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Thrombotic events in Covid-19 patients using Meta-Analysis

Corona virus disease caused by severe acute respiratory virus 2 causes blockage of the blood vessel which leads to thrombosis. Thrombotic events in covid-19 patients results to hospitalizations and death. And incidence of thrombosis in covid-19 patients have been increasing in most regions of the world. Due to the huge inequalities between developed and developing countries, incidence rates remain highest in more developed regions, but mortality is relatively much higher in less developed countries due to a lack of early detection and access to treatment facilities. The aim of this study was to investigate the incidence of thrombosis in covid-19 by performing a systematic review on research articles talking about thrombotic events in covid-19 patients, carrying out a meta-analysis on the generated data to make an inference on the statistical result in order to create an information concerning complications covid-19 patients suffer from. Literatures with cases of covid-19 that reported D-dimer elevation and that followed the WHO standard for covid-19 diagnosis were included. Literatures excluded were studies with pregnant women, cancer patients and patients undergoing chemotherapy and with no approved ethical considerations. Information sources included only original literatures with initial search yielding 55 results from 4 databases. After reviewing titles and abstracts of all 55 literatures, 35 studies were further screened and 10 were included in the analysis representing 3359 patients. A forest plot using the R programming language was done, and an overall pooled estimate using the random effect model was 20 % (95 % confidence interval 12.0 % - 29.0 %) with heterogeneity of 96 %, and p <0.01. The incidence of thrombosis among moderate cases of c ovid-19 patients was 12 % with (95 % confidence interval 8.0 % - 18.0 %) with heterogeneity 93 %, and the incidence of thrombosis among severe Covid-19 patients was 22 % (95% confidence 10.0 %-37.0 %) with 97 % heterogeneity, and p <0.01.

Identiferoai:union.ndltd.org:UPSALLA1/oai:DiVA.org:his-22082
Date January 2022
CreatorsOkeke, Ugonna
PublisherHögskolan i Skövde, Institutionen för biovetenskap
Source SetsDiVA Archive at Upsalla University
LanguageEnglish
Detected LanguageEnglish
TypeStudent thesis, info:eu-repo/semantics/bachelorThesis, text
Formatapplication/pdf
Rightsinfo:eu-repo/semantics/openAccess

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