Urinalysis, but Not Blood Biochemistry, Detects the Early Renal Impairment in Patients with COVID-19

Electrochemical biosensor for sensitive detection of SARS-CoV-2 gene fragments using Bi2Se3 topological insulator

In this study, we have designed an electrochemical biosensor based on topological material Bi2Se3 for the sensitive detection of SARS-CoV-2 in the COVID-19 pandemic. Flake-shaped Bi2Se3 was obtained directly from high-quality single crystals using mechanical exfoliation, and the single-stranded DNA was immobilized onto it. Under optimal conditions, the peak current of the differential pulse voltammetry method exhibited a linear relationship with the logarithm of the concentration of target-complementary-stranded DNA, ranging from 1.0 × 10-15 to 1.0 × 10-11 M, with a detection limit of 3.46 × 10-16 M. The topological material Bi2Se3, with Dirac surface states, enhanced the signal-to-interference plus noise ratio of the electrochemical measurements, thereby improving the sensitivity of the sensor. Furthermore, the electrochemical sensor demonstrated excellent specificity in recognizing RNA. It can detect complementary RNA by amplifying and transcribing the initial DNA template, with an initial DNA template concentration ranging from 1.0 × 10-18 to 1.0 × 10-15 M. Furthermore, the sensor also effectively distinguished negative and positive results by detecting splitting-synthetic SARS-CoV-2 pseudovirus with a concentration of 1 copy/μL input. Our work underscores the immense potential of the electrochemical sensing platform based on the topological material Bi2Se3 in the detection of pathogens during the rapid spread of acute infectious diseases.

The COVID-19 Severity and Its Association with Intestinal Parasite Coinfection and Urine Biochemical Parameters among COVID-19-Confirmed Patients Admitted to Debre Markos University COVID-19 Center, Northwest Ethiopia

Background

Though most people with COVID-19 disease show asymptomatic to mild illness, a substantial number of patients are at high risk of developing severe disease and adverse outcomes with long COVID-19 and death. Even though some studies showed that previously existing infections with parasites amend the host's body defenses to increase resistance to infection with SARS-CoV-2, there is limited data in Ethiopia.

Objectives

This study is aimed at determining the COVID-19 disease severity and its association with intestinal parasite coinfection and urine biochemical parameters among COVID-19-confirmed patients admitted at Debre Markos University COVID-19 Center, 2021.

Methods

A prospective cohort study was conducted on 136 RT-qPCR-confirmed COVID-19 patients admitted at Debre Markos University COVID-19 Center from January 1 to March 30, 2021. Sociodemographic and clinical data were collected by using standardized data collection forms. A urine biochemical test was performed using a dry urine dipstick kit and stool examination using direct wet mount microscopic examination and formalin-ether concentration method. The chi-square test, Fisher exact test, and ordinal logistic regression analysis were computed to assess association with outcome variables using Statistical Package for Social Science software (version 24).

Result

A total of 136 COVID-19-confirmed patients participated in this study. The median age of the participants was 48 years. The majority (86 (62.5%)) of them were male in sex. Of the 136 cases, 39 (28.7%) had died. Among the 136 patients, 22 (16.2%) were coinfected with intestinal parasites. COVID-19 patients who have intestinal parasite coinfection had lower odds of developing clinically severe COVID-19 compared to noninfected (AOR = 0.37; 95% CI = 0.147-0.944; P = 0.037). The majority (104 (76.5%)) of them have abnormal urine biochemical results. From the abnormal urine biochemical tests observed, the urine blood, glucose, and ketone tests were positive for 54 (39.7%), 36 (26.5%), and 30 (21.1%) patients, respectively. Among the 31 critical COVID-19 patients, 25 (80.6%) showed abnormal urine biochemical parameters. Age and comorbidity were significantly associated with COVID-19 severity (P < 0.05).

Conclusion

Patients with old age and comorbidity had an increased risk of developing severe COVID-19 disease. Patients having SARS-CoV-2 and intestinal parasitic coinfections demonstrated mild COVID-19 disease severity. Abnormal urine biochemical results were common among critical COVID-19 patients. Thus, advanced study on the effect of the interaction among intestinal parasites on COVID-19 clinical severity and its mechanisms is essential.

Clinical predictions of COVID-19 patients using deep stacking neural networks

The coronavirus disease 2019 (COVID-19) pandemic, which emerged in late 2019, has caused millions of infections and fatalities globally, disrupting various aspects of human society, including socioeconomic, political, and educational systems. One of the key challenges during the COVID-19 pandemic is accurately predicting the clinical development and outcome of the infected patients. In response, scientists and medical professionals globally have mobilized to develop prognostic strategies such as risk scores, biomarkers, and machine learning models to predict the clinical course and outcomes of COVID-19 patients. In this contribution, we deployed a mathematical approach called matrix factorization feature selection to select the most relevant features from the anonymized laboratory biomarkers and demographic data of COVID-19 patients. Based on these features, developed a model that leverages the deep stacking neural network (DSNN) to aid in clinical care by predicting patients' mortality risk. To gauge the performance of our suggested model, performed a comparative analysis with principal component analysis plus support vector machine, deep learning, and random forest, achieving outstanding performances. The DSNN model outperformed all the other models in terms of area under the curve (96.0%), F1-score (98.1%), recall (98.5%), accuracy (99.0%), precision (97.7%), specificity (97.0%), and maximum probability of correction decision (93.4%). Our model outperforms the clinical predictive models regarding patient mortality risk and classification in the literature. Therefore, we conclude that our robust model can help healthcare professionals to manage COVID-19 patients more effectively. We expect that early prediction of COVID-19 patients and preventive interventions can reduce the mortality risk of patients.

Acute kidney injury in critical COVID-19 patients: usefulness of urinary biomarkers and kidney proximal tubulopathy

Tubular injury is the main cause of acute kidney injury (AKI) in critically ill COVID-19 patients. Proximal tubular dysfunction (PTD) and changes in urinary biomarkers, such as NGAL, TIMP-2, and IGFBP7 product ([TIMP-2]•[IGFBP7]), could precede AKI. We conducted a prospective cohort study from 2020/03/09 to 2020/05/03, which consecutively included all COVID-19 patients who had at least one urinalysis, to assess the incidence of PTD and AKI, and the effectiveness of PTD, NGAL, and [TIMP-2]•[IGFBP7] in AKI and persistent AKI prediction using the area under the receiver operating characteristic curves (AUCs), Kaplan-Meier methodology (log-rank tests), and Cox models. Among the 60 patients admitted to the ICU with proven COVID-19 (median age: 63-year-old (interquartile range: IQR, 55-74), 45 males (75%), median simplified acute physiology score (SAPS) II: 34 (IQR, 22-47) and median BMI: 25.7 kg/m2 (IQR, 23.3-30.8)) analyzed, PTD was diagnosed in 29 patients (48%), AKI in 33 (55%) and persistent AKI in 20 (33%). Urinary NGAL had the highest AUC for AKI prediction: 0.635 (95%CI: 0.491-0.779) and persistent AKI prediction: 0.681 (95%CI: 0.535-0.826), as compared to PTD and [TIMP-2]•[IGFBP7] (AUCs <0.6). AKI was independently associated with higher SAPSII (HR = 1.04, 95%CI: 1.01-1.06, p = 0.005) and BMI (HR = 1.07, 95%CI: 1.00-1.14, p = 0.04) and persistent AKI with higher SAPSII (HR = 1.03, 95%CI: 1.00-1.06, p = 0.048) and nephrotoxic drug use (HR = 3.88, 95%CI: 1.20-12.5, p = 0.02). In conclusion, in critically ill COVID-19 patients, the incidence of PTD and AKI was relatively high. NGAL was the best urinary biomarker for predicting AKI, but only clinical severity was independently associated with its occurrence.

Prognostic Performance of Cystatin C in COVID-19: A Systematic Review and Meta-Analysis

Cystatin C is a specific biomarker of kidney function. We perform this meta-analysis to determine the association of Cystatin C with the COVID-19 severity. In this systematic review and meta-analysis, we searched PubMed, EMBASE, Cochrane library, and Web of Science for studies published until 2nd September 2022 that reported associations between Cystatin C levels and COVID-19 severity. The analysis was performed using a random-effects model to calculate pooled standard mean difference (SMD). Twenty-five studies were included in the meta-analysis. Pooled analysis showed statistically significant differences of Cystatin C levels among survive vs. decreased patients (0.998 ± 0.225 vs. 1.328 ± 0.475 mg/dL, respectively; SMD = -2.14; 95%CI: -3.28 to -1.01; p < 0.001). Cystatin C levels in COVID-19 severe vs. non-severe groups varied and amounted to 1.485 ± 1.191 vs. 1.014 ± 0.601 mg/dL, respectively (SMD = 1.81; 95%CI: 1.29 to 2.32; p < 0.001). Additionally, pooled analysis showed that Cystatin C levels in patients with acute kidney injury (AKI) was 1.562 ± 0.885 mg/dL, compared to 0.811 ± 0.108 mg/dL for patients without AKI (SMD = 4.56; 95%CI: 0.27 to 8.85; p = 0.04). Summing up, Cystatin C is a potentially very good marker to be used in the context of COVID-19 disease due to the prognosis of patients' serious condition, risk of AKI and mortality. In addition, Cystatin C could be used as a marker of renal complications in COVID-19 other than AKI due to the need to monitor patients even longer after leaving the hospital.

Clinical characteristics and laboratory parameters associated with the risk of severe COVID-19 in patients from two hospitals in Northeast Brazil

Background:

Although most coronavirus disease 2019 (COVID-19) infections are mild, some patients have severe clinical conditions requiring hospitalization. Data on the severity of COVID-19 in Brazil are scarce and are limited to public databases. This study aimed to investigate the clinical and laboratory factors associated with the severity of COVID-19 in a cohort of hospitalized adults from two hospitals in Northeast Brazil.

Methods:

Patients over 18 years of age who were hospitalized between August 2020 and July 2021 with a confirmed diagnosis of COVID-19 were included. The patients were classified into two groups: moderate and severe. Clinical, laboratory and imaging parameters were collected and compared between the groups. A multivariate logistic regression model was used to determine the predictors of COVID-19 severity.

Results:

This study included 495 patients (253 moderate and 242 severe). A total of 372 patients (75.2%) were between 18 and 65 years of age, and the majority were male (60.6%; n = 300). Patients with severe disease had higher levels of leukocytes, neutrophils, platelets, neutrophil-to-lymphocyte ratio, monocyte-to-lymphocyte ratio, blood glucose, C-reactive protein, ferritin, D-dimer, aspartate aminotransferase, creatinine, and urea (p < 0.05). In multivariate logistic regression, the following variables were significant predictors of COVID-19 severity: leukocytes (odds ratio [OR] 3.27; 95% confidence interval [CI] 2.12-5.06), international normalized ratio (INR) (OR 0.22, 95% CI 0.14-0.33), and urea (OR 4.03; 95% CI 2.21-7.35).

Conclusions:

The present study identified the clinical and laboratory factors associated with the severity of COVID-19 in hospitalized Brazilian individuals.

Organ Involvement in COVID-19: A Molecular Investigation of Autopsied Patients

Precise reasons for severe manifestation of SARS-CoV-2 remain unanswered, and efforts have been focused on respiratory system management. Demonstration of unequivocal presence of SARS-CoV-2 in vital body organs by cadaver autopsy was the only way to prove multi-organ involvement. Hence, the primary objective of the study was to determine presence of the SARS-CoV-2 in various organs of patients succumbing to SARS-CoV-2 infection. A total of 246 samples from different organs of 21 patients who died due to severe COVID-19 illness were investigated by qRT-PCR, and SARS-CoV-2 was detected in 181 (73.57%) samples and highest positivity of SARS-CoV-2 being (expectedly) found in nasopharynx (90.4%) followed by bilateral lungs (87.30%), peritoneal fluid (80%), pancreas (72.72%), bilateral kidneys (68.42%), liver (65%) and even in brain (47.2%). The deceased patients were categorized to three subgroups based upon the extent of organs in which SARS-CoV-2 was detected by qRT-PCR (high intensity ≥80%, intermediate intensity = 65-80% and low intensity ≤65% organs involvement). It was conclusively established that SARS-CoV-2 has the property of invasion beyond lungs and even crosses the blood-brain barrier, resulting in multi-system disease; this is probably the reason behind cytokine storm, though it is not clear whether organ damage is due to direct injury caused by the virus or result of inflammatory assault. Significant inverse correlation was found between the Ct value of lung samples and number of organs involved, implying that higher viral load in lungs is directly proportionate to involvement of extrapulmonary organs and patients with higher viral load in respiratory secretions should be monitored more closely for any warning signs and the treatment strategies should also address involvement of other organs for better outcome, because lungs, though the primary site of infection, are not the only organ system responsible for pathogenesis of systemic illness.

Insight into prognostics, diagnostics, and management strategies for SARS CoV-2

The foremost challenge in countering infectious diseases is the shortage of effective therapeutics. The emergence of coronavirus disease (COVID-19) outbreak has posed a great menace to the public health system globally, prompting unprecedented endeavors to contain the virus. Many countries have organized research programs for therapeutics and management development. However, the longstanding process has forced authorities to implement widespread infrastructures for detailed prognostic and diagnostics study of severe acute respiratory syndrome (SARS CoV-2). This review discussed nearly all the globally developed diagnostic methodologies reported for SARS CoV-2 detection. We have highlighted in detail the approaches for evaluating COVID-19 biomarkers along with the most employed nucleic acid- and protein-based detection methodologies and the causes of their severe downfall and rejection. As the variable variants of SARS CoV-2 came into the picture, we captured the breadth of newly integrated digital sensing prototypes comprised of plasmonic and field-effect transistor-based sensors along with commercially available food and drug administration (FDA) approved detection kits. However, more efforts are required to exploit the available resources to manufacture cheap and robust diagnostic methodologies. Likewise, the visualization and characterization tools along with the current challenges associated with waste-water surveillance, food security, contact tracing, and their role during this intense period of the pandemic have also been discussed. We expect that the integrated data will be supportive and aid in the evaluation of sensing technologies not only in current but also future pandemics.