Submit manuscript...
Journal of
eISSN: 2376-0060

Lung, Pulmonary & Respiratory Research

Letter to Editor Volume 7 Issue 3

Simple classification of COVID-19 patients

Askin Gülsen

Department of Pneumology, University of Lübeck, Germany

Correspondence: Askin Gülsen, MD, Department of Pneumology (MK-III), University of Lübeck, Germany, Ratzeburger Allee 160, 23538 Lübeck, Germany, Tel 49-451-50045063, Fax +49-451-50045004

Received: September 10, 2020 | Published: September 25, 2020

Citation: Gülsen A. Simple classification of COVID-19 patients. J Lung Pulm Respir Res. 2020;7(3):62-63. DOI: 10.15406/jlprr.2020.07.00230

Download PDF

Dear editor,

The severe acute respiratory syndrome coronavirus 2 causes the coronavirus disease (COVID-19), which was detected in Wuhan, China, in December 2019, and subsequently spread to other continents and countries, to affect 28.0 million people and cause 908,500 deaths (until 10.09.2020).1 The case-fatality rate of COVID-19 ranges from 1.6% to 16.0%, although the average rate is 3.5% worldwide.2 The mortality rate in patients younger than 19 years is 0%, but varies from 3% to 11% and 10% to 27% among individuals in the age range of 65–84 and >85 years.3 The common clinical symptoms of COVID-19 are cough, diarrhea, fever, headache, loss of smell or taste, myalgia or fatigue, pharyngitis, and dyspnea.4 The spectrum of disease severity in 80–90% of COVID-19 patients includes asymptomatic individuals and patients with signs of lower or upper respiratory tract infections, lobar or multilobar viral pneumonia, acute respiratory distress syndrome, and cytokine storm. Besides these, clinical findings of secondary infections, cardiomyopathy, and thrombosis may be observed.4

The research that has been reported in the literature compares patients as follows: (a) nonsevere/ severe; (b) non-intensive care unit (ICU)/ICU; (c) improvement/progression; (d) general/refractory; (e) common type/severe; (f) noninvasive mechanical ventilation (IMV)/IMV; (g) good/poor outcomes; and (h) survivors/non-survivors. Although classifications are recommended based on radiological imaging, also clinical classification is urgently needed.5 Therefore, a uniform stratification of COVID-19 patients is necessary to standardize the future research studies and to enable meta-analyses that can more appropriately evaluate the data.

With this objective, the following classification (Table-1) of COVID-19 patients seems reasonable and, in routine clinical practice, the patients can be switched between these classes.



Clinical findings 


asymptomatic patients

individuals without clinical signs



outpatients and patients with mild clinical symptoms or lower or upper respiratory tract infections.



patients requiring hospitalization, with lobar or multilobar pneumonia with/without the need for supplemental oxygen, or refractory to initial treatment.



patients who need ICU treatment, noninvasive or invasive mechanical ventilatory support, or with acute respiratory distress syndrome and/or non-pulmonary involvement.


very severe or critical

patients who need immunomodulatory therapy or with multiorgan failure and/or cytokine storm.

ICU, intensive care unit

Table 1 Simple clinical classification

In conclusion, this simple classification can facilitate an appropriate initial categorization of COVID-19 patients that can be improved further based on various findings that emerge over time. However, a clustering model through clinical cases correlating with the prognosis would be needed for a classification to be reliable.

Ethics committee approval

According to the rule of our institution, there is no requirement of ethics committee approval for editorial letter.

Informed consent

Not required.

Conflicts of interest

The author has stated explicitly that there are no conflicts of interest in connection with this article. 

Financial disclosure


Authorship and contributorship

A.G. Concept and design, data collection, interpretation of data, manuscript preparation, and drafting of the manuscript.




Creative Commons Attribution License

©2020 Gülsen. This is an open access article distributed under the terms of the, which permits unrestricted use, distribution, and build upon your work non-commercially.