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VOLUME 6 , ISSUE 1 ( January-April, 2021 ) > List of Articles

RESEARCH ARTICLE

Impact of Triaging for COVID-19 Patients in a Tertiary Care Hospital in West India: A Retrospective Analysis of a Case Series

Srishti S. Jain, Anchin Kalia, Pallaavi Goel, Nimish Mathur, Puneet Rijhwani

Keywords : Biomarkers, Capacity management, COVID-19, Point-of-care testing, Radiological imaging, Triaging

Citation Information : Jain SS, Kalia A, Goel P, Mathur N, Rijhwani P. Impact of Triaging for COVID-19 Patients in a Tertiary Care Hospital in West India: A Retrospective Analysis of a Case Series. J Mahatma Gandhi Univ Med Sci Tech 2021; 6 (1):5-9.

DOI: 10.5005/jp-journals-10057-0145

License: CC BY-NC 4.0

Published Online: 31-08-2021

Copyright Statement:  Copyright © 2021; The Author(s).


Abstract

Introduction: Assessing the clinical severity of coronavirus disease-2019 (COVID-19) and triaging to appropriate levels of care is certainly one of the key elements in the success of managing COVID-19 patients. During the concluded wave of the pandemic, cases were categorized and cared for with set criteria prescribed by authorities. Other triaging criteria were included in contemporary international guidelines, but this hypothesis was never tested if anyone set is ever better than the other. Materials and methods: This is a case series of 165 deceased patients of COVID-19. All patients were categorized as per clinical disease severity and admitted to the designated care area after confirmation of SARS-CoV-2 infection as decided by the admitting doctors. We collected retrospective data from patient medical records and analyzed for medical history, comorbidity profiles, hematology investigations, organ function tests, computed tomography of the thorax, and point-of-care biomarker test (D-dimer, procalcitonin, NT-proBNP, Trop-T). These data were analyzed to compare the differences between the variables of ward and ICU patients by using XLstat software. Results: In this analysis of deceased patients’ case series, we found that there was no significant difference among the patients admitted to ward and ICU for initial demographic and biomarker variables and risk factors. Diabetes was the most commonly found comorbidity. The mortality rate among the ward and ICU (5.89 vs 6.67%, p value: 0.44) was also similar among both the cohorts. Conclusion: In this case series, we could conclude that both the cohorts were comparable at admission on demographic and laboratory parameter profile. Clinical significance: This analysis led us to the conclusion that our existing “triage criteria” for COVID-19 patients will need appropriate modification before the second wave sets in the region.


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