Clinical efficacy of Azithromycin for COVID-19 management: A systematic meta-analysis of meta-analyses.

BACKGROUND: Azithromycin has been adopted as a component of the COVID-19 management protocol throughout the global healthcare settings but with a questionable if not downright unsubstantiated evidence base. OBJECTIVES: In order to amalgamate and critically appraise the conflicting evidence around the clinical efficacy of Azithromycin (AZO) vis a vis COVID-19 management outcomes, a meta-analysis of meta-analyses was carried out to establish an evidence-based holistic status of AZO vis a vis its efficacy as a component-in-use of the COVID-19 management protocol. METHODS: A comprehensive systematic search was carried out through PubMed/Medline, Cochrane and Epistemonikos with a subsequent appraisal of abstracts and full-texts, as required. The Quality of Reporting of Meta-analyses (QUOROM) checklist and the Assessment of Multiple Systematic Reviews (AMSTAR) methodology were adopted to assess the methodological quality of the included meta-analyses. Random-effects models were developed to calculate summarized pool Odds Ratios (with 95% confidence interval) for the afore determined primary and secondary outcomes. RESULTS: AZO, when compared with best available therapy (BAT) including or excluding Hydroxychloroquine, exhibited statistically insignificant reduction in mortality [(n= 27,204 patients) OR= 0.77 (95% CI: 0.51-1.16) (I2= 97%)], requirement of mechanical ventilation [(n= 14,908 patients) OR= 1.4 (95% CI: 0.58-3.35) (I2= 98%)], induction of arrhythmia [(n= 9,723 patients) OR= 1.21 (95% CI: 0.63-2.32) (I2= 92%)] and QTc prolongation (a surrogate for torsadogenic effect) [(n= 6,534 patients) OR= 0.62 (95% CI: 0.23-1.73) (I2= 96%)]. CONCLUSION: The meta-analysis of meta-analyses portrays AZO as a pharmacological agent that does not appear to have a comparatively superior clinical efficacy than BAT when it comes to COVID-19 management. Secondary to a very real threat of anti-bacterial resistance, it is suggested that AZO be discontinued and removed from COVID-19 management protocols.

Detection of hepatitis through proteases and protease inhibitors genes expression and identification of HCV untypable genotype in Abbottabad, Pakistan.

Liver cancer is the 5th most common cancer caused mainly due to the late detection of hepatitis. Therefore, the early detection of hepatitis through genetic markers boosts effective and remedial management. In addition, to determine the occurrence of hepatitis C virus (HCV), genotyping is indispensable as majority of hepatitis cases remain undiagnosed. The current study was designed to find the gene expression of proteases and proteases inhibitors in different hepatitis patients and to determine HCV genotypes mainly focusing on untypeable genotypes of HCV in Abbottabad, Pakistan. PCR was conducted to find the expression of proteases and protease inhibitors genes in hepatitis patients and healthy individuals. HCV genotyping was done by PCR based method and untypeable genotypes were sequenced and verified using online tools. Controlled individuals showed normal expression of cystatin C and leptin, low expression of cathepsin B while high expression of other studied genes including cathepsin D and G, TPP1 and serpin B1 could be seen. Hepatitis A patients showed high expression of leptin while other genes showed low expression. Hepatitis B patients revealed considerable variations in the cathepsin and cystatin C gene expression. Therefore, low cystatin C (high cathepsin B) and/or high cystatin C (low cathepsin B) levels can be regarded as a potential marker for hepatitis B. Hepatitis C infected patients showed high gene expression of cystatin C and leptin, so they could be useful markers for the diagnostics and prediction of the severity of HCV infections. While genotyping findings showed that about 45% of total PCR positive samples (110) were found to be of 3a genotype followed by 3b in 18%, 1a in 13.6% and 1b in 10%. About 9% of infections turned out to be mixed infections, whereas only 4.5% were untraceable by our genotyping system. Sequencing of untypeable genotypes and applying online tools revealed that the described untypeable genotypes of HCV were in fact variants of 3a genotype. Furthermore, full length characterization of these variants could help to classify them into types and subtypes. Keywords: hepatitis; genotyping; genes expression; proteases and protease inhibitors; ML; NJ.