Background: Patients with cardiovascular disease and risk factors for cardiovascular illness are more likely to acquire severe 2019 novel coronavirus (2019-nCoV) infection (COVID-19). COVID-19 infection is more common in patients with cardiovascular illness, and they are more likely to develop severe symptoms. Nevertheless, whether COVID-19 patients are more likely to develop cardiovascular disorders such as acute myocardial infarction (AMI) is still up for debate. Methods: We will follow the preferred reporting items for systematic review and meta-analysis (PRISMA) to report our final study, including a systematic search of the bibliographic database using the appropriate combination of search terms or keywords. The choice of search terms is discussed in more detail later in this paper. The obtained results will be screened, and the data extracted from the studies selected for systematic review will be based on the predefined inclusion and exclusion criteria. Using the obtained data, we will then perform the associated Meta-analysis to generate the forest plot (pooled estimated effect size Hazard Ratio (HR) and 95% Confidence Intervals (CI) values) using the random-effects model. Any publication bias will be assessed using the funnel plot symmetry, Orwin and Classic Fail-Safe N Test and Begg and Mazumdar Rank Correlation Test and Egger’s Test of the intercept. In cases where insufficient data occur, we will also perform a qualitative review. Discussion: This systematic review will explore COVID-19 clinical outcomes, especially survival in patients hospitalised with Acute Myocardial Infarction, by utilising a collection of previously published data on hospitalised COVID-19 patients and Myocardial Infarction. Highlighting these prognostic survival analyses of COVID-19 patients with AMIT will have significant clinical implications by allowing for better overall treatment strategies and patient survival estimates by offering clinicians a method of quantitatively analysing the pattern of COVID-19 cardiac complications.
Chemoresistance is a significant barrier to combating head and neck cancer, and decoding this resistance can widen the therapeutic application of such chemotherapeutic drugs. This systematic review and meta-analysis explores the influence of microRNA (miRNA) expressions on chemoresistance in head and neck cancers (HNC). The objective is to evaluate the theragnostic effects of microRNA expressions on chemoresistance in HNC patients and investigate the utility of miRNAs as biomarkers and avenues for new therapeutic targets. Methods: We performed a comprehensive bibliographic search that included the SCOPUS, PubMed, and Science Direct bibliographic databases. These searches conformed to a predefined set of search strategies. Following the PRISMA guidelines, inclusion and exclusion criteria were framed upon completing the literature search. The data items extracted were tabulated and collated in MS Excel. This spreadsheet was used to determine the effect size estimation for the theragnostic effects of miRNA expressions on chemoresistance in HNC, the hazard ratio (HR), and 95% confidence intervals (95% CI). The comprehensive meta-analysis was performed using the random effects model. Heterogeneity among the data collected was assessed using the Q test, Tau2, I2, and Z measures. Publication bias of the included studies was checked using the Egger’s bias indicator test, Orwin and classic fail-safe N test, Begg and Mazumdar rank collection test, and Duval and Tweedie’s trim and fill methods. Results: After collating the data from 23 studies, dysregulation of 34 miRNAs was observed in 2189 people. These data were gathered from 23 studies. Out of the 34 miRNAs considered, 22 were up-regulated, while 12 were down-regulated. The TaqMan transcription kits were the most used miRNA profiling platform, and miR-200c was seen to have a mixed dysregulation. We measured the overall pooled effect estimate of HR to be 1.516 for the various analyzed miRNA at a 95% confidence interval of 1.303–1.765, with a significant p-value. The null hypothesis test’s Z value was 5.377, and the p-value was correspondingly noted to be less than 0.0001. This outcome indicates that the risk of death is determined to be higher in up-regulated groups than in down-regulated groups. Among the 34 miRNAs that were investigated, seven miRNAs were associated with an improved prognosis, especially with the overexpression of these seven miRNAs (miR15b-5p, miR-548b, miR-519d, miR-1278, miR-145, miR-200c, Hsa- miR139-3p). Discussion: The findings reveal that intricate relationships between miRNAs’ expression and chemotherapeutic resistance in HNC are more likely to exist and can be potential therapeutic targets. This review suggests the involvement of specific miRNAs as predictors of chemoresistance and sensitivity in HNC. The examination of the current study results illustrates the significance of miRNA expression as a theragnostic biomarker in medical oncology.
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