https://socictopen.socict.org/files/original/0f3cd80623f9be17cfd82c8de67ce9d8.pdf fb5efde5991c58e454a150cec648aeab Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Coronavirus Description An account of the resource Dominio científico: Coronavirus Text A resource consisting primarily of words for reading. Examples include books, letters, dissertations, poems, newspapers, articles, archives of mailing lists. Note that facsimiles or images of texts are still of the genre Text. Dublin Core The Dublin Core metadata element set is common to all Omeka records, including items, files, and collections. For more information see, http://dublincore.org/documents/dces/. Title A name given to the resource Predictive Efficacy of Haematological Biomarkers in COVID-19 infection Creator An entity primarily responsible for making the resource Nadeem Ikram, Asma Nafisa, Rabia Anjum Description An account of the resource Introduction: The ongoing Corona Virus Pandemic is linked with high rates of morbidity and mortality globally. Early and effective predictors of clinical outcomes are urgently required to develop effective management protocols. Objective: To investigate the predictive efficacy of haematological biomarkers in Covid -19 infection Methods: Blood samples were drawn from COVID‐19 infected pneumonia patients. Baseline clinical information was collected and quantification of hemostatic variable was done.  Laboratory data both groups expired and recovered were compared using t- test, Mann Whitney- U test, chi squared-test and Kruskal Wallis test. Multivariate regression analysis was performed to determine the independent contribution of haematological variable in Covid19 related mortality. Receiver operating characteristic curve were drawn to find the predictive efficacy of significantly related parameters. Results: Out of 191 patients 68.1%  were male. D‐dimer (median 800 ng/mL; IQR 200‐3200) and NLR (median 10.40; IQR 3.20-22.80) were found to be predominantly raised and significantly correlated with Covid mortality in multivariate regression analysis. The optimum cutoff value of D-dimer to predict in-hospital mortality was 450 ng/ml with a sensitivity of 71.6% and a specificity of 95.8%. The optimum cutoff value of NLR to predict in-hospital mortality was 5.450 with a sensitivity of 70.1% and a specificity of 71%. Conclusion: D-dimer and NLR could be used as the significant indicators in predicting the mortality of COVID-19. Date A point or period of time associated with an event in the lifecycle of the resource 2020 Subject The topic of the resource COVID‐19 Identifier An unambiguous reference to the resource within a given context 10.37939/jrmc.v24i4.1517 Source A related resource from which the described resource is derived Journal of Rawalpindi Medical College Publisher An entity responsible for making the resource available Rawalpindi Medical University Coverage The spatial or temporal topic of the resource, the spatial applicability of the resource, or the jurisdiction under which the resource is relevant Medicine