSS software (version 21.0). RESULTS Of 270 patients, 135 people (50%) were men. The mean age of patients was 46.7 years. Based on the severity of the disease, 91 patients had mild disease, 90 patients presented with moderate disease, 54 patients were in severe condition and 35 patients were critical. Hypocalcaemia (Ca 2+ ≤8.6 mg/dL) was detected in 49 patients (18.1%) on admission. The mean of serum magnesium, phosphorus and albumin levels on admission was 2.2 ± 0.22 mEq/L, 3.39 ± 0.79 mg/dL and 4.49 ± 0.66g/dL, respectively. Phosphorus level was lower than 2.63 mg/dL in 11 patients (4.07%) and 43 patients (15.92%) had hypoalbuminemia. The mean 25(OH) D level was 32.92 ± 10.29 μg/L; therefore, 182 patients (67.40%) fall within the normal range (&amp;gt;30 μg/L). CONCLUSION Patients with mild and moderate disease tend to develop hypocalcaemia, hypoalbuminemia and hypomagnesaemia more often than severe and critical COVID-19 patients during treatment. 25(OH) D deficiency rate was higher in the moderate group. Patients with hypocalcaemia during treatment had higher mortality than other patients. We recommend electrolytes be measured at initial presentation and serially monitored during hospitalization in order to establish timely and appropriate corrective actions and prevent the serious complications of the disease.

Home Management of COVID-19 Patients: A Successful Model in Non-severe COVID-19 Patients in the Developing World.

BackgroundAround 80-85% of coronavirus disease 2019 (COVID-19) cases were reported to have mild disease and home treatment of such patients was proved to be effective without significant morbidity or mortality. Therefore, the aim of this study was to assess the outcome of home management of non-severe COVID-19 infection in healthcare providers in the developing world.MethodsThis observational cohort study was conducted at the National Institute of Cardiovascular Diseases from June 2020 till January 2021. It included health care workers who tested positive for COVID-19 with non-severe infection and received home treatment. The COVID-19 management team monitored their symptoms and oxygen saturation over the phone. Need-based lab tests, X-rays, home proning, steroids, and oxygen were administered along with the standard intuitional management strategies. Study outcomes included duration of recovery, need for hospitalization, and expiry.ResultsA total of 128 patients were included, out of which 98 (76.6%) were male, and the mean age was 32.9 ± 5.9 years. Fever was the most common symptom, seen in 89.8% of patients. Most of the patients (85.9%) had no pre-existing comorbidities. Five patients received home oxygen therapy, seven received steroid therapy, and one received home pruning. The average time of recovery was 13.8 ± 8.1 days with no mortality; however, 14 (10.9%) patients were hospitalized due to worsening of symptoms.ConclusionHome treatment for COVID-19 patients with mild to moderate disease after appropriate risk assessment can be a safe and effective option to preserve hospital capacities for more needy and severely ill patients.

Early Identification of COVID-19 Progression to Its Severe Form Using Artificial Intelligence

Background: Early prediction of disease progression in coronavirus disease 2019 (COVID-19) patients can be helpful for personalized therapy, as well as the optimal allocation of public health resources. Objectives: This study aimed to present predictive models for identifying potential high-risk COVID-19 patients upon hospital admission, based on the examination of clinical and radiological features by radiologists and artificial intelligence (AI). Patients and Methods: A total of 786 initially non-severe COVID-19 patients were retrospectively enrolled in this study between January 2 and May 28, 2020. The patients were randomly divided into training (n = 628, 80%) and test (n = 158, 20%) groups. Clinical factors, laboratory indicators, and radiologist- and AI-extracted radiological features of pneumonia lesions were determined using a convolution neural network. The features were selected based on the Boruta algorithm with five-fold cross-validation. Four models, including a model based on clinical findings (model C), a model based on the physician’s examination of radiological features (R-Doc model), a model based on AI-derived radiological features (R-AI model), and an AI-based model mimicking the physician’s examinations (AI-Mimic-Doc model), were constructed for predicting COVID-19 progression upon admission, using a logistic regression analysis. The predictive performance of the four models was evaluated by calculating the area under the receiver operating characteristic (AUC) curve with a 95% confidence interval (95% CI) and then compared using the DeLong test. Results: Overall, 238 out of 786 patients (30.3%) progressed into severe or critical pneumonia during the 14-day follow-up. Nine clinical findings, 17 laboratory indicators, 48 physician-extracted radiological features of pneumonia lesions, and 126 AI-driven radiological features were collected. The urea, albumin level, and lesion size in the basal segment of the right lower lobe of the lung or the proportion of CT values in the range of -200 - 60 in the left lung were the representative features for constructing the R-Doc and R-AI models, respectively. Comparison of the R-Doc model (AUC: 0.840, 95% CI: 0.747 - 0.933 for the training set and 0.731, 95% CI: 0.606 - 0.857 for the test set) with the R-AI model (AUC: 0.803, 95% CI: 0.701 - 0.906 for the training set and AUC: 0.731, 95% CI: 0.606 - 0.857 for the validation set) indicated a marginal difference in identifying patients at risk of progression to pneumonia upon admission (P &lt; 0.1). The R-AI model was superior to model C, with an AUC of 0.770 for the training set (95% CI: 0.657 - 0.882) and 0.666 for the validation set to identify high-risk non-severe cases upon admission. Conclusion: By using radiological features along with blood tests, early identification of COVID-19 patients, who are at risk of disease progression, can be achieved on admission (rapidly by using AI); therefore, the use of these features can contribute to the clinical management of COVID-19.

The effect of vitamin E and vitamin C in patients with COVID-19 pneumonia;a randomized controlled clinical trial

Introduction: Cytokine storm and oxidative stress play a key role in the pathogenesis of coronavirus disease 2019 (COVID-19). Vitamins C and E are two known antioxidants with possible theoretical beneficial effects in COVID-19 patients. Objectives: This study aimed to clinically evaluate the effects of the combination of these agents as adjunctive therapy with the standard treatment in the outcome of COVID-19 patients. Patients and Methods: Hospitalized non-severe COVID-19 patients were randomly divided into two groups of intervention (n=38) and control (n=34) to receive either oral vitamin C 1000 mg daily plus oral vitamin E 400 IU daily in addition to the national standard treatment regimen (hydroxychloroquine) or standard regimen alone, respectively, during the hospitalization period until hospital discharge or ICU admission. The clinical response of patients at the end of treatment (either cure, improvement, or failure), the duration of hospitalization, and the mortality rate were recorded and compared between the groups. Results: During the study, three patients in the intervention group (7.89%) and five patients in the control group (14.71%) had treatment failure, while all other patients had clinical improvement (P = 0.380). The duration of hospitalization was shorter in the intervention group (7.95 ± 3.18 days) compared to the control group (8.03 ± 2.83 days); however, the difference was not statistically significant (P = 0.821). Furthermore, no patients in both groups died during the study. Conclusion: The combination of oral vitamins C (1000 mg daily) and E (400 IU daily) has no beneficial effect in COVID-19 patients. Trial Registration: Registration of trial protocol has been approved in Iranian registry of clinical trials (identifier: IRCT20180425039414N3; https://www.irct.ir/trial/48083, ethical# IR.MUI.MED.REC.1399.047).