Comparative Global Epidemiological Investigation of SARS-CoV-2 and SARS-CoV Diseases Using Meta-MUMS Tool Through Incidence, Mortality, and Recovery Rates

A systematic review and meta-analysis on the outcomes of extracorporeal shock wave compared to ureteroscopic lithotripsy for the treatment of ureteral stones

Objectives

In this systematic review and meta-analysis, we sought to identify whether extracorporeal shockwave lithotripsy (ESWL) or ureteroscopic lithotripsy (URSL) is the most appropriate method for treating ureteral stones.

Methods

We identified relevant literature by searching the Google Scholar and PubMed databases in accordance with PRISMA guidelines. We focused on the outcomes of extracorporeal shockwave lithotripsy and ureteroscopic lithotripsy. For each method, we compared complications, hematuria, perforation, failure, stone clearance, initial stone-free, operating time, stone size, auxiliary procedures, and overall stone-free outcomes. Our analysis involved meta-analysis, heterogeneity testing, subgroup analysis, meta-regression sensitivity analyses, Egger's tests, Smoothed Variance Egger's (SVE) testing, and Smoothed Variance Thomson (SVT) testing. In addition, we detected publication bias for all outcomes related to the two procedures.

Results

Based on ten eligible studies, we conducted a meta-analysis on a total of 1509 patients. Extracorporeal shockwave lithotripsy was used to treat 677 patients; the remaining 832 patients were treated by the ureteroscopic lithotripsy procedure. Considering the meta-analysis statistical parameters including odds ratio (OR), standardized mean difference (SMD), Q, I² and their p-values, the overall stone-free, operating time, stone size outcomes were identified with significant OR, SMD, and Q values. The hematuria, failure, and stone clearance outcomes were determined to have significant Q values. The perforation and initial stone free outcomes had significant OR values. And, complications and auxiliary urinary procedures were not significant in terms of OR and Q values.

Conclusions

Analysis indicated that ESWL and URSL procedures are essential for the treatment of ureteral stones, even though the perforation rate is higher for URSL than for ESWL. Overall stone-free rates were better for the URSL procedure.

A review on in silico virtual screening methods in COVID-19 using anticancer drugs and other natural/chemical inhibitors

The present coronavirus disease 2019 (COVID-19) pandemic scenario has posed a difficulty for cancer treatment. Even under ideal conditions, malignancies like small cell lung cancer (SCLC) are challenging to treat because of their fast development and early metastases. The treatment of these patients must not be jeopardized, and they must be protected as much as possible from the continuous spread of the COVID-19 infection. Initially identified in December 2019 in Wuhan, China, the contagious coronavirus illness 2019 (COVID-19) is caused by the severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Finding inhibitors against the druggable targets of SARS-CoV-2 has been a significant focus of research efforts across the globe. The primary motivation for using molecular modeling tools against SARS-CoV-2 was to identify candidates for use as therapeutic targets from a pharmacological database. In the published study, scientists used a combination of medication repurposing and virtual drug screening methodologies to target many structures of SARS-CoV-2. This virus plays an essential part in the maturation and replication of other viruses. In addition, the total binding free energy and molecular dynamics (MD) modeling findings showed that the dynamics of various medications and substances were stable; some of them have been tested experimentally against SARS-CoV-2. Different virtual screening (VS) methods have been discussed as potential means by which the evaluated medications that show strong binding to the active site might be repurposed for use against SARS-CoV-2.

A meta-analysis of systematic reviews and meta-analyses to evaluate the psychological consequences of COVID-19

BACKGROUND

Several meta-analysis studies have been reported in the literature on the incidence of psychopathological conditions resulting from the COVID-19 pandemic. This investigation aims to compile and analyze the findings of previously published meta-analysis research, as shown by the present meta-analysis of previous meta-analysis studies.

METHODS

The PubMed and Scopus databases were searched from 1 January 2019 to 30 May 2022. The procedure was carried out according to the PRISMA flow chart and the qualities of the identified studies were analyzed using AMSTAR 2. Heterogeneities and risk of bias were assessed using the Meta-MUMS tool. The corresponding results, forest and funnel plots of the psychological consequences of COVID-19 were synthesized.

RESULTS

Eleven meta-analysis studies were included. Random-effects meta-analysis of anxiety and depression showed (ER = 0.318 p-value < 0.001, ER = 0.295 p-value < 0.001) high heterogeneities (I2 = 99.70%, I2 = 99.75) between studies. Random-effects meta-analyses of sleep difficulties and insomnia were shown (ER = 0.347 p-value < 0.001, ER = 0.265, p-value < 0.001) along with heterogeneities (I2 = 99.89, I2 = 99.64). According to the random meta-analysis of post-traumatic stress syndrome (PTSS) and post-traumatic stress disorder (PTSD) (ER = 0.246, p-value = 0.001, ER = 0.223 p-value < 0.001) with heterogeneities (I2 = 99.75, I2 = 99.17). Random-effects meta-analyses of somatic and fear symptoms have been shown (ER = 0.16 p-value < 0.001, ER = 0.41, p-value = 0.089) with high heterogeneities (I2 = 99.62, I2 = 98.63). Random-effects meta-analysis of obsessive-compulsive symptoms and distress (ER = 0.297 p-value = 0.103; ER = 0.428, p-value = 0.013) with high heterogeneity, as I2 = 99.38%. Subgroup analysis of all symptoms and Egger's tests for detecting publication bias were also assessed.

CONCLUSION

The data from the current meta-analysis showed different psychological disorders of COVID-19 during the pandemic. Clinicians should be aware of the prevalence with which COVID-19-infected patients experience emotional distress, anxiety, fatigue, and PTSD. About half of the included systematic reviews (SRs)/meta-analyses (MAs) suffered from poorer methodological quality and increased risk of bias, reducing confidence in the findings. There must be more SRs/MAs and high-quality clinical trials conducted to confirm these findings.

Targeting SELPLG/P-selectin glycoprotein ligand 1 in preclinical ARDS: Genetic and epigenetic regulation of the SELPLG promoter

We previously identified a missense single nucleotide polymorphism rs2228315 (G>A, Met62Ile) in the selectin-P-ligand gene (SELPLG), encoding P-selectin glycoprotein ligand 1 (PSGL-1), to be associated with increased susceptibility to acute respiratory distress syndrome (ARDS). These earlier studies demonstrated that SELPLG lung tissue expression was increased in mice exposed to lipopolysaccharide (LPS)- and ventilator-induced lung injury (VILI) suggesting that inflammatory and epigenetic factors regulate SELPLG promoter activity and transcription. In this report, we used a novel recombinant tandem PSGL1 immunoglobulin fusion molecule (TSGL-Ig), a competitive inhibitor of PSGL1/P-selectin interactions, to demonstrate significant TSGL-Ig-mediated decreases in SELPLG lung tissue expression as well as highly significant protection from LPS- and VILI-induced lung injury. In vitro studies examined the effects of key ARDS stimuli (LPS, 18% cyclic stretch to simulate VILI) on SELPLG promoter activity and showed LPS-mediated increases in SELPLG promoter activity and identified putative promoter regions associated with increased SELPLG expression. SELPLG promoter activity was strongly regulated by the key hypoxia-inducible transcription factors, HIF-1α, and HIF-2α as well as NRF2. Finally, the transcriptional regulation of SELPLG promoter by ARDS stimuli and the effect of DNA methylation on SELPLG expression in endothelial cell was confirmed. These findings indicate SELPLG transcriptional regulation by clinically-relevant inflammatory factors with the significant TSGL-Ig-mediated attenuation of LPS and VILI highly consistent with PSGL1/P-selectin as therapeutic targets in ARDS.

Strategies to DAMPen COVID-19-mediated lung and systemic inflammation and vascular injury

Approximately 15%-20% of patients infected with SARS-CoV-2 coronavirus (COVID-19) progress beyond mild and self-limited disease to require supplemental oxygen for severe pneumonia; 5% of COVID-19-infected patients further develop acute respiratory distress syndrome (ARDS) and multiorgan failure. Despite mortality rates surpassing 40%, key insights into COVID-19-induced ARDS pathology have not been fully elucidated and multiple unmet needs remain. This review focuses on the unmet need for effective therapies that target unchecked innate immunity-driven inflammation which drives unchecked vascular permeability, multiorgan dysfunction and ARDS mortality. Additional unmet needs including the lack of insights into factors predicting pathogenic hyperinflammatory viral host responses, limited approaches to address the vast disease heterogeneity in ARDS, and the absence of clinically-useful ARDS biomarkers. We review unmet needs persisting in COVID-19-induced ARDS in the context of the potential role for damage-associated molecular pattern proteins in lung and systemic hyperinflammatory host responses to SARS-CoV-2 infection that ultimately drive multiorgan dysfunction and ARDS mortality. Insights into promising stratification-enhancing, biomarker-based strategies in COVID-19 and non-COVID ARDS may enable the design of successful clinical trials of promising therapies.

Analysis of the Clinical and Epidemiological Meaning of Screening Test for SARS-CoV-2: Considerations in the Chronic Kidney Disease Patients during the COVID-19 Pandemic

The COronaVIrus Disease 19 (COVID-19) pandemic is an emerging reality in nephrology. In a continuously changing scenario, we need to assess our patients’ additional risk in terms of attending hemodialysis treatments, follow-up peritoneal dialysis, and kidney transplant visits. The prevalence of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-20 infection in the general population plays a pivotal role in estimating the additional COVID-19 risk in chronic kidney disease (CKD) patients. Unfortunately, local prevalence is often obscure, and when we have an estimation, we neglect the number of asymptomatic subjects in the same area and, consequently, the risk of infection in CKD patients. Furthermore, we still have the problem of managing COVID-19 diagnosis and the test’s accuracy. Currently, the gold standard for SARS-CoV-2 detection is a real-time reverse transcription-polymerase chain reaction (rRT-PCR) on respiratory tract samples. rRT-PCR presents some vulnerability related to pre-analytic and analytic problems and could impact strongly on its diagnostic accuracy. Specifically, the operative proceedings to obtain the samples and the different types of diagnostic assay could affect the results of the test. In this scenario, knowing the local prevalence and the local screening test accuracy helps the clinician to perform preventive measures to limit the diffusion of COVID-19 in the CKD population.

Artificial neural network and logistic regression modelling to characterize COVID-19 infected patients in local areas of Iran

Background

COVID-19 is an infectious disease that started spreading globally at the end of 2019. Due to differences in patient characteristics and symptoms in different regions, in this research, a comparative study was performed on COVID-19 patients in 6 provinces of Iran. Also, multilayer perceptron (MLP) neural network and Logistic Regression (LR) models were applied for the diagnosis of COVID-19.

Methods

A total of 1043 patients with suspected COVID-19 infection in Iran participated in this study. 29 characteristics, symptoms and underlying disease were obtained from hospitalized patients. Afterwards, we compared the obtained data between confirmed cases. Furthermore, the data was applied for building the ANN and LR models to diagnosis the infected patients by COVID-19.

Results

In 750 confirmed patients, Common symptoms were: fever (%) >37.5 °C, cough, shortness of breath, fatigue, chills and headache. The most common underlying diseases were: hypertension, diabetes, chronic obstructive pulmonary disease and coronary heart disease. Finally, the accuracy of the ANN model to the diagnosis of COVID-19 infection was higher than the LR model.

Conclusion

The prevalent symptoms and underlying diseases of COVID-19 patients were similar in different provinces, but the incidence of symptoms was significantly different from each other. Also, the study demonstrated that ANN and LR models have a high ability in the diagnosis of COVID-19 infection.

IoMT amid COVID-19 pandemic: Application, architecture, technology, and security

In many countries, the Internet of Medical Things (IoMT) has been deployed in tandem with other strategies to curb the spread of COVID-19, improve the safety of front-line personnel, increase efficacy by lessening the severity of the disease on human lives, and decrease mortality rates. Significant inroads have been achieved in terms of applications and technology, as well as security which have also been magnified through the rapid and widespread adoption of IoMT across the globe. A number of on-going researches show the adoption of secure IoMT applications is possible by incorporating security measures with the technology. Furthermore, the development of new IoMT technologies merge with Artificial Intelligence, Big Data and Blockchain offers more viable solutions. Hence, this paper highlights the IoMT architecture, applications, technologies, and security developments that have been made with respect to IoMT in combating COVID-19. Additionally, this paper provides useful insights into specific IoMT architecture models, emerging IoMT applications, IoMT security measurements, and technology direction that apply to many IoMT systems within the medical environment to combat COVID-19.

Clinical Symptom Differences Between Mild and Severe COVID-19 Patients in China: A Meta-Analysis

Objective: The prognosis of mild and severe patients has prominent differences during the prevalence of COVID-19, and it will be significant to identify patients' potential risk of progressing to severe cases according to their first clinical presentations. Therefore, we aim to review the clinical symptoms of the COVID-19 epidemic systematically. Methods:We searched PubMed, Embase, Web of Science, and CNKI (Chinese Database) for studies about the clinical features of COVID-19 in China from March 18 to April 18. Then we used REVMAN to conduct a meta-analysis. Results: After screening, 20 articles including 3,326 COVID-19 confirmed cases were selected from 142 articles we retrieved at the beginning of our research. We divided all the cases into a severe group (including severe and critically severe patients) and a mild group according to the "Diagnosis and Treatment Protocol for Novel Coronavirus Infection-Induced Pneumonia" version 4 (trial). Of all the initial symptoms (including fever, cough, abdominal pain, anorexia, chest tightness, diarrhea, dyspnea, expectoration, fatigue, headache, hemoptysis, myalgia, nausea or vomiting, and pharyngalgia) we studied, we found that cough (odds ratio [OR] = 1.4, 95% confidence interval [CI]: 1.2-1.7; p < 0.001), fever (OR = 1.5, 95% CI: 1.2-1.9; p < 0.001), dyspnea (OR = 6.2, 95% CI: 3.6-10.6; p < 0.001), diarrhea (OR = 2.6, 95% CI: 1.3-4.9; p < 0.001), fatigue (OR = 2.1, 95% CI: 1.3-3.3; p < 0.01), expectoration (OR = 1.7, 95% CI: 1.2-2.6; p < 0.01), myalgia (OR = 1.6, 95% CI: 0.8-3.1; p < 0.001), hemoptysis (OR = 4.0, 95% CI: 1.5-11.3; p < 0.001), abdominal pain (OR = 7.5, 95% CI: 2.4-23.4; p < 0.001), and anorexia (OR = 2.8, 95% CI: 1.5-5.1; p < 0.001) had a different distribution in two groups and were statistically significant (p < 0.05). Conclusion:COVID-19 patients whose initial manifestation is dyspnea, hemoptysis, anorexia, diarrhea, or fatigue, especially abdominal pain should be closely monitored to prevent disease deterioration.

From Hospital to Home: An Intensive Transitional Care Management Intervention for Patients with COVID-19

Implementing emergency department (ED) and hospital patient throughput management coupled with at-home medical and tele-management upon discharge may increase surge capacity during national emergencies and pandemics. This novel intensive transitional care management (ITCM) intervention presents the opportunity to optimize hospital bed capacity through prevention of inpatient admissions for patients who could be discharged home safely with appropriate in-home medical support and tele-management. This observational cohort intervention was conducted between April 7, 2020 and April 30, 2020, at the 4 largest inpatient facilities of RWJBarnabas Health System in New Jersey. The intervention group included a convenience sample of 192 patients who were evaluated in the ED, monitored in the observation unit, or admitted to the hospital with a diagnosis of mild-to-moderate COVID-19 infection. Their outcomes were compared to a matched comparison group of 593 patients who were admitted with the same COVID-19-related diagnosis and severity. The primary outcome was the reduction in inpatient days as a result of the intervention that included provision of at-home oxygen supplementation therapy, expanded home care services, and tele-management sessions. Secondary outcomes were re-encounters with the health system in the ED, observation unit, or inpatient readmissions. A total of 481.6 hospital patient days were avoided for 78 patients who had been discharged from the ED or observation unit stays. Secondary analysis included hospital readmission rates. The ITCM intervention demonstrated a feasible strategy for improving throughput of patients with COVID-19, resulting in increased hospital bed capacity.

Low plasma 25(OH) vitamin D level is associated with increased risk of COVID-19 infection: an Israeli population-based study

Vitamin D deficiency is a worldwide pandemic. The aim of this study was to evaluate associations of plasma 25(OH)D levels with the likelihood of coronavirus disease 2019 (COVID‐19) infection and hospitalization. The study population included the 14 000 members of Leumit Health Services, who were tested for COVID‐19 infection from February 1^st to April 30^th, 2020, and who had at least one previous blood test for the plasma 25(OH)D level. ‘Suboptimal’ or ‘low’ plasma 25(OH)D level was defined as plasma 25‐hydroxyvitamin D, or 25(OH)D, concentration below the level of 30 ng/mL. Of 7807 individuals, 782 (10.02%) were COVID‐19‐positive, and 7025 (89.98%) COVID‐19‐negative. The mean plasma vitamin D level was significantly lower among those who tested positive than negative for COVID‐19 [19.00 ng/mL (95% confidence interval (CI) 18.41–19.59) vs. 20.55 (95% CI: 20.32–20.78)]. Univariate analysis demonstrated an association between the low plasma 25(OH)D level and increased likelihood of COVID‐19 infection [crude odds ratio (OR) of 1.58 (95% CI: 1.24–2.01, P < 0.001)], and of hospitalization due to the SARS‐CoV‐2 virus [crude OR of 2.09 (95% CI: 1.01–4.30, P < 0.05)]. In multivariate analyses that controlled for demographic variables, and psychiatric and somatic disorders, the adjusted OR of COVID‐19 infection [1.45 (95% CI: 1.08–1.95, P < 0.001)] and of hospitalization due to the SARS‐CoV‐2 virus [1.95 (95% CI: 0.98–4.845, P = 0.061)] were preserved. In the multivariate analyses, age over 50 years, male gender and low–medium socioeconomic status were also positively associated with the risk of COVID‐19 infection; age over 50 years was positively associated with the likelihood of hospitalization due to COVID‐19. We concluded that low plasma 25(OH)D levels appear to be an independent risk factor for COVID‐19 infection and hospitalization.