Nitazoxanide, a US Food and Drug Administration-approved antiparasitic agent, was reported to be effective in treating coronavirus disease 2019 (COVID-19). The lack of effective and precise treatments for COVID-19 infection earlier in the pandemic forced us to depend on symptomatic, empirical, and supportive therapy, which overburdened intensive care units and exhausted hospital resources. Therefore, the aim of this systematic review and meta-analysis was to assess the efficacy and safety of nitazoxanide for COVID-19 treatment. A systematic review and meta-analysis synthesizing relevant randomized controlled trials from six databases (MedRxiv, WOS, SCOPUS, EMBASE, PubMed, and CENTRAL) until 17 May 2022 was conducted. Risk ratio (RR) for dichotomous outcomes was used and data with a 95% confidence interval (CI) are presented. The protocol was registered in PROSPERO with ID: CRD42022334658. Six randomized controlled trials with 1412 patients were included in the analysis. Nitazoxanide was effective in accelerating viral clearance compared with placebo (RR: 1.30 with 95% CI 1.08, 1.56, p = 0.006) and reducing oxygen requirements (RR: 0.48 with 95% CI 0.39, 0.59, p = 0.00001), but we found no difference between nitazoxanide and placebo in improving clinical resolution (RR: 1.01 with 95% CI 0.94, 1.08, p = 0.88), reducing the mortality rate (RR: 0.88 with 95% CI 0.4, 1.91, p = 0.74), and intensive care unit admission (RR: 0.69 with 95% CI 0.43, 1.13, p = 0.14). Moreover, nitazoxanide was as safe as placebo (RR: 0.9 with 95% CI 0.72, 1.12, p = 0.34). Compared with placebo, nitazoxanide was effective in expediting viral clearance and decreasing oxygen requirements. However, there was no difference between nitazoxanide and placebo regarding clinical response, all-cause mortality, and intensive care unit admission. Therefore, more large-scale studies are still needed to ascertain the clinical applicability of nitazoxanide in COVID-19. 

/pdf/the-effect-of-nitazoxanide-on-the-clinical-outcomes-in-7nss49al.pdf

The Effect of Nitazoxanide on the Clinical Outcomes in Patients with COVID-19: A Systematic Review and Meta-Analysis of Randomized Controlled Trials

https://doi.org/10.1016/j.intimp.2023.110439

COVID-19 and severity of liver diseases: Possible crosstalk and clinical implications

Abstract Background The clinical spectrum of acute SARS-CoV-2 infection ranges from an asymptomatic to life-threatening disease. Considering the broad spectrum of severity, reliable biomarkers are required for early risk stratification and prediction of clinical outcomes. Despite numerous efforts, no COVID-19-specific biomarker has been established to guide further diagnostic or even therapeutic approaches, most likely due to insufficient validation, methodical complexity, or economic factors. COVID-19-associated coagulopathy is a hallmark of the disease and is mainly attributed to dysregulated immunothrombosis. This process describes an intricate interplay of platelets, innate immune cells, the coagulation cascade, and the vascular endothelium leading to both micro- and macrothrombotic complications. In this context, increased levels of immunothrombotic components, including platelet and platelet-leukocyte aggregates, have been described and linked to COVID-19 severity. Methods Here, we describe a label-free quantitative phase imaging approach, allowing the identification of cell-aggregates and their components at single-cell resolution within 30 min, which prospectively qualifies the method as point-of-care (POC) testing. Results We find a significant association between the severity of COVID-19 and the amount of platelet and platelet-leukocyte aggregates. Additionally, we observe a linkage between severity, aggregate composition, and size distribution of platelets in aggregates. Conclusions This study presents a POC-compatible method for rapid quantitative analysis of blood cell aggregates in patients with COVID-19. 

Platelet aggregates detected using quantitative phase imaging associate with COVID-19 severity

Abstract Purpose Since the declaration of COVID-19 as a pandemic, a wide between-country variation was observed regarding in-hospital mortality and its predictors. Given the scarcity of local research and the need to prioritize the provision of care, this study was conducted aiming to measure the incidence of in-hospital COVID-19 mortality and to develop a simple and clinically applicable model for its prediction. Methods COVID-19-confirmed patients admitted to the designated isolation areas of Ain-Shams University Hospitals (April 2020–February 2021) were included in this retrospective cohort study ( n = 3663). Data were retrieved from patients’ records. Kaplan–Meier survival and Cox proportional hazard regression were used. Binary logistic regression was used for creating mortality prediction models. Results Patients were 53.6% males, 4.6% current smokers, and their median age was 58 (IQR 41–68) years. Admission to intensive care units was 41.1% and mortality was 26.5% (972/3663, 95% CI 25.1–28.0%). Independent mortality predictors—with rapid mortality onset—were age ≥ 75 years, patients’ admission in critical condition, and being symptomatic. Current smoking and presence of comorbidities particularly, obesity, malignancy, and chronic haematological disorders predicted mortality too. Some biomarkers were also recognized. Two prediction models exhibited the best performance: a basic model including age, presence/absence of comorbidities, and the severity level of the condition on admission (Area Under Receiver Operating Characteristic Curve (AUC) = 0.832, 95% CI 0.816–0.847) and another model with added International Normalized Ratio (INR) value (AUC = 0.842, 95% CI 0.812–0.873). Conclusion Patients with the identified mortality risk factors are to be prioritized for preventive and rapid treatment measures. With the provided prediction models, clinicians can calculate mortality probability for their patients. Presenting multiple and very generic models can enable clinicians to choose the one containing the parameters available in their specific clinical setting, and also to test the applicability of such models in a non-COVID-19 respiratory infection. 

/pdf/developing-a-mortality-risk-prediction-model-using-data-of-g0kadsvi.pdf

Developing a mortality risk prediction model using data of 3663 hospitalized COVID-19 patients: a retrospective cohort study in an Egyptian University Hospital

Abstract Background COVID-19 has emerged as the most serious outbreak in recent years. Certain medications such as sofosbuvir (SOF), ledipasvir (LDV) and paracetamol (PAR) were proposed as a safer and recommended substance to control symptoms of COVID-19. Results Using built-in spectrophotometer software, zero order and derivative spectra of the studied components, two extremely clear, quick, and sensitive spectrophotometric techniques for simultaneous determinations of SOF, LDV, as well as PAR have been developed. LDV was calculated using a zero order absorption spectrum at wavelength maxima of 333 nm. SOF and PAR were evaluated simultaneously using a first derivative spectrophotometer at 247.2 nm and 260.8 nm, respectively. The calibration graphs for SOF, LDV, and PAR are linear over ranges of concentrations of 8–60 µg/mL, 4–22 µg/mL, and 2–14 µg/mL, consequently. The suggested methodologyspecificity was investigated using laboratory manufactured (different ratios) mixtures, which were then effectively used to the analysis of Mpiviropack plus® and Panadol® pills. Valid limitations included accuracy, precision, and specificity. The methodologies were validated in accordance with some ICH standards. Conclusions The methods proposed were simple, accurate, precise, and neither require any complex equipment nor specific software. 

pdf/simultaneous-spectrophotometric-determination-of-recombined-3m65009r3h.pdf

Simultaneous spectrophotometric determination of recombined sofosbuvir, ledipasvir and paracetamol together as commonly repurposed drugs for COVID-19 treatment

Peroral endoscopic myotomy (POEM) is a well-established endoscopic therapy for achalasia with high success rates. Severe submucosal fibrosis correlates with prolonged procedure duration, higher perioperative complications, and even failed POEM. Methods to overcome severe submucosal fibrosis include changing to an anterior approach, simultaneous submucosal tunnel dissection [1], open POEM [2], and initial submucosal tunneling followed by through-muscle dissection [3], with variable rates of success and complications. Here, we present a novel and successful method of initial intramuscular dissection (IIMD) in two patients with severe submucosal fibrosis where submucosal tunneling was not possible ([Video 1]). 

Initial intramuscular dissection as a rescue therapy during peroral endoscopic myotomy for achalasia patients with severe submucosal fibrosis

Comparison of early results of balloon mitral valvotomy to closed mitral commissurotomy in complex mitral stenosis

Background & Aims: The safety and efficacy of hepatitis C (HCV) direct-acting antivirals (DAAs) have been established in several real-world trials; however, some reports have claimed an association between DAAs and hepatocellular carcinoma (HCC) occurrence or aggressive behavior. We aimed to prospectively examine differences in de-novo HCC tumor behavior and overall survival (OS) in DAAs-treated versus HCV-untreated patients as measured by BCLC progression during a two-year follow-up period. Methods: This multicenter cohort study recruited 523 patients with de-novo HCV-related HCC. After exclusion criteria were applied, 353 patients were placed into; Group 1, including 236 patients without a history of DAAs therapy, and Group 2 including 117 patients with de-novo HCC developed after receiving DAAs. Patients were then stratified in each group according to BCLC staging (Liver, 2018). All patients received standard of care management and were followed until death or a maximum of 2 years. Results: No statistically significant differences were observed between the two groups regarding tumor characteristics (number and size of lesions) and criteria for aggressiveness upon presentation. Among all BCLC stages, DAAs treated patients showed significantly lower baseline Fib4 values than DAA untreated patients in BCLC-0 stage (4.1 vs 7.7, p 0.019). No statistically significant differences were evident in HCC progression in the different BCLC stages at 12 and 24 months follow up periods (p 0.0718 and 0.279 respectively). Significantly better survival was recorded in Group 1 compared to Group 2 patients for BCLC stages C and D (p = 0.003 and 0.01, respectively). Conclusion: HCC may develop at an earlier stage of liver disease after DAAs therapy. No defensive role was found for DAAs treatment in delaying HCC progression that occurs after viral eradication.

http://journal.waocp.org/article_90496_dc54b53c5fa8772c1f6af54d7f427ed9.pdf

Prospective Comparison of Hepatocellular Carcinoma Behavior and Survival of Patients who Did or Did not Receive HCV Direct-Acting Antivirals

Introduction: COVID-19 severity and mortality predictors could determine admission criteria and reduce mortality. We aimed to evaluate the clinical-laboratory features of hospitalized patients with COVID-19 to develop a novel score of severity and mortality. Methodology: This retrospective cohort study was conducted using data from patients with COVID-19 who were admitted to five Egyptian university hospitals. Demographics, comorbidities, clinical manifestations, laboratory parameters, the duration of hospitalization, and disease outcome were analyzed, and a score to predict severity and mortality was developed. Results: A total of 1308 patients with COVID-19, with 996 (76.1%) being moderate and 312 (23.9%) being severe cases, were included. The mean age was 46.5 ± 17.1 years, and 61.6% were males. The overall mortality was 12.6%. Regression analysis determined significant predictors, and a ROC curve defined cut-o ff values. The COVEG severity score was defined by age ≥ 54, D - dimer ≥ 0.795, serum ferritin ≥ 406, C- reactive protein ≥ 30.1, and neutrophil: lymphocyte ratio ≥ 2.88. The COVEG mortality score was based on COVEG severity and t he presence of cardiac diseases. Both COVEG scores had high predictive values (area under the curve 0.882 and 0.883, respectively). Conclusions: COVEG score predicts the severity and mortality of patients with COVID-19 accurately.

Coronavirus Pandemic The COVEG score to predict severity and mortality among hospitalized patients with COVID-19

INTRODUCTION
COVID-19 severity and mortality predictors could determine admission criteria and reduce mortality. We aimed to evaluate the clinical-laboratory features of hospitalized patients with COVID-19 to develop a novel score of severity and mortality.


METHODOLOGY
This retrospective cohort study was conducted using data from patients with COVID-19 who were admitted to five Egyptian university hospitals. Demographics, comorbidities, clinical manifestations, laboratory parameters, the duration of hospitalization, and disease outcome were analyzed, and a score to predict severity and mortality was developed.


RESULTS
A total of 1308 patients with COVID-19, with 996 (76.1%) being moderate and 312 (23.9%) being severe cases, were included. The mean age was 46.5 ± 17.1 years, and 61.6% were males. The overall mortality was 12.6%. Regression analysis determined significant predictors, and a ROC curve defined cut-off values. The COVEG severity score was defined by age ≥ 54, D-dimer ≥ 0.795, serum ferritin ≥ 406, C-reactive protein ≥ 30.1, and neutrophil: lymphocyte ratio ≥ 2.88. The COVEG mortality score was based on COVEG severity and the presence of cardiac diseases. Both COVEG scores had high predictive values (area under the curve 0.882 and 0.883, respectively).


CONCLUSIONS
COVEG score predicts the severity and mortality of patients with COVID-19 accurately.

The COVEG score to predict severity and mortality among hospitalized patients with COVID-19.

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