Decreased serum albumin level indicates poor prognosis of COVID-19 patients: hepatic injury analysis from 2,623 hospitalized cases

Construction and Validation of a Prediction Model for Postoperative Fatigue Syndrome in Chinese Patients with Lung Cancer

BACKGROUND

Postoperative fatigue syndrome (POFS) is prevalent in patients with lung cancer after surgery but often overlooked clinically, affecting patient care and recovery. Predictive models for assessing the risk and severity of postoperative fatigue in persons diagnosed with lung cancer are lacking.

OBJECTIVE

To develop a predictive model for POFS in patients with lung cancer to address under-recognition and its impact on recovery.

METHODS

Data from 203 lung cancer surgery patients were analyzed through univariate analysis to compare the relevant factors between 2 groups . Least absolute shrinkage and selection operator regression were used to screen potential key predictors. Multivariate regression analysis was used to identify independent influencing factors and build a nomogram. Receiver operating characteristic curve, calibration curve, and decision curve analysis (DCA) were used to evaluate the discrimination, accuracy, and clinical usability of the prediction model, with internal validation by the Bootstrap method.

RESULTS

Of the 203 patients, 57.1% developed POFS. The prediction model included 5 significant predictors: sleep quality, pain, activated partial thromboplastin time, forced vital capacity, and forced expiratory volume in 1 second/forced vital capacity ratio. The nomogram based on this model achieved an area under the receiver operating characteristic curve of 0.870, indicating good accuracy, with strong predictive power in internal validation. DCA showed clinical utility when the probability of POFS was above approximately 13%.

CONCLUSIONS

We found a high prevalence of POFS in survivors with lung cancer and successfully constructed a comprehensive nomogram with 5 factors.

Association between the lactate dehydrogenase-to-albumin ratio and 28-day mortality in septic patients with malignancies: analysis of the MIMIC-IV database

BACKGROUND

Sepsis remains a leading cause of mortality in critically ill patients, particularly those with malignancies who face heightened risks due to immunosuppression and metabolic dysregulation. This study aimed to evaluate the prognostic value of the lactate dehydrogenase-to-albumin ratio (LDAR) for predicting 28-day ICU mortality in septic patients with malignancies.

METHODS

A retrospective cohort analysis was conducted using data from 1,635 septic patients with malignancies in the MIMIC-IV (3.1) database. Participants were stratified into quartiles based on LDAR values. The primary outcome was 28-day ICU mortality, with secondary outcomes including in-hospital and ICU mortality. Multivariable logistic regression, restricted cubic spline (RCS) analysis, and machine learning models were employed to assess associations between LDAR and outcomes. Subgroup analyses and feature importance evaluations were performed to validate robustness. The Shapley additive explanations method was used to enhance model interpretability and assess individual predictor contributions.

RESULTS

Higher LDAR is independently associated with increased 28-day ICU mortality (OR: 3.441, 95% CI: 2.497-4.741), ICU mortality (OR: 3.478, 95% CI: 2.396-5.049), and in-hospital mortality (OR: 3.747, 95% CI: 2.688-5.222), even after adjustment, highlighting its potential as a prognostic marker in ICU patients. RCS analysis revealed a nonlinear relationship, with mortality risk escalating sharply beyond log₂(LDAR) = 6.940. Metastatic cancer patients had higher median LDAR (135.0 vs. 118.5, P = 0.004) and mortality rates (52.0% vs. 36.4%, P < 0.001). Boruta feature selection showed that LDAR as the top predictor of mortality. Nine machine learning model with 20 variables were built, with random forest model performing best, achieving an AUC of 0.751 (0.708-0.794) in validation and 0.727 (0.682- 0.772) in text cohort.

CONCLUSIONS

LDAR is a robust, independent prognostic biomarker for 28-day ICU mortality in septic patients with malignancies, outperforming traditional scoring systems. The identified threshold (log₂(LDAR) ≥ 6.940) may aid early risk stratification and clinical decision-making. Prospective studies are warranted to validate these findings and explore dynamic LDAR monitoring in diverse populations.

Time Course of Biochemical and Metabolic Parameters During and After COVID-19

BACKGROUND

Long COVID is characterized by the persistence of symptoms among individuals who are infected with the SARS-CoV-2 virus. The enduring impact of these long-term effects on the health and well-being of those affected cannot be denied.

METHODS

470 patients with SARS-CoV-2 were consecutively recruited in this longitudinal study. The participants were entered into moderate, severe, and critical groups. 235 out of 470 participants were female. The levels of fasting blood sugar (FBS), alanine transaminase (SGPT), aspartate aminotransferase (SGOT), alkaline phosphatase (ALP), creatinine (Cr), urea, uric acid (UA), and total protein (TP) were measured during hospitalization and again at one and three months after infection. The levels of Zn and hemoglobin A1c (HbA1c) were also measured only during hospitalization.

RESULTS

COVID-19 severity was associated with high levels of glucose, urea, Cr, ALT, AST, ALP, and HbA1c, and low levels of Zn, UA, and TP. There were significant sex differences for these markers at all three-time points. Glucose, urea, Cr, ALT, AST, and ALP all decreased three months after infection, whereas the levels of UA and TP returned towards normal.

CONCLUSION

COVID-19 infection affects the levels of multiple biochemical factors in a gender-dependent manner. The biochemical changes become more tangible with increasing disease severity, and several of these predict mortality. Levels begin to return to normal after the acute phase of the disease, but in some individuals, at three months, several markers were still not within the normal range. Whether the trajectory of these changes can predict long COVID requires further testing.

Construction of geriatric hypoalbuminemia predicting model for hypoalbuminemia patients with and without pneumonia and explainability analysis

Background and objectives

Pneumonia portrays a critical health concern in geriatrics. Geriatric pneumonia can lead to changes on other complications, in which hypoalbuminemia is a common complication. However, few studies have looked at the impact of pneumonia on the course of hypoalbuminemia and predicting. This study aims to predicting hypoalbuminemia in geriatric pneumonia and non-pneumonia patients and exploring the clinical difference between the two groups.

Materials and methods

This retrospective study enrolled 42 pneumonia patients group and 76 non-pneumonia patients group. The indicators difference of different groups were analyzed, then a mutual information-grey relational coefficient gradual fusion model was constructed to predict hypoalbuminemia in the future by the indicators of vital signs, N-Terminal Pro-Brain Natriuretic Peptide, blood routine examination and urine routine examination at admission. Through the sensitivity analysis of model, we analysed the important of four examines in patients with and without pneumonia.

Results

The predicted accuracy of our gradual fusion model was 0.954, which improve the prediction accuracy by nearly 17.6% compared with the classical machine learning method. The AUC of gradual fusion model was 0.96 and 0.9 in hypoalbuminemia patients with and without pneumonia. The sensitivity analysis of gradual fusion model showed blood routine examine was most important to predict hypoalbuminemia in patients with pneumonia, while urine routine examine was most important to predict hypoalbuminemia in non-pneumonia patients.

Conclusion

The changes in the blood of patients with hypoalbuminemia combined with pneumonia were more significant than that of patients with hypoalbuminemia alone, which was characterized by abnormal excretion due to low protein. We suggested doctors should pay more attention to blood routine results when preventing hypoalbuminemia in patients with pneumonia and pay more attention to urine routine examine results when preventing hypoalbuminemia in patients without pneumonia.

High platelet-to-albumin ratio is associated with 30-day mortality in critically ill patients

BACKGROUND

The role of inflammation and hypoproteinemia in influencing outcomes of critically ill patients has been widely recognized. However, there is a paucity of research on the prognostic value of the platelet-to-albumin ratio (PAR) in critically ill patients. Therefore, the aim of this study is to assess the prognostic significance of PAR in this population.

METHODS

Patients diagnosed with critical illnesses from January 2020 to October 2022 were retrospectively enrolled in our study. Baseline demographic and clinical data were collected for each participant. Platelet counts and albumin levels were measured at baseline, and the PAR was calculated. The area under the receiver operating characteristic curve, Kaplan-Meier survival analysis, and multivariate Cox regression analysis were used to predict 30-day mortality.

RESULTS

Three hundred and seventy-eight patients diagnosed with critical illness were categorized into two groups: survivors (n = 299) and non-survivors (n = 79). Analysis of the 30-day outcome revealed that the area under the curve (AUC) for the PAR (AUC: 0.705; 95% CI 0.639-0.771; p < 0.001) was significantly higher than that for albumin (AUC: 0.673; 95% CI 0.609-0.736; p < 0.001), but slightly lower than that for the APACHE II score (AUC: 0.713; 95% CI 0.650-0.777; p < 0.001). In addition, the Kaplan-Meier survival analysis demonstrated a significantly higher 30-day mortality in the high-PAR group. Furthermore, Cox regression analysis identified albumin (HR: 0.936; 95% CI 0.895-0.978; p = 0.003), APACHE II score (HR: 1.225; 95% CI 1.149-1.305; p < 0.001), and high PAR (HR: 1.237; 95% CI 1.130-1.353; p < 0.001) as independent risk factors for the prognosis of critically ill patients.

CONCLUSIONS

The PAR has emerged as a significant prognostic indicator in critically ill patients, with an elevated ratio being associated with poorer clinical outcomes.

Clinical, biochemical, and genetic study of TACE/TNF-α/ACE signaling pathway in pediatric COVID-19 infection

BACKGROUND

Pediatric patients infected with coronavirus disease 2019 (COVID-19) have unique clinical characteristics. Tumor necrosis factor (TNF) is a proinflammatory cytokine that greatly contributes to tumor pathogenesis.

PURPOSE

To describe the presenting characteristics of COVID-19 infection among pediatric patients, and investigate the possible role of the TNF-α signaling pathway.

METHODS

This prospective case-control study included 50 Egyptian pediatric patients with COVID-19 and 50 healthy controls. Clinical, laboratory, and radiological assessments were performed. Serum TNF-alpha (TNF-α), TNF-α-converting enzyme (TACE), and angiotensin-converting enzyme 2 (ACE2) were measured using enzyme-linked immunosorbent assay. ACE (I/D) (rs4646994), ACE2 rs2285666, and TNF-α-308G/A single nucleotide polymorphisms (SNPs) were performed using conventional polymerase chain reaction techniques with or without restriction fragment length polymorphism.

RESULTS

The median age was 1 year (interquartile range [IQR], 0.31-2.50 years) in the case group and 1.45 years (IQR, 1.00-3.00) in the control group. The main presenting symptoms were fever (92%), dry cough (74%), and dyspnea (72%). The lymphocytic count was normal in 14 patients (28%), decreased in 16 patients (32%), and increased in 20 patients (40%) of the case group. Positive chest computed tomography finding of COVID-19 infection were demonstrated among 40% of patients using COVID-19 Reporting and Data System categories (ground-glass opacity with or without consolidations in the lungs). There were significant increased serum TACE and TNF-α with decreased ACE2 levels among cases versus controls (P< 0.001). The GG genotype and G allele of the TNF-α-308G/A SNP were significantly higher in patients than in controls (P<0.05 for both), with insignificant differences in genotype and allelic frequencies in the ACE (I/D) (rs4646994) and ACE2 rs2285666 SNPs.

CONCLUSION

The TNF signaling pathway was significantly activated in pediatric COVID-19 infection. Only the TNF-α-308G/A SNP was significantly associated with pediatric COVID-19 infection.

A retrospective cohort study on the association between nutritional status and prognosis in COVID-19 patients with severe and critical infection

OBJECTIVE

To evaluate the relationship between nutritional scoring systems, nutritional support methods, and the prognosis of severe and critically ill patients infected with the Omicron variant of coronavirus disease 2019 (COVID-19).

METHODS

Patients with confirmed Omicron variant severe and critical COVID-19, who were admitted to Chongqing Medical University First Hospital between December 2022 and January 2023, were enrolled into this retrospective study. Clinical data of patients who survived for 28 days were compared with those who died during the same period. Nutritional status was assessed using the 2002 Nutrition Risk Screening (NRS) tool and Prognostic Nutritional Index (PNI). Factors influencing patient mortality were identified by multivariate logistic regression, and the relationship between patient nutrition and mortality as the disease progressed was illustrated using Kaplan-Meier curves. The study was registered on the ChiCTR platform (No. ChiCTR2300067595).

RESULTS

A total of 508 patients were included (349 survivors and 159 non-survivors). Significant differences were found in sex, age, NRS score, PNI score, albumin level, lymphocyte count, chronic comorbidities, mechanical ventilation, neutrophil count, procalcitonin, and platelet count between survivors and non-survivors. Multivariate analysis revealed that high NRS score (OR 3.87, 95% CI, 1.97, 7.63), fourth-level nutritional support (combined enteral and parenteral nutrition; OR 7.89, 95% CI, 1.32, 47.28), chronic comorbidities (OR 4.03, 95% CI, 1.91, 8.51), and mechanical ventilation (OR 6.03, 95% CI, 3, 12.13) were risk factors for mortality (OR > 1). The malnutrition rate among patients with NRS ≥ 3 was 41.93%. The median (interquartile range) PNI score was 38.20 (35.65, 41.25) for survivors versus 32.65 (29.65, 36.58) for non-survivors. The mortality rate was higher in patients with high nutritional risk within 28 days of hospitalization. The descending order for mortality rate in patients receiving different nutritional support was: dual parenteral and enteral nutrition, no nutritional intervention, single enteral nutrition, and single parenteral nutrition.

CONCLUSION

A high proportion of severe and critically ill patients with COVID-19 experience malnutrition, and various factors are associated with their prognosis. High nutritional risk is significantly related to patient mortality. Early assessment using NRS or PNI is crucial for these patients, and personalized interventions should be implemented to improve overall nutritional status, maintain organ function, and enhance the body's antiviral defence.

Evaluation of Oxidative Stress and Endothelial Dysfunction in COVID-19 Patients

Background and Objectives: Heat shock proteins (HSPs) are stress proteins. The endogenous nitric oxide (NO) synthase inhibitor asymmetric dimethyl arginine (ADMA) is a mediator of endothelial dysfunction. Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) virus causes endothelial dysfunction and coagulopathy through severe inflammation and oxidative stress. Using these markers, we analyzed the prognostic value of serum ADMA and HSP-90 levels for early prediction of severe coronavirus disease (COVID-19) patients. Materials and Methods: A total of 76 COVID-19 patients and 35 healthy control subjects were included in this case-control study. COVID-19 patients were divided into two groups: mild and severe. Results: Serum ADMA and HSP-90 levels were significantly higher in the COVID-19 patients compared to the control subjects (p < 0.001). Additionally, serum ADMA and HSP-90 levels were determined to be higher in a statistically significant way in severe COVID-19 compared to mild COVID-19 (p < 0.001). Univariable logistic regression analysis revealed that ADMA and HSP-90, respectively, were independent predictors of severe disease in COVID-19 patients (ADMA (OR = 1.099, 95% CI = 1.048-1.152, p < 0.001) and HSP-90 (OR = 5.296, 95% CI = 1.719-16.316, p = 0.004)). When the cut-off value for ADMA was determined as 208.94 for the prediction of the severity of COVID-19 patients, the sensitivity was 72.9% and the specificity was 100% (AUC = 0.938, 95%CI = 0.858-0.981, p < 0.001). When the cut-off value for HSP-90 was determined as 12.68 for the prediction of the severity of COVID-19 patients, the sensitivity was 88.1% and the specificity was 100% (AUC = 0.975, 95% CI= 0.910-0.997, p < 0.001). Conclusions: Increased levels of Heat shock proteins-90 (HSP-90) and ADMA were positively correlated with increased endothelial damage in COVID-19 patients, suggesting that treatments focused on preventing and improving endothelial dysfunction could significantly improve the outcomes and reduce the mortality rate of COVID-19. ADMA and HSP-90 might be simple, useful, and prognostic biomarkers that can be utilized to predict patients who are at high risk of severe disease due to COVID-19.

ARDS in solid organ transplant recipients hospitalized for COVID-19 based on the 2023 new definition

BACKGROUND

Solid organ transplant recipients (SOTRs) are more likely to suffer complications after being infected with severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

OBJECTIVES

We aimed to describe the clinical features of SOTRs infected with SARS-CoV-2 and to assess independent risk factors associated with the development of acute respiratory distress syndrome (ARDS) following COVID-19 infection in SOTRs based on the new ARDS definition.

METHODS

358 SOTRs infected with SARS-CoV-2 were recruited and divided into two groups, patients with ARDS (n = 81) and patients without ARDS (n = 277). Demographic data, initial laboratory findings, therapeutic measures, and outcome indicators were compared between the two groups. The association between the onset of ARDS and related factors was analyzed using a logistic regression model. A nomogram was created to estimate the probability of developing ARDS.

RESULTS

Approximately 22.6 % (81/358) of hospitalized SOTRs infected with SARS-CoV-2 developed ARDS. In comparison to patients without ARDS, those with ARDS presented with more underlying conditions, decreased lymphocyte counts and serum albumin levels, but increased levels of leukocytes, serum creatinine, nitrogen urea, uric acid, and inflammatory markers. Cerebrovascular disease, leukocyte counts, albumin levels, and IL-6 levels were independent risk factors for the development of ARDS in this population. Furthermore, a nomogram prediction model was created utilizing the aforementioned factors to facilitate early prediction of ARDS, exhibiting an AUC (area under curve) of 0.81.

CONCLUSIONS

Cerebrovascular disease, leukocyte counts, albumin levels, and IL-6 levels were independent risk factors for the development of ARDS following COVID-19 infection in SOTRs.

Prognostic factors of fungal infection in anti-melanoma differentiation-associated gene 5 antibody-positive associated interstitial lung disease

OBJECTIVE

To investigate the potential risk factors for mortality in fungal infection in anti-melanoma differentiation-associated gene 5 antibody-positive associated interstitial lung disease (MDA5-ILD).

METHODS

Patients diagnosed with MDA5-ILD from April 2017 to November 2022 were included. The demographic data, laboratory examinations, therapeutic and follow-up information were recorded. Fungal infection diagnosis was established based on a combinations of host factors, clinical features and mycologic evidences. High-dose corticosteroid therapy was defined as the initial corticosteroid doses > 240mg/d. The primary endpoint was mortality. Potential factors for fungal infection occurrence and prognostic factors were analyzed using logistic regression analysis and Cox proportional hazards regression.

RESULTS

In total, 121 patients with MDA5-ILD were included. During follow-up, 41 (33.9%) patients had suffered fungal infection and 39.0% (16/41) of whom had ever received high-dose corticosteroid therapy. The median interval from corticosteroid use to the occurrence of fungal infection was 29 (10-48) days. The mean survival time of patients with fungal infection was 234.32 ± 464.76 days. The mortality in MDA5-ILD with fungal infection was 85.4% (35/41), which was significantly higher than those without (85.4% VS 56.3%, P < 0.001). High-dose corticosteroid therapy (P = 0.049) was independent risk factor for fungal infection occurrence. Decreased serum albumin level (P = 0.024) and high-dose corticosteroid therapy (P = 0.008) were both associated with increased mortality in MDA5-ILD patients with fungal infection.

CONCLUSION

Fungal infection is associated with an increased mortality in MDA5-ILD. The serum albumin level and corticosteroid dose should be taken into consideration when treating MDA5-ILD. Key Points • This study showed fungal infection is associated with an increased mortality in MDA5-ILD. In MDA5-ILD patients with fungal infection, the presence of decreased serum albumin level and high-dose corticosteroid therapy were identified as predictors for mortality.

Diagnostic Value of Galectin-3 in Exacerbations of Chronic Obstructive Pulmonary Disease

Background and Objectives: Chronic obstructive pulmonary disease (COPD) is a chronic inflammatory disease characterized by acute exacerbations. Systemic inflammation and oxidative stress play an important role in the pathogenesis of COPD. Exacerbations in COPD reduce the quality of life and are associated with rapid disease progression. Galectin-3 is a beta-galactoside-binding lectin of approximately 30 kDa with pro-inflammatory and pro-fibrotic properties. This study aims to analyze the efficacy of serum galectin-3 in predicting exacerbations in COPD patients. Materials and Methods: Baseline demographic and clinical characteristics of all patients were recorded and blood samples were collected. A total of 58 consecutive COPD patients, including 28 patients (19 male and 9 female) with stable COPD and 30 patients (23 male and 7 female) with acute exacerbation of COPD (AECOPD), were included in the study. Results: Serum galectin-3 levels were significantly higher in the AECOPD group compared to the stable COPD group. A logistic regression analysis revealed that increased galectin-3 levels and disease duration were independent predictors of COPD exacerbation (OR = 5.322, 95% CI: 1.178-24.052, p = 0.03; and OR = 1.297, 95% CI: 1.028-1.635, p = 0.028; respectively). Conclusions: The results of our study demonstrated that Galectin-3 was a strong and independent predictor of exacerbations in COPD patients.

Blood Urea Nitrogen-to-Albumin Ratio May Predict Mortality in Patients with Traumatic Brain Injury from the MIMIC Database: A Retrospective Study

Traumatic brain injury (TBI), a major global health burden, disrupts the neurological system due to accidents and other incidents. While the Glasgow coma scale (GCS) gauges neurological function, it falls short as the sole predictor of overall mortality in TBI patients. This highlights the need for comprehensive outcome prediction, considering not just neurological but also systemic factors. Existing approaches relying on newly developed biomolecules face challenges in clinical implementation. Therefore, we investigated the potential of readily available clinical indicators, like the blood urea nitrogen-to-albumin ratio (BAR), for improved mortality prediction in TBI. In this study, we investigated the significance of the BAR in predicting all-cause mortality in TBI patients. In terms of research methodologies, we gave preference to machine learning methods due to their exceptional performance in clinical support in recent years. Initially, we obtained data on TBI patients from the Medical Information Mart for Intensive Care database. A total of 2602 patients were included, of whom 2260 survived and 342 died in hospital. Subsequently, we performed data cleaning and utilized machine learning techniques to develop prediction models. We employed a ten-fold cross-validation method to obtain models with enhanced accuracy and area under the curve (AUC) (Light Gradient Boost Classifier accuracy, 0.905 ± 0.016, and AUC, 0.888; Extreme Gradient Boost Classifier accuracy, 0.903 ± 0.016, and AUC, 0.895; Gradient Boost Classifier accuracy, 0.898 ± 0.021, and AUC, 0.872). Simultaneously, we derived the importance ranking of the variable BAR among the included variables (in Light Gradient Boost Classifier, the BAR ranked fourth; in Extreme Gradient Boost Classifier, the BAR ranked sixth; in Gradient Boost Classifier, the BAR ranked fifth). To further evaluate the clinical utility of BAR, we divided patients into three groups based on their BAR values: Group 1 (BAR < 4.9 mg/g), Group 2 (BAR ≥ 4.9 and ≤10.5 mg/g), and Group 3 (BAR ≥ 10.5 mg/g). This stratification revealed significant differences in mortality across all time points: in-hospital mortality (7.61% vs. 15.16% vs. 31.63%), as well as one-month (8.51% vs. 17.46% vs. 36.39%), three-month (9.55% vs. 20.14% vs. 41.84%), and one-year mortality (11.57% vs. 23.76% vs. 46.60%). Building on this observation, we employed the Cox proportional hazards regression model to assess the impact of BAR segmentation on survival. Compared to Group 1, Groups 2 and 3 had significantly higher hazard ratios (95% confidence interval (CI)) for one-month mortality: 1.77 (1.37-2.30) and 3.17 (2.17-4.62), respectively. To further underscore the clinical potential of BAR as a standalone measure, we compared its performance to established clinical scores, like sequential organ failure assessment (SOFA), GCS, and acute physiology score III(APS-III), using receiver operator characteristic curve (ROC) analysis. Notably, the AUC values (95%CI) of the BAR were 0.67 (0.64-0.70), 0.68 (0.65-0.70), and 0.68 (0.65-0.70) for one-month mortality, three-month mortality, and one-year mortality. The AUC value of the SOFA did not significantly differ from that of the BAR. In conclusion, the BAR is a highly influential factor in predicting mortality in TBI patients and should be given careful consideration in future TBI prediction research. The blood urea nitrogen-to-albumin ratio may predict mortality in TBI patients.

A prospective observational study to correlate lung ultrasound with clinical severity and prognosis score in patients with primary pulmonary pathology on invasive ventilatory support

Background

Lung ultrasound (LUS) is a known imaging modality employed for monitoring patients in an intensive care unit. This study evaluates, LUS in assessing disease severity and prognosis, by correlating its score with the three commonly used clinical severity scoring systems (CSSS), namely, sequential organ failure assessment (SOFA) score, acute physiology and chronic health evaluation (APACHE) II score, and simplified acute physiology score (SAPS) II.

Methods

This single-center prospective observational study included 54 adult patients of primary lung disease-induced acute respiratory distress syndrome (ARDS), on invasive ventilation. The primary objective was to correlate LUS score with SOFA score. Secondary objectives were to correlate LUS score with APACHE II and SAPS II scores. LUS score was also correlated with the estimated mortality derived from the above-mentioned scores. A subgroup analysis on COVID-19-positive cases was also carried out. All scores were calculated on the initiation of mechanical ventilation, daily for 7 days or mortality, whichever was earlier.

Results

A significant positive correlation (P < 0.001) was found between LUS and all three severity scores, as well as their corresponding estimated mortality percentages, for all days of the study period, in both non-COVID-19 ARDS patients and in COVID-19 patients. The merit of all four scores in differentiating between the survivor and mortality group for the duration of study also showed significant (P < 0.05) to very significant (P < 0.001) results.

Conclusion

Point-of-care LUS in conjunction with CSSS is a reliable tool for assessing the severity and progression of primary lung disease.

Clinical features and risk factors analysis for poor outcomes of severe community-acquired pneumonia in children: a nomogram prediction model

Background

Pneumonia remains the leading cause of death among children aged 1-59 months. The early prediction of poor outcomes (PO) is of critical concern. This study aimed to explore the risk factors relating to PO in severe community-acquired pneumonia (SCAP) and build a PO-predictive nomogram model for children with SCAP.

Methods

We retrospectively identified 300 Chinese pediatric patients diagnosed with SCAP who were hospitalized in the Affiliated Hospital of Southwest Medical University from August 1, 2018, to October 31, 2021. Children were divided into the PO and the non-PO groups. The occurrence of PO was designated as the dependent variable. Univariate and multivariate logistic regression analyses were used to identify the risk factors of PO. A nomogram model was constructed from the multivariate logistic regression analysis and internally validated for model discrimination and calibration. The performance of the nomogram was estimated using the concordance index (C-index).

Results

According to the efficacy evaluation criteria, 56 of 300 children demonstrated PO. The multivariate logistic regression analysis resulted in the following independent risk factors for PO: co-morbidity (OR: 8.032, 95% CI: 3.556-18.140, P < 0.0001), requiring invasive mechanical ventilation (IMV) (OR: 7.081, 95% CI: 2.250-22.282, P = 0.001), and ALB < 35 g/L (OR: 3.203, 95% CI: 1.151-8.912, P = 0.026). Results of the internal validation confirmed that the model provided good discrimination (concordance index [C-index], 0.876 [95% CI: 0.828-0.925]). The calibration plots in the nomogram model were of high quality.

Conclusion

The nomogram facilitated accurate prediction of PO in children diagnosed with SCAP and could be helpful for clinical decision-making.

Prognostic Nutritional Index (PNI) as a Predictor in Patients with Metabolic Syndrome and Heart Failure

Purpose

There is a lack of research on nutritional status and poor prognosis in patients with metabolic syndrome and heart failure. This study evaluated the relationship between nutritional status as defined by the PNI and adverse outcomes in patients with metabolic syndrome and heart failure.

Methods

A total of 1048 heart failure patients with metabolic syndrome admitted to the Heart Center of the First Affiliated Hospital of Xinjiang Medical University from January 2015 to December 2019 were consecutively. PNI was used to assess their nutritional status.

Results

A total of 51.0% of the patients were in the nonmalnutrition group (PNI≥45), 27.9% were in the mild malnutrition group (40≤PNI<45), and 21.1% of patients were in the malnutrition group (PNI<40). At 36 months of follow-up, after adjusting for other confounding factors, malnutrition (PNI<40) was independently associated with all-cause death (HR: 1.787, 95% CI: 1.451-2.201, P<0.001) and cardiovascular death (HR: 1.837, 95% CI: 1.467-2.301, P<0.001). PNI showed additional prognostic predictive value when included in the established risk factor model, both for all-cause death (AUC: 0.620, 95% CI: 0.579-0.661, P<0.001) and cardiovascular death (AUC: 0.596, 95% CI: 0.555-0.636, P<0.001).

Conclusion

In patients with metabolic syndrome and heart failure, malnutrition assessed by PNI is an independent predictor for all-cause death and cardiovascular death, and PNI is negatively correlated with the occurrence of adverse outcomes.

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.

COVID-19-induced liver injury in infants, children, and adolescents

Coronavirus disease 2019 (COVID-19) typically presents with fever and respiratory symptoms in children. Most children develop an asymptomatic and mild illness, with a minority requiring specialist medical care. Gastrointestinal manifestations and liver injury can also occur in children following infection. The mechanisms of liver injury may include infection following direct viral hepatic tissue invasion, immune response, or medication effects. Affected children might develop mild liver dysfunction which has a benign course in most children with no pre-existing liver disease. However, the presence of non-alcoholic fatty liver disease or other pre-existing chronic liver disorders is associated with a higher risk of developing severe COVID-19 illness with poor outcomes. On the other hand, the presence of liver manifestations is associated with the severity of COVID-19 disease and is considered an independent prognostic factor. Respiratory, hemodynamic, and nutritional supportive therapies are the mainstay of management. Vaccination of children at increased risk of developing severe COVID-19 disease is indicated. This review describes the liver manifestations in children with COVID-19, detailing its epidemiology, basic mechanisms, clinical expression, management, and prognosis in those with and without pre-existing liver disease and also children who have had earlier liver transplantation.

Post-COVID-19 effect on biochemical parameters in children: Should we take heed?

The aim of this research is to analyze the potential impact of the COVID-19 infection on the serum biochemical concentration of children 6 months after recovery from the infection. The study included 72 children with a median age of 11 years. The case group consisted of 37 children who had contracted COVID-19 6 months prior to the analysis. They reported no other pre- or post-covid chronic or systemic diseases. The control group consisted of 35 children who had no prior record of COVID-19 infection. The analysis showed a substantial variation (P = 0.026) in the mean urea values (mmol/L) between the case group (4.513 ± 0.839) and the control group (5.425 ± 1.173). However, both groups' urea levels were within the normal range of their age group. No statistical differences were found analyzing the variations between the two groups in the levels of LDH, AST, ALT, BiliT, GGT, AlbBCG2, CRP, CK, AlKP, UA, Phos, Crea2, Gluc, Ca, Na, K, Cl, TP, TC, TG, and HDL (P > 0.05). The DMFT score was substantially greater (P < 0.002) in the infected team (5.38 ± 2.841) in comparison to the non-infected group (2.6 ± 2.257). The study indicates that COVID-19 infection does not leave biochemical alterations among children who did not have pre-existing conditions. The biochemical analysis suggests that children recover better than adults from COVID-19. Furthermore, it calls for investigating non-lethal COVID-19 infection as a tool to discover underlying conditions. The DMFT score shows a correlation between COVID-19 infection and caries. However, the nature of the correlation is yet to be investigated.

Direct Application of 3-Maleimido-PROXYL for Proving Hypoalbuminemia in Cases of SARS-CoV-2 Infection: The Potential Diagnostic Method of Determining Albumin Instability and Oxidized Protein Level in Severe COVID-19

Oxidative stress and the albumin oxidized form can lead to hypoalbuminemia, which is a predisposing factor for reduced treatment effectiveness and an increased mortality rate in severe COVID-19 patients. The aim of the study is to evaluate the application of free radical 3-Maleimido-PROXYL and SDSL-EPR spectroscopy in the in vitro determination of ox/red HSA in serum samples from patients with SARS-CoV-2 infection. Venous blood was collected from patients intubated (pO₂ < 90%) with a positive PCR test for SARS-CoV-2 and controls. At the 120th minute after the incubation of the serum samples from both groups with the 3-Maleimido-PROXYL, the EPR measurement was started. The high levels of free radicals were determined through the nitroxide radical TEMPOL, which probably led to increased oxidation of HSA and hypoalbuminemia in severe COVID-19. The double-integrated spectra of 3-Maleimido-PROXYL radical showed a low degree of connectivity due to high levels of oxidized albumin in COVID-19 patients. The low concentrations of reduced albumin in serum samples partially inhibit spin-label rotation, with A_max values and ΔH₀ spectral parameters comparable to those of 3-Maleimido-PROXYL/DMSO. Based on the obtained results, we suggest that the stable nitroxide radical 3-Maleimido-PROXYL can be successfully used as a marker to study oxidized albumin levels in COVID-19.

Comparing the predictive values of procalcitonin/albumin ratio and other inflammatory markers in determining COVID-19 severity

Objective

To examine the relationship between COVID-19 severity and procalcitonin/albumin ratio (PAR) and compare the PAR with oft-reported inflammatory markers, including procalcitonin, white blood cell (WBC), neutrophil/lymphocyte ratio (NLR) and C-reactive protein (CRP).

Methods

In this retrospective research study conducted at Sanliurfa Training and Research Hospital during May to September 2020; total, 577 adult subjects diagnosed with COVID-19 were included and categorized into two groups based on place of hospitalization: the intensive care unit (ICU) group (n=151) and the general ward (GW) group (n=426). Laboratory test results and demographic characteristics of the subjects were recorded.

Results

PAR, NLR, CRP, WBC, neutrophil and procalcitonin values were markedly higher in the ICU group than in the GW group. On the contrary, lymphocyte count and albumin level were markedly lower. PAR showed positive correlations with WBC, NLR, and CRP. Multivariate analysis showed that advanced age, presence of hypertension, elevated PAR, WBC, NLR, urea and lactate dehydrogenase levels were independent risk factors associated with the need for intensive care in COVID-19 subjects. Among them, the PAR showed the highest odds ratio (5.564) for ICU admission. Additionally, the area under the ROC curve of the PAR (0.888) was markedly greater than that of WBC (0.777), NLR (0.822), CRP (0.842) and procalcitonin (0.870).

Conclusions

This study revealed that PAR was superior to procalcitonin, WBC, NLR and CRP in determining COVID-19 severity. PAR was an important predictor of ICU requirement in COVID-19 cases.

Liver injury associated with the severity of COVID-19: A meta-analysis

Background

The current 2019 novel coronavirus disease (COVID-19) pandemic is a major threat to global health. It is currently uncertain whether and how liver injury affects the severity of COVID-19. Therefore, we conducted a meta-analysis to determine the association between liver injury and the severity of COVID-19.

Methods

A systematic search of the PubMed, Embase, and Cochrane Library databases from inception to August 12, 2022, was performed to analyse the reported liver chemistry data for patients diagnosed with COVID-19. The pooled odds ratio (OR), weighted mean difference (WMD) and 95% confidence interval (95% CI) were assessed using a random-effects model. Furthermore, publication bias and sensitivity were analyzed.

Results

Forty-six studies with 28,663 patients were included. The pooled WMDs of alanine aminotransferase (WMD = 12.87 U/L, 95% CI: 10.52-15.23, I ² = 99.2%), aspartate aminotransferase (WMD = 13.98 U/L, 95% CI: 12.13-15.83, I ² = 98.2%), gamma-glutamyl transpeptidase (WMD = 20.67 U/L, 95% CI: 14.24-27.10, I ² = 98.8%), total bilirubin (WMD = 2.98 μmol/L, 95% CI: 1.98-3.99, I ² = 99.4%), and prothrombin time (WMD = 0.84 s, 95% CI: 0.46-1.23, I ² = 99.4%) were significantly higher and that of albumin was lower (WMD = -4.52 g/L, 95% CI: -6.28 to -2.75, I ² = 99.9%) in severe cases. Moreover, the pooled OR of mortality was higher in patients with liver injury (OR = 2.72, 95% CI: 1.18-6.27, I ² = 71.6%).

Conclusions

Hepatocellular injury, liver metabolic, and synthetic function abnormality were observed in severe COVID-19. From a clinical perspective, liver injury has potential as a prognostic biomarker for screening severely affected patients at early disease stages.

Systematic review registration

https://www.crd.york.ac.uk/prospero/, Identifier: CRD42022325206.

Efficacy of serum apelin and galectin-3 as potential predictors of mortality in severe COVID-19 patients

Apelin is a cardioprotective biomarker while galectin-3 is a pro-inflammatory and profibrotic biomarker. Endothelial dysfunction, hyperinflammation, and pulmonary fibrosis are key mechanisms that contribute to the development of adverse outcomes in Coronavirus disease 2019 (COVID-19) infection. This study aims to analyze the prognostic value of serum apelin and galectin-3 levels to early predict patients at high risk of mortality in patients hospitalized for severe COVID-19 pneumonia. The study included 78 severe COVID-19 patients and 40 healthy controls. The COVID-19 patients were divided into two groups, survivors and nonsurvivors, according to their in-hospital mortality status. Basic demographic and clinical data of all patients were collected, and blood samples were taken before treatment. In our study, serum apelin levels were determined to be significantly lower in both nonsurvivor and survivor COVID-19 patients compared to the control subjects (for both groups, p < 0.001). However, serum apelin levels were similar in survivor and nonsurvivor COVID-19 patients (p > 0.05). Serum galectin-3 levels were determined to be higher in a statistically significant way in nonsurvivors compared to survivors and controls (for both groups; p < 0.001). Additionally, serum galectin-3 levels were significantly higher in the survivor patients compared to the control subjects (p < 0.001). Positive correlations were observed between galectin-3 and age, ferritin, CK-MB and NT-proBNP variables (r = 0.32, p = 0.004; r = 0.24, p = 0.04; r = 0.24, p = 0.03; and r = 0.33, p = 0.003, respectively) while a negative correlation was observed between galectin-3 and albumin (r = -0.31, p = 0.006). Multiple logistic regression analysis revealed that galectin-3 was an independent predictor of mortality in COVID-19 patients (odds ratio [OR] = 2.272, 95% confidence interval [CI] = 1.106-4.667; p = 0.025). When the threshold value for galectin-3 was regarded as 2.8 ng/ml, it was discovered to predict mortality with 80% sensitivity and 57% specificity (area under the curve = 0.738, 95% CI = 0.611-0.866, p = 0.002). Galectin-3 might be a simple, useful, and prognostic biomarker that can be utilized to predict patients who are at high risk of mortality in severe COVID-19 patients.

COVID-19 and liver injury: An ongoing challenge

The new coronavirus severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) was identified in December 2019, in Wuhan, China. The virus was rapidly spread worldwide, causing coronavirus disease 2019 (COVID-19) pandemic. Although COVID-19 is presented, usually, with typical respiratory symptoms (i.e., dyspnea, cough) and fever, extrapulmonary manifestations are also encountered. Liver injury is a common feature in patients with COVID-19 and ranges from mild and temporary elevation of liver enzymes to severe liver injury and, even, acute liver failure. The pathogenesis of liver damage is not clearly defined; multiple mechanisms contribute to liver disorder, including direct cytopathic viral effect, cytokine storm and immune-mediated hepatitis, hypoxic injury, and drug-induced liver toxicity. Patients with underlying chronic liver disease (i.e., cirrhosis, non-alcoholic fatty liver disease, alcohol-related liver disease, hepatocellular carcinoma, etc.) may have greater risk to develop both severe COVID-19 and further liver deterioration, and, as a consequence, certain issues should be considered during disease management. The aim of this review is to present the prevalence, clinical manifestation and pathophysiological mechanisms of liver injury in patients with SARS-CoV-2 infection. Moreover, we overview the association between chronic liver disease and SARS-CoV-2 infection and we briefly discuss the management of liver injury during COVID-19.

Predictive Nomogram for Hyperprogressive Disease During Anti-PD-1/PD-L1 Treatment in Patients with Advanced Non-Small Cell Lung Cancer

Introduction

Various studies have reported that anti-PD-1/PD-L1 treatment may lead to the rapid development of tumors called hyperprogressive disease (HPD). A nomogram for HPD prediction in NSCLC patients is urgently needed.

Methods

This retrospective cohort study included 176 cases for establishing a model of HPD prediction and 85 cases for validation in advanced NSCLC patients treated with PD-1/PD-L1 inhibitors. HPD was defined as tumor growth rate (TGR, ≥ 2), tumor growth kinetics (TGK, ≥ 2) or time to treatment failure (TTF, ≤ 2 months). Univariate and multivariate logistic regression were used to estimate the specified factors associated with HPD. Then, the nomogram was developed and validated.

Results

Anti-PD-1/PD-L1 therapy resulted in a 9.66% (17/176) incidence of HPD in advanced NSCLC. The overall survival (OS) and progression-free survival (PFS) in patients with HPD were significantly shorter than those in patients without HPD (OS: 7.00 vs 12.00 months, P<0.01; PFS: 2.00 vs 5.00 months, P<0.001, respectively). The HPD prediction nomogram included APTT (P<0.01), CD4+ CD25+ CD127-low cells (Treg cells) (P<0.01), the presence of liver metastasis (P<0.05), and more than two metastatic sites (P<0.05). Then, patients were divided into two groups by the "HPD score" calculated by the nomogram. The C-index was 0.845, while the area under the curve (AUC) was 0.830 (sensitivity 75.00%, specificity 91.70%). The calibration plot of HPD probability showed an optimal agreement between the actual observation and prediction by the nomogram. In the validation cohort, the AUC was up to 0.960 (sensitivity 88.70%, specificity 89.80%).

Conclusions

The nomogram was constructed with the presence of liver metastasis, more than two metastatic sites, lengthened APTT and a high level of Treg cells, which could be used to predict HPD risk.

Liver disease during the pandemic of COVID-19 infection: prediction of the course and tactics of management: A review

The hepatic consequences of SARS-CoV-2 infection are now recognized as an important component of CoronaVIrus Disease 2019 (COVID-19). This aspect is most clinically relevant in patients with pre-existing chronic liver disease (CKD), who are at extremely high risk of severe COVID-19 and death. Risk factors for severe CKD, especially in people with liver cirrhosis and non-alcoholic fatty liver disease, are the direct and indirect cytotoxic effects of coronavirus against the background of systemic inflammation, blood clotting disorders and immune dysfunction. The severe negative impact of the pandemic in the presence of CKD and the difficulties of patient relationships contribute to the progressive increase in the global burden of liver disease on the health system.

Liver injury in COVID-19: A minireview

Coronavirus disease 2019 (COVID-19), caused by infection with the severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), has escalated into a global tragedy afflicting human health, life, and social governance. Through the increasing depth of research and a better understanding of this disease, it has been ascertained that, in addition to the lungs, SARS-CoV-2 can also induce injuries to other organs including the liver. Liver injury is a common clinical manifestation of COVID-19, particularly in severe cases, and is often associated with a poorer prognosis and higher severity of COVID-19. This review focuses on the general existing information on liver injury caused by COVID-19, including risk factors and subpopulations of liver injury in COVID-19, the association between preexisting liver diseases and the severity of COVID-19, and the potential mechanisms by which SARS-CoV-2 affects the liver. This review may provide some useful information for the development of therapeutic and preventive strategies for COVID-19-associated liver injury.

The correlation between COVID-19 segmentation volume based on artificial intelligence technology and gastric wall edema: a multi-center study in Wuhan

PURPOSE

This study aimed to investigate manifestations of the gastric wall and related risk factors in COVID-19 patients with gastrointestinal symptoms by CT.

MATERIALS AND METHODS

Two hundred and forty patients diagnosed with COVID-19 by RT-PCR were enrolled from January 2020 to April 2020. Patients showed gastrointestinal symptoms, including nausea, vomiting, or diarrhea. Results of the initial laboratory examination were performed after admission. Chest CT was performed for all patients, with the lower bound including the gastric antrum. The volume of COVID-19 and lungs was segmented, and the ratio was calculated as follows: PV/LV = Volume_pneumonia/Volume_lungs.

RESULTS

Among the 240 patients, 109 presented with gastric wall edema (edema group), and 131 showed no gastric wall edema (non-edema group); the PV/LV values between the two groups were significantly different (P = 0.002). Univariate analysis revealed the following: fibrinogen (Fib), thrombin time (TT), activated partial thromboplastin time (APTT), and albumin (ALB) significantly differed between the two groups (P < 0.05). Binary logistic regression analysis showed that only APTT had a negative effect on gastric wall edema (P = 0.003).

CONCLUSIONS

SARS-CoV-2 invades the gastrointestinal tract, gastric wall edema is the primary CT manifestation, and gastric wall edema is more likely to occur with a shorter APTT and severe pneumonia, with a slightly longer hospitalization time. Patients with gastric wall edema observed by CT should intervene early, which may improve digestive function, and further strengthen immune potency against COVID-19.

The Predictive Score for Patients Hospitalized With COVID-19 in Resource-Limited Settings

Background and aims The second wave of coronavirus disease 2019 (COVID-19) has been devastating in India and many developing countries. The mortality reported has been 40% higher than in the first wave, overwhelming the nation's health infrastructure. Despite a better understanding of the disease and established treatment protocols including steroids and heparin, the second wave was disastrous. Subsequent waves have the potential to further cripple healthcare deliveries, also affecting non-COVID-19 care across many developing economies. It is then important to identify and triage high-risk patients to best use the limited resources. Routine tests such as neutrophil and monocyte counts have been identified but have not been successfully validated uniformly, and their utility is still being understood in COVID-19. Various predictive models that are available require online resources and calculators and additionally await validation across all populations. These, although useful, might not be available or accessible across all institutions. It is then important to identify easy-to-use scores that utilize tests done routinely. In identifying with this goal, we did a retrospective review of the institutional database to identify potential predictors of intensive care unit (ICU) admission and mortality in patients hospitalized during the second wave who accessed healthcare at our academic setup. Results Three predictors of mortality and four predictors of ICU admission were identified. Absolute neutrophil count was a common predictor of both ICU admission and mortality but with two separate cut points. An absolute neutrophil count of >4,200 predicted need for ICU admission (odds ratio (OR): 3.1 (95% confidence interval (CI): 2.0, 4.8)), and >7,200 predicted mortality (adjusted OR: 4.2 (95% CI: 1.9, 9.4)). We observed that a blood urea level greater than 45 was predictive of needing ICU care (adjusted OR: 8.0 (95% CI: 3.7, 17.6)). In our dataset, serum ferritin of >500 was predictive of ICU admission (adjusted OR: 2.7 (95% CI: 1.2, 5.9)). We noted a right shift of partial pressure (p50 is the oxygen tension at which hemoglobin is 50% saturated) (p50c) in SARS-CoV-2 as a predictor of ICU care (OR: 2.6 (95% CI: 1.7, 3.9)) when partial pressure is >26.5. In our analysis, a serum protein of less than 7 g/dL (OR: 2.8 (95% CI: 1.7, 4.4)) was a predictive variable for ICU admission. An LDH value of >675 was predictive of severity with a need for ICU admission (OR: 9.2 (95% CI: 5.4, 15.5)) in our series. We then assigned a score to each of the predictive variables based on the adjusted odds ratio. Conclusion We identified a set of easy-to-use predictive variables and scores to recognize the subset of patients hospitalized with COVID-19 with the highest risk of death or clinical worsening requiring ICU care.

The clinical course and risk factors in COVID-19 patients with acute kidney injury

Background

Acute kidney injury (AKI) has the most prevalent complications in COVID-19 patients. A variety of factors is involved in the disease progression and its associated outcomes. The present study aimed at both examining the correlated clinical features of COVID-19 disease and AKI and evaluating its clinical outcomes.

Materials and Methods

In the present retrospective study, 102 COVID-19 patients that encountered AKI were enrolled and categorized into three AKI stages. Basic and clinical characteristics, clinical signs and symptoms, laboratory and imaging findings, and treatment approaches were examined. Then, clinical outcomes as well as the factors associated with the mortality of patients were evaluated.

Results

Diabetes was the only significant clinical characteristic among the patients (P = 0.004). An increasing trend was observed for neutrophil-to-lymphocyte ratio (P = 0.027) and potassium (K) (P = 0.006), and a decreasing trend was seen for hemoglobin (P < 0.001), albumin (P = 0.005), and calcium (P < 0.001) factors at higher stages of AKI. Secondary infection (P = 0.019) and hypoproteinemia (P = 0.018) were the most significant clinical outcomes. Chronic obstructive lung disease (OR = 1.362, P = 0.007), renal replacement therapy (OR = 2.067, P = 0.005), lung consolidation (OR = 0.722, P = 0.032), and bilateral pulmonary infiltration (OR = 4.793, P = 0.002) were the factors associated with mortality rate of COVID-19 patients with AKI.

Conclusion

AKI, as an important complication of COVID-19, that can predict the higher mortality rate as well as the laboratory and clinical characteristics should receive more due consideration in order to employ proper preventive or supportive treatment approaches that are the pivotal key to reduce the mortality rate in target patients.

The incidence of acute kidney injury and its association with mortality in patients diagnosed with COVID-19 followed up in intensive care unit

INTRODUCTION

The kidneys are some of the most frequently affected organs during coronavirus disease 2019 (COVID-19). This multicenter study evaluated the incidence of and risk factors for acute kidney injury (AKI) in COVID-19 patients followed up in intensive care unit (ICU) and its association with mortality.

METHODS

Three hundred twenty-eight patients diagnosed with COVID-19 and hospitalized in ICU were included. Risk factors associated with AKI and mortality were evaluated.

RESULTS

Eighty-eight patients (27.9%) were diagnosed with AKI. AKI was significantly associated with older age, higher baseline creatinine level, lower albumin level, and coexistence of cardiovascular disease and chronic obstructive pulmonary disease. Mortality in the entire study group was significantly associated with AKI, older age, requirement of invasive mechanical ventilation, higher neutrophil level, lower lymphocyte, and albumin levels.

CONCLUSION

AKI is frequently seen during the course of COVID-19 and is associated with high mortality. Identifying AKI-related risk factors appears essential in the management of COVID-19 patients.

The change in nutritional status is related to cardiovascular events in patients with pacemaker implantation: A 4-year follow-up study

Background

The aim of our study was to evaluate changes in nutritional status as measured by the prognostic nutritional index (PNI) and geriatric nutritional risk index (GNRI) scores, and their abilities to predict clinical prognosis in patients with pacemaker implantation (PMI).

Methods

A total of 595 patients who underwent permanent PMI from January 2011 to December 2020 were included. PNI and GNRI scores were separately calculated at the beginning day of PMI operation and at the end of 12-month follow-up, and their net changes (Δ) were calculated by PNI or GNRI scores at follow-up minus the corresponding scores on admission. The cohort patients were divided into low risk of malnutritional status (ΔPNI or ΔGNRI scores ≥ 0) and high risk of malnutritional status (ΔPNI or ΔGNRI scores < 0) groups. Primary outcome measure was a composite major adverse cardiovascular event (MCE), defined as heart failure hospitalization (HFH), myocardial infarction (MI), stroke, or death from any cause, presented as hazard ratios (HR) with 95% confidence intervals (CI) calculated by MCE in the crude or multivariate-adjusted Cox Proportional Hazards models. Receiver operating characteristic (ROC) curve analysis was used to compare the differential ability to predict incident MCEs betweenΔPNI andΔGNRI scores.

Results

In total, 16% of patients developed the MCE during the follow-up. The cumulative event rates determined by Kaplan–Meier analysis were significantly higher in the high risk of malnutritional patients compared to the low risk of malnutritional patients (P < 0.05). Adjusted multivariate analysis showed that decreased PNI scores (HR: 2.228, 95% CI: 1.482–3.350) and decreased GNRI scores (HR: 2.178, 95% CI: 1.439–3.295) were independently associated with favorable outcomes. ROC curve analysis revealed an area under curve (AUC) of 0.586 forΔPNI scores and AUC of 0.592 for ΔGNRI scores, but their predictive abilities were not statistically different.

Conclusion

Either positive change of PNI or GNRI scores were associated with reduced risk of MCEs in patients with PMI, and they have similar ability to predict clinical cardiometabolic risk. Additional enhancing nutritional status during follow-up may help to prevent unfavorable prognosis in clinical practices.

Inadequate energy and protein intake, underweight and malnutrition are associated with in-hospital mortality among COVID-19 rehabilitation patients during the omicron outbreak in Hong Kong

Objective

Malnourished COVID-19 patients were prone to higher mortality and longer length of stay (LOS). This study aims to investigate the malnutrition risk prevalence in the COVID-19 patients and how other nutritional indicators are related to the clinical outcomes in a rehabilitation hospital.

Methods

A retrospective cross-sectional study involved 174 COVID-19 patients during the rehabilitation phase. Malnutrition risk, nutritional indicators, mortality, and LOS were compared among different risk groups. Albumin, nutrition intake, and body mass index (BMI) were investigated for their effects on the clinical outcomes.

Results

The prevalence of malnutrition risk was 94.9%; those older were higher in malnutrition risk. BMI, energy and protein intakes decreased as the malnutrition risk increased. Albumin, energy and protein intakes were lower in the death group. The high malnutrition risk group and severely underweight patients had 2.7 times and 2.2 times higher in-hospital death, respectively. For subjects ≥75 years old, the odds ratio to death was 6.2 compared to those <75 years old.

Conclusion

We observed a high malnutrition risk of 94.9% in COVID-19 patients. Patients with malnutrition risk had a lower BMI, lower nutritional intake, and a higher chance of in-hospital death. These results reinforced the importance of nutrition management in COVID-19 patients.

What is the role of prognostic indexes in COVID-19 patients with diabetes mellitus? Data of patients from Turkey

Aim: We aimed to determine the prognostic performance of the Glasgow Prognostic Score (GPS), systemic immune-inflammation index and early warning score (the 'ANDC' system) in patients with diabetes mellitus who had COVID-19. Patients & methods: Patients were divided into two groups: with and without diabetes mellitus. Results: In the diabetic patient group, the rates of in-hospital mortality, intensive care unit hospitalization and corticosteroid treatment were higher compared with the nondiabetic patient group (p < 0.05). A GPS of 2 was useful for predicting in-hospital mortality in diabetic patients (p < 0.05). The ANDC score was significantly higher in diabetic patients (p < 0.05) and in diabetic patients with mortality and those who needed ICU hospitalization (p < 0.05). Conclusion: The presence of a GPS of 2 at the time of admission and a high ANDC value were associated with poor prognosis in diabetic COVID-19 patients.

The Potential Role of Growth Differentiation Factor 15 in COVID-19: A Corollary Subjective Effect or Not?

Coronavirus disease 2019 (COVID-19) is primarily caused by various forms of severe acute respiratory syndrome coronavirus type 2 (SARS-CoV-2) variants. COVID-19 is characterized by hyperinflammation, oxidative stress, multi-organ injury (MOI)-like acute lung injury (ALI) and acute respiratory distress syndrome (ARDS). Different biomarkers are used in the assessment of COVID-19 severity including D-dimer, ferritin, lactate dehydrogenase (LDH), and hypoxia-inducible factor (HIF). Interestingly, growth differentiation factor 15 (GDF15) has recently become a potential biomarker correlated with the COVID-19 severity. Thus, this critical review aimed to determine the critical association between GDF15 and COVID-19. The perfect function of GDF15 remains not well-recognized; nevertheless, it plays a vital role in controlling cell growth, apoptosis and inflammatory activation. Furthermore, GDF15 may act as anti-inflammatory and pro-inflammatory signaling in diverse cardiovascular complications. Furthermore, the release of GDF15 is activated by various growth factors and cytokines including macrophage colony-stimulating factor (M-CSF), angiotensin II (AngII) and p53. Therefore, higher expression of GDF15 in COVID-19 might a compensatory mechanism to stabilize and counteract dysregulated inflammatory reactions. In conclusion, GDF15 is an anti-inflammatory cytokine that could be associated with the COVID-19 severity. Increased GDF15 could be a compensatory mechanism against hyperinflammation and exaggerated immune response in the COVID-19. Experimental, preclinical and large-scale clinical studies are warranted in this regard.

The relationship between hematocrit and serum albumin levels difference and mortality in elderly sepsis patients in intensive care units-a retrospective study based on two large database

BACKGROUND

Sepsis still threatens the lives of more than 300 million patients annually and elderly patients with sepsis usually have a more complicated condition and a worse prognosis. Existing studies have shown that both Hematocrit (HCT) and albumin (ALB) can be used as potential predictors of sepsis, and their difference HCT-ALB has a significant capacity to diagnose infectious diseases. Currently, there is no relevant research on the relationship between HCT-ALB and the prognosis of elderly sepsis patients. Therefore, this study aims to explore the association between HCT-ALB and mortality in elderly patients with sepsis.

METHODS

This study was a multi-center retrospective study based on the Medical Information Mart for Intensive Care (MIMIC-IV) database and the eICU Collaborative Research Database (eICU-CRD) in elderly patients with sepsis. The optimal HCT-ALB cut-off point for ICU mortality was calculated by the Youden Index based on the eICU-CRD dataset, and multivariate logistic regressions were conducted to explore the association between HCT-ALB and ICU/hospital mortality in the two databases. Subgroup analyses were performed for different parameters and comorbidity status.

RESULTS

The number of 16,127 and 3043 elderly sepsis patients were selected from two large intensive care databases (eICU-CRD and MIMIC-IV, respectively) in this study. Depending on the optimal cut-off point, patients in both eICU-CRD and MIMIC-IV were independently divided into low HCT-ALB (< 6.7) and high HCT-ALB (≥ 6.7) groups. The odds ratio (95%confidence interval) [OR (95CI%)] of the high HCT-ALB group were 1.50 (1.36,1.65) and 1.71 (1.58,1.87) for ICU and hospital mortality in the eICU-CRD database after multivariable adjustment. Similar trends in the ICU and hospital mortality [OR (95%CI) 1.41 (1.15,1.72) and 1.27 (1.07,1.51)] were observed in MIMIC-IV database. Subgroup analysis showed an interaction effect with SOFA score in the eICU-CRD database however not in MIMIC-IV dataset.

CONCLUSIONS

High HCT-ALB (≥ 6.7) is associated with 1.41 and 1.27 times ICU and hospital mortality risk in elderly patients with sepsis. HCT-ALB is simple and easy to obtain and is a promising clinical predictor of early risk stratification for elderly sepsis patients in ICU.

Development of novel spectroscopic and machine learning methods for the measurement of periodic changes in COVID-19 antibody level

In this research, blood samples of 47 patients infected by COVID were analyzed. The samples were taken on the 1st, 3rd and 6th month after the detection of COVID infection. Total antibody levels were measured against the SARS-CoV-2 N antigen and surrogate virus neutralization by serological methods. To differentiate COVID patients with different antibody levels, Fourier Transform InfraRed (FTIR) and Raman spectroscopy methods were used. The spectroscopy data were analyzed by multivariate analysis, machine learning and neural network methods. It was shown, that analysis of serum using the above-mentioned spectroscopy methods allows to differentiate antibody levels between 1 and 6 months via spectral biomarkers of amides II and I. Moreover, multivariate analysis showed, that using Raman spectroscopy in the range between 1317 cm-1 and 1432 cm-1, 2840 cm-1 and 2956 cm-1 it is possible to distinguish patients after 1, 3, and 6 months from COVID with a sensitivity close to 100%.

Association between sleep duration and albumin in US adults: a cross-sectional study of NHANES 2015-2018

BACKGROUND

Albumin has multiple functions and is used in the clinical assessment of liver function, kidney function and nutritional status. However, few epidemiological studies have evaluated the association between sleep duration and albumin. Therefore, we carried out a cross-sectional study to address this issue. The aim of the study was to investigate the association between sleep duration and albumin in American adults based on the NHANES (National Health and Nutrition Examination Survey).

METHODS

A total of 9,973 participants aged [Formula: see text] 20 years were included in this study from NHANES 2015-2018. Weighted data were calculated according to analytical guidelines. Linear regression models and smooth curve fitting were used to assess and describe the relationship between sleep duration and albumin. The inflection point was determined by a two-step recursive method. Moreover, univariate and stratified analyses were performed.

RESULTS

There was an inverted U-shaped association between sleep duration and albumin levels. Albumin levels were highest when the sleep duration was 7.5 h. Compared to 7-8 h of sleep, short sleep duration was linked to lower albumin levels [sleep duration [Formula: see text] 5 h: β [Formula: see text]-1.00, 95% CI (-1.26, -0.74), P < 0.0001]. Compared to 7-8 h of sleep, long sleep duration was related to lower albumin levels [sleep duration [Formula: see text] 9 h: β [Formula: see text] -0.48, 95% CI (-0.68, -0.27), P < 0.0001].

CONCLUSIONS

Sleep duration had an inverted U-shaped relationship with albumin, with short or long sleep duration associated with significantly lower albumin levels.

Prognostic value of albumin-to-globulin ratio in COVID-19 patients: A systematic review and meta-analysis

Background and aims

The albumin-to-globulin ratio (AGR) has been used to predict severity and mortality in infectious diseases. The aim of this study is to evaluate the prognostic value of the AGR in COVID-19 patients.

Methods

A systematic review and meta-analysis were conducted. We included observational studies assessing the association between the AGR values upon hospital admission and severity or all-cause mortality in COVID-19 patients. In the meta-analyses we used random effect models. Risk of bias was assessed using the Newcastle-Ottawa Scale (NOS). The effect measures were expressed as mean difference (MD) and their 95% confidence intervals (CI). We performed Egger's test and funnel plots to assess the publication bias.

Results

The included studies had a total of 11356 patients corresponding to 31 cohort studies. Severe COVID-19 patients had lower AGR values than non-severe COVID-19 patients (mean difference (MD), −0.27; 95% IC, −0.32 to −0.22; p < 0.001; I² = 88%). Non-survivor patients with COVID-19 had lower AGR values than survivor patients (MD, −0.29; 95% IC, −0.35 to −0.24; p < 0.001; I² = 79%). In the sensitivity analysis, we only included studies with low risk of bias, which decreased the heterogeneity for both outcomes (severity, I² = 20%; mortality, I² = 5%).

Conclusions

Low AGR values upon hospital admission were found in COVID-19 patients with a worse prognosis.

Identification of serum metabolites enhancing inflammatory responses in COVID-19

Coronavirus disease 2019 (COVID-19), caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), is characterized by a strong production of inflammatory cytokines such as TNF and IL-6, which underlie the severity of the disease. However, the molecular mechanisms responsible for such a strong immune response remains unclear. Here, utilizing targeted tandem mass spectrometry to analyze serum metabolome and lipidome in COVID-19 patients at different temporal stages, we identified that 611 metabolites (of 1,039) were significantly altered in COVID-19 patients. Among them, two metabolites, agmatine and putrescine, were prominently elevated in the serum of patients; and 2-quinolinecarboxylate was changed in a biphasic manner, elevated during early COVID-19 infection but levelled off. When tested in mouse embryonic fibroblasts (MEFs) and macrophages, these 3 metabolites were found to activate the NF-κB pathway that plays a pivotal role in governing cytokine production. Importantly, these metabolites were each able to cause strong increase of TNF and IL-6 levels when administered to wildtype mice, but not in the mice lacking NF-κB. Intriguingly, these metabolites have little effects on the activation of interferon regulatory factors (IRFs) for the production of type I interferons (IFNs) for antiviral defenses. These data suggest that circulating metabolites resulting from COVID-19 infection may act as effectors to elicit the peculiar systemic inflammatory responses, exhibiting severely strong proinflammatory cytokine production with limited induction of the interferons. Our study may provide a rationale for development of drugs to alleviate inflammation in COVID-19 patients.

SARS-CoV-2 Spike Protein Binding of Glycated Serum Albumin-Its Potential Role in the Pathogenesis of the COVID-19 Clinical Syndromes and Bias towards Individuals with Pre-Diabetes/Type 2 Diabetes and Metabolic Diseases

The immune response to SARS-CoV-2 infection requires antibody recognition of the spike protein. In a study designed to examine the molecular features of anti-spike and anti-nucleocapsid antibodies, patient plasma proteins binding to pre-fusion stabilised complete spike and nucleocapsid proteins were isolated and analysed by matrix-assisted laser desorption ionisation–time of flight (MALDI-ToF) mass spectrometry. Amongst the immunoglobulins, a high affinity for human serum albumin was evident in the anti-spike preparations. Careful mass comparison revealed the preferential capture of advanced glycation end product (AGE) forms of glycated human serum albumin by the pre-fusion spike protein. The ability of bacteria and viruses to surround themselves with serum proteins is a recognised immune evasion and pathogenic process. The preference of SARS-CoV-2 for AGE forms of glycated serum albumin may in part explain the severity and pathology of acute respiratory distress and the bias towards the elderly and those with (pre)diabetic and atherosclerotic/metabolic disease.

The Association Between the Albumin and Viral Negative Conversion Rate in Patients Infected with Novel Coronavirus Disease 2019 (COVID-19)

Purpose

The novel coronavirus disease 2019 (COVID-19) epidemic is the severe global pandemic with large numbers of infected cases and deaths in recent decades. The previous studies were all about the influence of albumin (ALB) for the severity and mortality of in-patients infected with COVID-19. But few studies exist about the influence factors to achieve viral negative conversion. Therefore, this study conducted an exploratory study to investigate the effect of albumin on negative conversion rate.

Methods

Among the 190 hospitalized patients with moderate COVID-19 who had a course of disease longer than 30 days, 102 achieved viral negative conversion in 30–45 days and 88 not after 45 days. Taking other variables as concomitant variable, Cox proportional hazard regression model was applied to explore the influence of albumin to negative conversion rate under various factors.

Results

By comparing patients who could and could not achieve the finally viral negative conversion, a possible nonlinear relationship between the continuous variables and clinical outcomes was examined by a restricted cubic spline regression model. An association was found between albumin levels and hazard ratio of viral negative conversion rate (P = 0.027). The increase of albumin was accompanied with decreases of hazard ratio of viral negative conversion rate (the value of albumin <38 g/L). But when the value of albumin was higher than 38 g/L, the hazard ratio of viral negative conversion rate approached 1, it means that albumin is not a risk factor for the viral negative conversion rate of COVID-19 disease.

Conclusion

For patients with COVID-19, albumin is a common and observed laboratory parameter. It is associated with final viral negative conversion rate although its underlying mechanism and relationship with the viral negative conversion rate still need to be clarified.

Research Progress and Treatment Status of Liver Cirrhosis with Hypoproteinemia

Liver cirrhosis is the 14th leading cause of death in adults worldwide. The liver is an important organ for the metabolism of sugar, protein, and fat. Liver cirrhosis with hypoproteinemia (LCH) can lead to metabolic disorders of the nutrients such as sugar, protein, and fat, as well as insufficient protein intake, digestion and absorption disorders, and continuous leakage of plasma protein into the abdominal cavity. Severe hypoproteinemia leads to a poor prognosis in patients. For every 10 g/L decrease in peripheral blood albumin, the risk of secondary liver disease complications will increase by 89% and the mortality rate increased by 24%–56%. Therefore, it is necessary to take urgent measures to treat liver cirrhosis with hypoalbuminemia and effectively treat and reverse the deterioration of the disease caused by hypoalbuminemia, so as to reduce the burden of secondary liver disease. Emerging evidence suggests that protein balance disorders, auxin resistance, and hyperleptinemia are key steps in the development of cirrhosis and hypoproteinemia. This study comprehensively analyzed the common complications, pathogenic mechanisms, and treatment status of cirrhosis caused by hypoproteinemia and proposed research prospects for dealing with this increasingly serious problem.

Serum albumin levels monitoring in ICU in early days and mortality risk association in patients with moderate to severe COVID-19 pneumonia

Objective

To establish correlation between serum albumin during early days of ICU admission and risk of death in COVID-19 pneumonia.

Methods

In this retrospective study, we included 76 patients hospitalized in ICU, who stayed for at least four days with COVID-19 pneumonia, from May 1, 2020 to June 30, 2020 in Lahore Health Care Hospital and Al-Shafi Hospital. Patients were labelled as COVID-19 pneumonia on radiological basis as bilateral 'ground-glass opacity' in lower zones and RT-PCR positive result in nasopharyngeal swab. All patients were oxygen dependent, either on high flow oxygen via non rebreathing mask or invasive positive pressure ventilation support. Serum albumin levels were measured daily from first day to fourth day of ICU admission. The data was analyzed using SPSS version 26 and Microsoft excel 2016.

Results

Out of 76 patients of COVID-19 pneumonia admitted in ICU who stayed for more than four days, 38 patients expired. The mean age of all the patients was 58.9±12.56 years, 38(50%) of the patients were ≥60 years and 49 (62%) of them were male. On day four of ICU admission, mean serum albumin of discharged patients was 3.83±0.22 g/dl while mean serum albumin level of expired patients was 2.96±0.46 g/dl. Strong negative correlation (r = -767) was found between decrease in serum albumin level and increase number of deaths from COVID-19 pneumonia. Weak correlation was observed between increase in serum CRP and increase number of deaths in the same patients.

Conclusion

Daily monitoring of serum albumin level of COVID-19 pneumonia patients can be used as a biological marker for monitoring of cytokine storm and risk of death in COVID-19 pneumonia.

The Interplay Between Stress and Immunity Triggers Herpes Zoster Infection in COVID-19 Patients: A Review

Coronavirus disease 2019 (COVID-19) is a potential health threat in the highly mobile society of the world. Also, there are concerns regarding the co-infections occurring in COVID-19 patients. Herpes zoster (HZ) is now being reported as a co-infection in COVID-19 patients. It is a varicella-zoster virus induced viral infection affecting older people and immunocompromised individuals. Reactivation of HZ infection in COVID-19 patients are emerging and the mechanism of reactivation is still unknown. A most convincing argument would be, increased psychological and immunological stress leading to HZ in COVID-19 patients, and this review justifies this argument.

Galectin-3 as a potential prognostic biomarker of severe COVID-19 in SARS-CoV-2 infected patients

Severe COVID-19 is associated with a systemic hyperinflammatory response leading to acute respiratory distress syndrome (ARDS), multi-organ failure, and death. Galectin-3 is a ß-galactoside binding lectin known to drive neutrophil infiltration and the release of pro-inflammatory cytokines contributing to airway inflammation. Thus, we aimed to investigate the potential of galectin-3 as a biomarker of severe COVID-19 outcomes. We prospectively included 156 patients with RT-PCR confirmed COVID-19. A severe outcome was defined as the requirement of invasive mechanical ventilation (IMV) and/or in-hospital death. A non-severe outcome was defined as discharge without IMV requirement. We used receiver operating characteristic (ROC) and multivariable logistic regression analysis to determine the prognostic ability of serum galectin-3 for a severe outcome. Galectin-3 levels discriminated well between severe and non-severe outcomes and correlated with markers of COVID-19 severity, (CRP, NLR, D-dimer, and neutrophil count). Using a forward-stepwise logistic regression analysis we identified galectin-3 [odds ratio (OR) 3.68 (95% CI 1.47-9.20), p < 0.01] to be an independent predictor of severe outcome. Furthermore, galectin-3 in combination with CRP, albumin and CT pulmonary affection > 50%, had significantly improved ability to predict severe outcomes [AUC 0.85 (95% CI 0.79-0.91, p < 0.0001)]. Based on the evidence presented here, we recommend clinicians measure galectin-3 levels upon admission to facilitate allocation of appropriate resources in a timely manner to COVID-19 patients at highest risk of severe outcome.

Prolonged Impairment of Short-Chain Fatty Acid and L-Isoleucine Biosynthesis in Gut Microbiome in Patients With COVID-19

BACKGROUND AND AIMS

Coronavirus disease 2019 (COVID-19) caused by severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection is associated with altered gut microbiota composition. Phylogenetic groups of gut bacteria involved in the metabolism of short chain fatty acids (SCFAs) were depleted in SARS-CoV-2-infected patients. We aimed to characterize a functional profile of the gut microbiome in patients with COVID-19 before and after disease resolution.

METHODS

We performed shotgun metagenomic sequencing on fecal samples from 66 antibiotics-naïve patients with COVID-19 and 70 non-COVID-19 controls. Serial fecal samples were collected (at up to 6 times points) during hospitalization and beyond 1 month after discharge. We assessed gut microbial pathways in association with disease severity and blood inflammatory markers. We also determined changes of microbial functions in fecal samples before and after disease resolution and validated these functions using targeted analysis of fecal metabolites.

RESULTS

Compared with non-COVID-19 controls, patients with COVID-19 with severe/critical illness showed significant alterations in gut microbiome functionality (P < .001), characterized by impaired capacity of gut microbiome for SCFA and L-isoleucine biosynthesis and enhanced capacity for urea production. Impaired SCFA and L-isoleucine biosynthesis in gut microbiome persisted beyond 30 days after recovery in patients with COVID-19. Targeted analysis of fecal metabolites showed significantly lower fecal concentrations of SCFAs and L-isoleucine in patients with COVID-19 before and after disease resolution. Lack of SCFA and L-isoleucine biosynthesis significantly correlated with disease severity and increased plasma concentrations of CXCL-10, NT- proB-type natriuretic peptide, and C-reactive protein (all P < .05).

CONCLUSIONS

Gut microbiome of patients with COVID-19 displayed impaired capacity for SCFA and L-isoleucine biosynthesis that persisted even after disease resolution. These 2 microbial functions correlated with host immune response underscoring the importance of gut microbial functions in SARS-CoV-2 infection pathogenesis and outcome.

Albumin Binds COVID-19 Spike 1 Subunit and Predicts In-Hospital Survival of Infected Patients—Possible Alteration by Glucose

(1) Background: This study aimed to analyze if the serum albumin levels of hospitalized SARS-CoV-2 (COVID-19) patients on admission could predict <30 days in-hospital all-cause mortality, and if glucose levels on admission affected this predictive ability. (2) Methods: A multicenter retrospective cohort of 1555 COVID-19-infected adult patients from public hospitals of the Madrid community were analyzed. (3) Results: Logistic regression analysis showed increased mortality for ages higher than 49 y. After adjusting for age, comorbidities and on-admission glucose levels, it was found that on-admission serum albumin ≥3.5 g/dL was significantly associated with reduced mortality (OR 0.48; 95%CI:0.36–0.62). There was an inverse concentration-dependent association between on-admission albumin levels and <30 days in-hospital all-cause mortality. However, when on-admission glucose levels were above 125 mg/dL, higher levels of serum albumin were needed to reach an association with survival. In vitro experiments showed that the spike protein S1 subunit of SARS-CoV-2 binds to native albumin. The binding ability of native albumin to the spike protein S1 subunit was decreased in the presence of an increasing concentration of glycated albumin. (4) Conclusions: On-admission serum albumin levels were inversely associated with <30 days in-hospital all-cause mortality. Native albumin binds the spike protein S1 subunit, suggesting that native albumin may act as a scavenger of the SARS-CoV-2 virus.

Adjuvant Therapy System of COVID-19 Patient: Integrating Warning, Therapy, Post-Therapy Psychological Intervention

The 2019 novel coronavirus(COVID-19) spreads rapidly, and the large-scale infection leads to the lack of medical resources. For the purpose of providing more reasonable medical service to COVID-19 patients, we designed an novel adjuvant therapy system integrating warning, therapy, and post-therapy psychological intervention. The system combines data analysis, communication networks and artificial intelligence(AI) to design a guidance framework for the treatment of COVID-19 patients. Specifically, in this system, we first can use blood characteristic data to help make a definite diagnosis and classify the patients. Then, the classification results, together with the blood characteristics and underlying diseases disease characteristics of the patient, can be used to assist the doctor in treat treating the patient according to AI algorithms. Moreover, after the patient is discharged from the hospital, the system can monitor the psychological and physiological state at the data collection layer. And in the data feedback layer, this system can analyze the data and report the abnormalities of the patient to the doctor through communication network. Experiments show the effectiveness of our proposed system.