Article Data

  • Views 2646
  • Dowloads 183

Original Research

Open Access

Clinical characteristics of critically ill patients with 2019 novel coronavirus (COVID-19): do we need a new triage system?

  • Mehmet Akif YAZAR1
  • Yasin TIRE1
  • Fatih YUCEL2
  • Hasan SENAY2
  • Ercan KURTIPEK3
  • Nevin SEKMENLI4
  • Guzide YAZAR4

1Department of Anesthesiology and Reanimation, University of Health Sciences, Konya Training and Research Hospital, 42040 Konya, Turkey

2Department of Intensive Care, University of Health Sciences, Konya Training and Research Hospital,42040 Konya, Turkey

3Department of Chest Diseases, University of Health Sciences, Konya Training and Research Hospital,42040 Konya, Turkey

4Department of Radiology, University of Health Sciences, Konya Training and Research Hospital,42040 Konya, Turkey

DOI: 10.22514/sv.2021.066 Vol.17,Issue 3,May 2021 pp.121-129

Submitted: 10 February 2021 Accepted: 09 March 2021

Published: 08 May 2021

*Corresponding Author(s): Mehmet Akif YAZAR E-mail: makifyazar@hotmail.com

Abstract

Background: This expanded study presents the characteristic features of patients with novel Coronavirus 2019 (COVID-19) in intensive care units (ICUs). On the other hand, it has revealed an issue of triage on admission to ICUs for patients with COVID-19.

Methods: The critically ill patients’ characteristics, laboratory findings, treatment and outcomes data were recorded. All chest computed tomography (c-CT) images were reviewed by two experienced radiologists in chest imaging. Collected data were compared between the confirmed and suspected COVID-19 cases. Moreover, some detected parameters were evaluated via c-CT findings among suspected COVID-19 cases.

Results: The study population included 105 patients hospitalized in ICUs. Twenty-seven patients (25.7%) were confirmed COVID-19 through real-time reverse-transcription polymerase-chain-reaction (RT-PCR) assay, and 78 patients (74.3%) were suspected COVID-19. There was a significant difference between the confirmed COVID-19 and suspected COVID-19 patients in terms of PaO2/FiO2 ratio, APACHE II scoring system, the number of comorbidities. Interestingly, in suspected cases, mean PaO2/FiO2 ratio, APACHE II score, and the number of comorbidities were significantly higher in patients with typical c-CT findings for COVID-19 (P = 0.038, P = 0.034 and P = 0.020, respectively). Considering all three parameters, 33.3% of cases with typical CT findings could be reconsidered as highly probable COVID-19 infections. Moreover, 16.7% of the cases with atypical CT findings could be excluded and the unnecessary burden on ICUs could be reduced.

Conclusion: In many contagious diseases such as COVID-19, for a new triage system, specific characteristics, selected general physiological findings, and typical laboratory parameters may be standardized in addition to RT-PCR testing and c-CT examination.


Keywords

Coronavirus; COVID-19; SARS CoV-2; Intensive care unit; Critical illness; Triage


Cite and Share

Mehmet Akif YAZAR,Yasin TIRE,Fatih YUCEL,Hasan SENAY,Ercan KURTIPEK,Nevin SEKMENLI,Guzide YAZAR. Clinical characteristics of critically ill patients with 2019 novel coronavirus (COVID-19): do we need a new triage system?. Signa Vitae. 2021. 17(3);121-129.

References

[1] World Health Organization. Novel coronavirus (2019-nCoV): situation report-119. 2020. Available at: https://www.who.int/docs/default-source/coronaviruse/situation-reports/ 20200518-covid-19-sitrep-119.pdf?sfvrsn=4bd9de25_4 (Accessed: 18 May 2020).

[2] Chan JF, Yuan S, Kok K, To KK, Chu H, Yang J, et al. A familial cluster of pneumonia associated with the 2019 novel coronavirus indicating person-to-person transmission: a study of a family cluster. Lancet. 2020; 395: 514–523.

[3] Rothe C, Schunk M, Sothmann P, Bretzel G, Froeschl G, Wallrauch C, et al. Transmission of 2019-nCoV infection from an asymptomatic contact in Germany. New England Journal of Medicine. 2020; 382: 970–971.

[4] Wang Z, Yang B, Li Q, Wen L, Zhang R. Clinical features of 69 cases with coronavirus disease 2019 in Wuhan, China. Clinical Infectious Diseases. 2020; 71: 769–777.

[5] Chen L, Liu H, Liu W, Liu J, Liu K, Shang J, et al. Analysis of clinical features of 29 patients with 2019 novel coronavirus pneumonia. Chinese Journal of Tuberculosis and Respiratory Diseases. 2020; 43: 203–208.(In Chinese)

[6] Xu X, Yu C, Qu J, Zhang L, Jiang S, Huang D, et al. Imaging and clinical features of patients with 2019 novel coronavirus SARS-CoV-2. European Journal of Nuclear Medicine and Molecular Imaging. 2020; 47: 1275–1280.

[7] Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020; 395: 507–513.

[8] Bansal Garg I, Srivastava S, Rai C, Kumar V, Hembrom A, Ghosh N, et al. Coronavirus (COVID-19): prognostic risk associated with comorbidities and age. International Journal of Recent Scientific Research. 2020; 37983–37986.

[9] Fehr AR, Channappanavar R, Perlman S. Middle east respiratory syndrome: emergence of a pathogenic human coronavirus. Annual Review of Medicine. 2017; 68: 387–399.

[10] Huang C, Wang Y, Li X, Ren L, Zhao J, Hu Y, et al. Clinical features of patients infected with 2019 novel coronavirus in Wuhan, China. Lancet. 2020; 395: 497–506.

[11] Wang D, Hu B, Hu C, Zhu F, Liu X, Zhang J, et al. Clinical characteristics of 138 hospitalized patients with 2019 novel coronavirus-infected pneumonia in Wuhan, China. The Journal of the American Medical Association. 2020; 323: 1061–1069.

[12] World Health Organization. Laboratory testing for 2019 novel coronavirus (2019-nCoV) in suspected human cases. 2020. Available at: https://www.who.int/publications-detail/laboratory-testing-for-2019-novel-coronavirus-in-suspected-human-cases-20200117 (Accessed: 17 May 2020).

[13] Chung M, Bernheim A, Mei X, Zhang N, Huang M, Zeng X, et al. CT imaging features of 2019 novel coronavirus (2019-nCoV). Radiology. 2020; 295: 202–207.

[14] Ranieri VM, Rubenfeld GD, Thompson BT, Ferguson ND, Caldwell E, Fan E, et al. Acute respiratory distress syndrome: the Berlin definition. The Journal of the American Medical Association. 2012; 307: 2526–2533.

[15] Kidney Disease: Improving Global Outcomes (KDIGO) Acute Kidney Injury Work Group. KDIGO Clinical practice guideline for acute kidney injury. KDIGO. 2012; 2: 1–138.

[16] Hansell DM, Bankier AA, MacMahon H, McLoud TC, Müller NL, Remy J. Fleischner Society: glossary of terms for thoracic imaging. Radiology. 2008; 246: 697–722.

[17] Shi H, Han X, Jiang N, Cao Y, Alwalid O, Gu J, et al. Radiological findings from 81 patients with COVID-19 pneumonia in Wuhan, China: a descriptive study. Lancet Infectious Diseases. 2020; 20: 425–434.

[18] Pan F, Ye T, Sun P, Gui S, Liang B, Li L, et al. Time course of lung changes at chest CT during recovery from coronavirus disease 2019 (COVID-19). Radiology. 2020; 295: 715–721.

[19] Wu Z, McGoogan JM. Characteristics of and important lessons from the Coronavirus Disease 2019 (COVID-19) outbreak in China: summary of a report of 72,314 cases from the Chinese center for disease control and prevention. The Journal of the American Medical Association. 2020; 323: 1239–1242.

[20] Yang X, Yu Y, Xu J, Shu H, Xia J, Liu H, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. Lancet Respiratory Medicine. 2020; 8: 475–481.

[21] Murthy S, Gomersall CD, Fowler RA. Care for critically ill patients with COVID-19. The Journal of the American Medical Association. 2020; 323: 1499.

[22] Guan W-J, Liang W-H, Zhao Y, Liang H-R, Chen Z-S, Li Y-M, et al. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. The European Respiratory Journal. 2020; 55: 2000547.

[23] Wagner PD. Ventilation/perfusion relationships. In Hamid, Shannon, Martin (eds.) Physiological basis of respiratory disease (pp. 164-184). USA: People’s Medical Publishing House. 2005.

[24] Franklin C. Triage considerations in medical intensive care. Archives of Internal Medicine. 1990; 150: 1455–1459.

[25] Chen T, Wu D, Chen H, Yan W, Yang D, Chen G, et al. Clinical characteristics of 113 deceased patients with coronavirus disease 2019: retrospective study. British Medical Journal. 2020; 368: m1091.

[26] Ye Q, Wang B, Mao J. The pathogenesis and treatment of the ‘Cytokine Storm’ in COVID-19. Journal of Infection. 2020; 80: 607–613.

[27] World Health Organization. Clinical management of severe acute respiratory infection (SARI) when COVID-19 disease is suspected: interim guidance. 2020. Available at: https://www.who.int/publications-detail/clinicalmanagement-of-severe-acute-respiratory-infection-when-novelcoronavirus-

(ncov)-infection-is-suspected (Accessed: 15 March 2020).

[28] Arabi YM, Murthy S, Webb S. COVID-19: a novel coronavirus and a novel challenge for critical care. Intensive Care Medicine. 2020; 46: 833–836.

[29] Phua J, Weng L, Ling L, Egi M, Lim C, Divatia JV, et al. Intensive care management of coronavirus disease 2019 (COVID-19): challenges and recommendations. Lancet Respiratory Medicine. 2020; 8: 506–517.

[30] de Wit E, van Doremalen N, Falzarano D, Munster VJ. SARS and MERS: recent insights into emerging coronaviruses. Nature Reviews Microbiology. 2016; 14: 523–534.

[31] Sheahan TP, Sims AC, Leist SR, Schäfer A, Won J, Brown AJ, et al. Comparative therapeutic efficacy of remdesivir and combination lopinavir, ritonavir, and interferon beta against MERS-CoV. Nature Communications. 2020; 11: 222.

[32] Wang M, Cao R, Zhang L, Yang X, Liu J, Xu M, et al. Remdesivir and chloroquine effectively inhibit the recently emerged novel coronavirus (2019-nCoV) in vitro. Cell Research. 2020; 30: 269–271.

[33] Yao X, Ye F, Zhang M, Cui C, Huang B, Niu P, et al. In vitro antiviral activity and projection of optimized dosing design of hydroxychloroquine for the treatment of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2). Clinical Infectious Diseases. 2020; 71: 732–739.

[34] Gautret P, Lagier JC, Parola P, Hoang VT, Meddeb L, Mailhe M, et al. Hydroxychloroquine and azithromycin as a treatment of COVID-19: results of an open-label non-randomized clinical trial. International Journal of Antimicrobial Agents. 2020; 56: 105949.

[35] Chen C, Zhang XR. Advances in the research of cytokine storm mechanism induced by corona virus disease 2019 and the corresponding immunotherapies. Chinese Journal of Burns. 2020; 36: E005.

[36] Cai Q, Yang M, Liu D, Chen J, Shu D, Xia J, et al. Experimental treatment with favipiravir for COVID-19: an open-label control study. Engineering. 2020; 6: 1192–1198.

[37] Ai T, Yang Z, Hou H, Zhan C, Chen C, Lv W, et al. Correlation of chest CT and RT-PCR testing for coronavirus disease 2019 (COVID-19) in China: a report of 1014 cases. Radiology. 2020; 296: E32–E40.

[38] Fang Y, Zhang H, Xie J, Lin M, Ying L, Pang P, et al. Sensitivity of chest CT for COVID-19: comparison to RT-PCR. Radiology. 2020; 296: E115-E117.

[39] Long C, Xu H, Shen Q, Zhang X, Fan B, Wang C, et al. Diagnosis of the Coronavirus disease (COVID-19): rRT-PCR or CT? European Journal of Radiology. 2020; 126: 108961.


Abstracted / indexed in

Science Citation Index Expanded (SciSearch) Created as SCI in 1964, Science Citation Index Expanded now indexes over 9,200 of the world’s most impactful journals across 178 scientific disciplines. More than 53 million records and 1.18 billion cited references date back from 1900 to present.

Journal Citation Reports/Science Edition Journal Citation Reports/Science Edition aims to evaluate a journal’s value from multiple perspectives including the journal impact factor, descriptive data about a journal’s open access content as well as contributing authors, and provide readers a transparent and publisher-neutral data & statistics information about the journal.

Chemical Abstracts Service Source Index The CAS Source Index (CASSI) Search Tool is an online resource that can quickly identify or confirm journal titles and abbreviations for publications indexed by CAS since 1907, including serial and non-serial scientific and technical publications.

Index Copernicus The Index Copernicus International (ICI) Journals database’s is an international indexation database of scientific journals. It covered international scientific journals which divided into general information, contents of individual issues, detailed bibliography (references) sections for every publication, as well as full texts of publications in the form of attached files (optional). For now, there are more than 58,000 scientific journals registered at ICI.

Geneva Foundation for Medical Education and Research The Geneva Foundation for Medical Education and Research (GFMER) is a non-profit organization established in 2002 and it works in close collaboration with the World Health Organization (WHO). The overall objectives of the Foundation are to promote and develop health education and research programs.

Scopus: CiteScore 1.0 (2022) Scopus is Elsevier's abstract and citation database launched in 2004. Scopus covers nearly 36,377 titles (22,794 active titles and 13,583 Inactive titles) from approximately 11,678 publishers, of which 34,346 are peer-reviewed journals in top-level subject fields: life sciences, social sciences, physical sciences and health sciences.

Embase Embase (often styled EMBASE for Excerpta Medica dataBASE), produced by Elsevier, is a biomedical and pharmacological database of published literature designed to support information managers and pharmacovigilance in complying with the regulatory requirements of a licensed drug.

Submission Turnaround Time

Conferences

Top