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

Spectrochemical and explainable artificial intelligence approaches for molecular level identification of the status of critically ill patients with COVID-19

This study explores the molecular alterations and disease progression in COVID-19 patients using ATR-FTIR spectroscopy combined with spectrochemical and explainable artificial intelligence (XAI) approaches. Blood serum samples from intubated patients (IC), those receiving hospital services (SC), and recovered patients (PC) were analyzed to identify potential spectrochemical serum biomarkers. Spectrochemical parameters such as lipid, protein, nucleic acid concentrations, and IgG glycosylation were quantified, revealing significant alterations indicative of disease severity. Notably, increased lipid content, altered protein concentrations, and enhanced protein phosphorylation were observed in IC patients compared to SC and PC groups. The serum AGR (Albumin/Globulin Ratio) index demonstrated a distinct shift among patient groups, suggesting its potential as a rapid biochemical marker for COVID-19 severity. Additionally, alterations in IgG glycosylation and glucose concentrations were associated with disease severity. Spectral analysis highlighted specific bands indicative of nucleic acid concentrations, with notable changes observed in IC patients. XAI techniques further elucidated the importance of various spectral features in predicting disease severity across patient categories, emphasizing the heterogeneity of COVID-19's impact. Overall, this comprehensive approach provides insights into the molecular mechanisms underlying COVID-19 pathogenesis and offers a transparent and interpretable prediction algorithm to aid decision-making and patient management.

Association of vitamin B12, folate, and homocysteine with COVID-19 severity and mortality: A systematic review and meta-analysis

Objective

We aimed to review the available evidence on the association between vitamin B12, folate, and homocysteine levels with worse outcomes among COVID-19 patients.

Methods

The search was carried out in ten databases simultaneously run on 10 May 2023, without language restrictions. We included cross-sectional, case-control, and cohort studies. The random-effects meta-analysis was performed using the Sidik-Jonkman method and corrected 95% confidence intervals using the truncated Knapp-Hartung standard errors. Standardized mean difference and 95% CI was used as the measure effect size.

Results

Thirteen articles were included in this review (n = 2134). Patients with COVID-19 who did not survive had the highest serum vitamin B12 values (SMD: 1.05; 95% CI: 0.31-1.78; p = 0.01, I2 = 91.22%). In contrast, low serum folate values were associated with patients with severe COVID-19 (SMD: -0.77; 95% CI: -1.35 to -0.19; p = 0.02, I2 = 59.09%). The remaining tested differences did not yield significant results.

Conclusion

Elevated serum levels of vitamin B12 were associated with higher mortality in patients with COVID-19. Severe cases of COVID-19 were associated with low serum folate levels. Future studies should incorporate a larger sample size.

Fungal infections in patients after recovering from COVID-19: a systematic review

Background and aims

The presence of fungal infections has been described in patients after recovering from COVID-19. This study aims to conduct a systematic review of studies that reported fungal infections (Mucor spp., Pneumocystis jirovecii, or Aspergillus spp.) in adults after recovering from COVID-19.

Methods

We performed a systematic review through PubMed, Web of Science, OVID-Medline, Embase, and Scopus. The study selection process was performed independently and by at least two authors. We performed a risk of bias assessment using the Newcastle-Ottawa Scale for cohort and case-control studies, and the Joanna Briggs Institute's Checklists for Case Series and Case Reports.

Results

The systematic search found 33 studies meeting all inclusion criteria. There was a total population of 774 participants, ranging from 21 to 87 years. From them, 746 developed a fungal infection. In 19 studies, Mucor spp. was reported as the main mycosis. In 10 studies, P. jirovecii was reported as the main mycosis. In seven studies, Aspergillus spp. was reported as the main mycosis. Regarding the quality assessment, 12 studies were classified as low risk of bias and the remaining studies as high risk of bias.

Conclusion

Patients' clinical presentation and prognosis after recovering from COVID-19 with fungal infection differ from those reported patients with acute COVID-19 infection and those without COVID-19 infection.

Applications of human and bovine serum albumins in biomedical engineering: A review

Serum albumin, commonly recognized as a predominant major plasma protein, is ubiquitously distributed among vertebrates, demonstrating versatility and widespread accessibility. Numerous studies have discussed the composition and attributes of human and bovine serum albumin; nonetheless, few systematic and comprehensive summaries on human and bovine serum albumin exist. This paper reviews the applications of human and bovine serum albumin in biomedical engineering. First, we introduce the differences in the structure of human and bovine serum albumin. Next, we describe the extraction methods for human and bovine serum albumin (fractionation process separation, magnetic adsorption, reverse micellar (RM) extraction, and genetic engineering) and the advantages and disadvantages of recently developed extraction methods. The characteristics of different processing forms of human and bovine serum albumin are also discussed, concomitantly elucidating their intrinsic properties, functions, and applications in biomedicine. Notably, their pivotal functions as carriers for drugs and tissue-engineered scaffolds, as well as their contributions to cell reproduction and bioimaging, are critically examined. Finally, to provide guidance for researchers in their future work, this review summarizes the current state of human and bovine serum albumin research and outlines potential future research topics.

Adhatoda vasica and Tinospora cordifolia extracts ameliorate clinical and molecular markers in mild COVID-19 patients: a randomized open-label three-armed study

BACKGROUND

SARS-CoV-2 infections caused mild-to-moderate illness. However, a sizable portion of infected people experience a rapid progression of hyper-inflammatory and hypoxic respiratory illness that necessitates an effective and safer remedy to combat COVID-19.

METHODS

A total of 150 COVID-19-positive patients with no to mild symptoms, between the age groups 19-65 years were enrolled in this randomized, open-labeled three-armed clinical trial. Among them, 136 patients completed the study with RT-PCR negative reports. The patients received herbal drugs orally (Group A (Adhatoda vasica; AV; 500 mg; n = 50); Group B (Tinospora cordifolia; TC; 500 mg; n = 43), and Group C (AV + TC; 250 mg each; n = 43)) for 14 days. Clinical symptoms, vital parameters, and viral clearance were taken as primary outcomes, and biochemical, hematological parameters, cytokines, and biomarkers were evaluated at three time points as secondary outcomes.

RESULTS

We found that the mean viral clearance time was 13.92 days (95% confidence interval [CI] 12.85-14.99) in Group A, 13.44 days (95% confidence interval [CI] 12.14-14.74) in Group B, and 11.86 days (95% confidence interval [CI] 10.62-13.11) days in Group C. Over a period of 14 days, the mean temperature in Groups A, and B significantly decreased linearly. In Group A, during the trial period, eosinophils, and PT/INR increased significantly, while monocytes, SGOT, globulin, serum ferritin, and HIF-1α, a marker of hypoxia reduced significantly. On the other hand, in Group B hsCRP decreased at mid-treatment. Eosinophil levels increased in Group C during the treatment, while MCP-3 levels were significantly reduced.

CONCLUSIONS

All the patients of the three-armed interventions recovered from COVID-19 and none of them reported any adverse effects from the drugs. Group C patients (AV + TC) resulted in a quicker viral clearance as compared to the other two groups. We provide the first clinical report of AV herbal extract acting as a modifier of HIF-1α in COVID-19 patients along with a reduction in levels of ferritin, VEGF, and PT/INR as the markers of hypoxia, inflammation, and thrombosis highlighting the potential use in progression stages, whereas the TC group showed immunomodulatory effects. Trial registration Clinical Trials Database -India (ICMR-NIMS), CTRI/2020/09/028043. Registered 24th September 2020, https://www.ctri.nic.in/Clinicaltrials/pdf_generate.php?trialid=47443&EncHid=&modid=&compid=%27,%2747443det%27.

Interpretations of the Role of Plasma Albumin in Prognostic Indices: A Literature Review

This review assesses how publications interpret factors that influence the serum or plasma albumin (PA) level in prognostic indices, focusing on inflammation and nutrition. On PubMed, a search for "albumin AND prognosis" yielded 23,919 results. From these records, prognostic indices were retrieved, and their names were used as search strings on PubMed. Indices found in 10 or more original research articles were included. The same search strings, restricted to "Review" or "Systematic review", retrieved yielded on the indices. The data comprised the 10 latest original research articles and up to 10 of the latest reviews. Thirty indices had 294 original research articles (6 covering two indices) and 131 reviews, most of which were from recent years. A total of 106 articles related the PA level to inflammation, and 136 related the PA level to nutrition. For the reviews, the equivalent numbers were 54 and 65. In conclusion, more publications mention the PA level as a marker of nutrition rather than inflammation. This is in contrast to several general reviews on albumin and nutritional guidelines, which state that the PA level is a marker of inflammation but not nutrition. Hypoalbuminemia should prompt clinicians to focus on the inflammatory aspects in their patients.

Clinical and Biomarker Profile Responses to Rehabilitation Treatment in Patients with Long COVID Characterized by Chronic Fatigue

Long COVID (LC) syndrome is a complex multiorgan symptom that persists beyond >12 weeks after SARS-CoV-2 infection. The most frequently associated symptom is fatigue. Physical activity and exercise are recommended, although specific studies are lacking. The objectives of the present work are to analyze the impact of a supervised exercise program on the clinical evolution of LC with fatigue patients and to identify whether certain circulating biomarkers could predict the response to rehabilitation. The rehabilitation treatment response was analyzed in 14 women diagnosed with LC and fatigue, based on the changes in the 6 min walk test and Borg/Fatigue Impact scales. Patients who showed improvement in the meters walked were considered "responders" to the therapy. A total of 65% of patients responded to the exercise program, with an improvement in the meters walked and in oxygen saturation, with stability in the percentage of meters walked. Participants with obesity and those double-vaccinated against SARS-CoV-2 presented a lower degree of fatigue. LC patients presented a favorable response to a supervised exercise program. Differences in creatinine and protein levels were observed between rehabilitation therapy "responders" and "nonresponders". A good state of protein nutrition was related to a better rehabilitation response. The results are promising regarding possible predictive biomarkers of rehabilitation response, such as creatinine.

A comparison of machine learning algorithms in predicting COVID-19 prognostics

ML algorithms are used to develop prognostic and diagnostic models and so to support clinical decision-making. This study uses eight supervised ML algorithms to predict the need for intensive care, intubation, and mortality risk for COVID-19 patients. The study uses two datasets: (1) patient demographics and clinical data (n = 11,712), and (2) patient demographics, clinical data, and blood test results (n = 602) for developing the prediction models, understanding the most significant features, and comparing the performances of eight different ML algorithms. Experimental findings showed that all prognostic prediction models reported an AUROC value of over 0.92, in which extra tree and CatBoost classifiers were often outperformed (AUROC over 0.94). The findings revealed that the features of C-reactive protein, the ratio of lymphocytes, lactic acid, and serum calcium have a substantial impact on COVID-19 prognostic predictions. This study provides evidence of the value of tree-based supervised ML algorithms for predicting prognosis in health care.

C-Reactive Protein-to-Albumin Ratio and Clinical Outcomes in COVID-19 Patients: A Systematic Review and Meta-Analysis

C-reactive protein-to-albumin ratio (CAR) is an independent risk factor in cardiovascular, cerebrovascular, and infectious diseases. Through this study, we investigated the CAR values with respect to the severity and mortality of COVID-19 patients. We performed a systematic review and meta-analysis to retrieve studies that evaluated CAR values upon hospital admission in relation to the severity or mortality of COVID-19 patients. We adopted a random-effect model to calculate the pooled mean difference (MD) and their 95% confidence intervals (CI). Quality assessment was appraised using a Newcastle−Ottawa scale and publication bias was assessed using the Begg-test and funnel plot. We equally performed a subgroup analysis using study location and a sensitivity analysis only with studies with low risk of bias. We analyzed 32 studies (n = 12445). Severe COVID-19 patients had higher on-admission CAR values than non-severe COVID-19 patients (MD: 1.69; 95% CI: 1.35−2.03; p < 0.001; I2 = 89%). Non-survivor patients with COVID-19 had higher CAR values than survivor patients (MD: 2.59; 95% CI: 1.95−3.23; p < 0.001; I2 = 92%). In sensitivity analysis, the relationship remained with a decreasing of heterogeneity for severity (MD: 1.22; 95% CI: 1.03−1.40; p < 0.001; I2 = 13%) and for mortality (MD: 2.99; 95% CI: 2.47−3.51; p < 0.001; I2 = 0%). High CAR values were found in COVID-19 patients who developed severe disease or died.

Fibrinogen-to-Albumin Ratio and Blood Urea Nitrogen-to-Albumin Ratio in COVID-19 Patients: A Systematic Review and Meta-Analysis

Fibrinogen-to-albumin ratio (FAR) and blood urea nitrogen-to-albumin ratio (BAR) are inflammatory biomarkers that have been associated with clinical outcomes of multiple diseases. The objective of this study is to evaluate the association of these biomarkers with the severity and mortality of COVID-19 patients. A systematic search was performed in five databases. Observational studies that reported the association between FAR and BAR values with the severity and mortality of COVID-19 patients were included. Random-effects models were used for meta-analyses, and effects were expressed as Odds Ratio (OR) and their 95% confidence intervals (CI). Publication bias was assessed using the Begg test, while the quality assessment was assessed using the Newcastle Ottawa Scale. A total of 21 studies (n = 7949) were included. High FAR values were associated with a higher risk of severity (OR: 2.41; 95% CI 1.41−4.12; p < 0.001) and mortality (OR: 2.05; 95% CI 1.66−2.54; p < 0.001). High BAR values were associated with higher risk of mortality (OR: 4.63; 95% CI 2.11−10.15; p < 0.001). However, no statistically significant association was found between BAR values and the risk of severity (OR: 1.16; 95% CI 0.83−1.63; p = 0.38). High FAR and BAR values were associated with poor clinical outcomes.