Objective: This study aimed to investigate the association between hospitalization and admission symptoms, demographic information, laboratory results, and pre-existing chronic diseases in patients who sought care at the emergency outpatient clinic of a research hospital and were diagnosed with coronavirus disease of 2019 (COVID-19).

Material and Method: This retrospective cross-sectional study included 220 randomly selected patients who presented to the emergency outpatient clinic of a training and research hospital and were diagnosed with COVID-19. The patients were categorized into two groups, hospitalized and non-hospitalized, and an investigation was conducted to determine whether there were differences between the two groups regarding symptoms, chronic diseases, demographics, and laboratory data.

Results: Among the COVID-19 patients in the study, 50.9% had hypertension, 31.8% had diabetes, and 18.6% had chronic diseases, such as coronary artery disease. Thoracic computerized tomography (CT) scans of 83% of COVID-19 patients were consistent with COVID-19/viral pneumonia, and 92% were hospitalized. Regression analysis revealed that C-reactive protein levels and chest CT findings compatible with COVID-19/viral pneumo-nia, asthma positively and age, hemoglobine, myalgia-back/joint pain negatively predicted hospitalization.

Conclusion: The concordance of chest CT scans with COVID-19/viral pneumonia increased the likelihood of hospitalization by 32.43 times, while patients with asthma or chronic obstructive pulmonary disease had an 5.28 times higher risk. Contrary to expectations, hospitalization increased as age decreased. These parameters should be considered when making hospitalization decisions for individuals with suspected COVID-19.

Coronavirus disease of 2019 (COVID-19) is a rapidly spreading infectious disease. Although studies have revealed the symptoms and risk factors that may occur in COVID-19 patients, the presence of uncommon or unknown symptoms can delay the diagnosis and, con-sequently, the treatment of COVID-19¹.

Common symptoms of this infection, which can also occur asymptomatically, include fever, cough, and shortness of breath. In addition, symptoms such as headache, sore throat, runny nose, muscle and joint pain, weakness, loss of sense of smell and taste, and diarrhea can also be observed. In some severe cases, pneumonia, severe acute respiratory tract infection, kidney failure, and even death may develop².

Hospitalized adults and children and adults aged >60 years are less likely to show typical symptoms. Fever, cough, and shortness of breath were more common in men, while confusion, nausea and vomiting, diarrhea, chest pain, headache, and abdominal pain were more common in women. Confusion is frequently observed in patients > 60 years of age. Symptoms such as nausea and vomiting, headache, abdominal pain, and sore throat are more common in patients under the age of 30 years, and the frequency of these symptoms decreases with age^3,4.

Jain at al. suggested that shortness of breath is the only symptom sufficient for hospitalization in the intensive care unit⁵.

In this study, we investigated whether there was a relationship between hospitalization and admission symp-toms, demographic data, laboratory findings, and chro-nic diseases in patients who visited the emergency COVID-19 outpatient clinic of the training and rese-arch hospital and were diagnosed with COVID-19.

Patients and sample size
This retrospective cross-sectional study included 2,000 patients who attended the Training and Research Hos-pital COVID-19 outpatient clinic between November 1, 2020, and December 31, 2020. These patients were designated as the study population. Based on the criteria entered into our statistical model, we determined that the minimum sample size required for the study was 219 patients. We subsequently selected 220 patients through a simple random sampling method, ensuring that their data were accessible for inclusion in the study.

Inclusion and exclusion criteria
Patients included in the study were 18 years or older, tested positive for COVID-19 via PCR, presented with symptoms, and had a thoracic computed tomography (CT) evaluated for COVID-19 imaging. Complete data required for inclusion consisted of age, sex, blood urea nitrogen (BUN), creatinine, alanine aminotransferase (ALT), aspartate aminotransferase (AST), C-reactive protein (CRP), white blood cell (WBC) count, neutrophil count, lymphocyte count, hemoglobin, and platelet count (PLT).

Patients younger than 18 years of age, with negative COVID-19 PCR test results, pregnant and lactating patients, and patients with incomplete thoracic CT and laboratory values were not included in the study.

Study design
Patient symptoms at diagnosis, demographic data such as age and sex, chronic diseases diabetes mellitus (DM), coronary artery disease (CAD), hypertension (HT), asthma/chronic obstructive pulmonary disease (COPD), chronic renal failure (CRF), congestive heart failure (CHF), other chronic diseases, hospitalization decisions, laboratory findings, and imaging results were recorded.

The patients were divided into two groups: those who were hospitalized and those who were not. We investi-gated whether there was a difference in terms of symp-toms, comorbidity, and demographic and laboratory data in these patients.

In addition, to determine the factors predicting hospitalization, a model was created by evaluating findings such as age, AST, CRP, hemoglobin level, thoracic CT findings, myalgia-back/joint pain, CAD, HT, asthma-COPD, CRF, and weakness.

Ethical approval
The study was approved by the Ministry of Health and Clinical Research Ethics Committee of the Training and Research Hospital (decision number 2021/180 dated 21.06.2021). This study was conducted in accor-dance with the Declaration of Helsinki.

Statistical analyses
All data were analyzed in a computer environment using the SPSS 25.0package program. Categorical data were compared using the chi-squared test and Fisher's exact test. The conformity of continuous data to a nor-mal distribution was evaluated graphically using the Kolmogorov-Smirnov, skewness, and kurtosis tests. Variables other than hemoglobin were not normally distributed. An independent t-test was used to analyze data that met normality conditions, and the Mann-Whitney U test was used to analyze data that did not meet normality. Binary logistic regression analysis was used to estimate the hospitalization status of patients. The significance level for all analysis results was set at p <0.05.

The median age of the patients included in the study was 62 (22-93) years, of which 46.4% were female (n =102) . A total of 76.8% (n =169) of patients were hospitalized. Of the thoracic CT results, 182 (82.7%) were compatible with COVID-19 pneumonia, 9 (4.2%) were suspected to be COVID-19 pneumonia, and 29 (13.1%) were negative for COVID-19 pneumonia.

Cough, shortness of breath, weakness symptoms, and chronic diseases such as HT, DM, and CAD are frequ-ently observed in COVID-19 patients. The most com-mon complaint was cough (43.6%, n =96) and the most common chronic disease was hypertension (50.9%, n =112).

Thoracic CT of 83% of COVID-19 patients was com-patible with COVID-19/viral pneumonia, and this rate was 93.5% in hospitalized patients. There was a signi-ficant difference (p <0.001) between thoracic CT fin-dings compatible with COVID-19 pneumonia and hospitalization status. In other words, the rate of hospi-talization was higher in those whose thoracic CT findings were compatible with those of COVID-19 pneumonia.

Although the median age, lymphocyte count, and mean hemoglobin values of the hospitalized patients were significantly lower (respectively p <0.001, p <0.001, p :0.013) than those of the non-hospitalized patients, their CRP and AST levels were higher (p <0.001).

No statistically significant difference was found in the hospitalization of patients according to sex (p >0.05). The laboratory data according to hospitalization status are shown in table 1.

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Table 1: Comparison of laboratory data according to hospitalization status.

Significant differences were found between the presen-ce of shortness of breath and the absence of myalgia or back/joint pain at admission, in relation to hospitaliza-tion status (p <0.001) .

The symptoms, chronic diseases, demographic charac-teristics, and analysis results according to hospitaliza-tion status are shown in table 2.

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Table 2: Demographic characteristics and distribution of chronic diseases according to hospitalization status.

Other chronic diseases are found 12.7% (cerebrovascu-lar oclusion, Parkinson’s disease, atrial fibrillation, hypothyroidism, epilepsy, benign prostatic hyperplasia, dementia, osteoporosis, and bipolar disorder).

A regression model was established to estimate the hospitalization status of patients. The model was deve-loped using the following predictors: age, AST, CRP, hemoglobin, values, and thorax CT findings, myalgiaback/joint pain CAD, HT, asthma-COPD, CRF, and weakness. The correct classification rate was 89.1%, Cox&Snell R2 was 0.414 and Nagelkerke R2 was 0.626. CRP levels, thoracic CT findings consistent with COVID-19/viral pneumonia, and asthma-COPD were positive predictors of hospitalization. Conversely, age, hemoglobin levels, and myalgia-back/joint pain were statistically significant negative predictors (Table 3).

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Table 3: Evaluation of risk factors affecting the hospitalization status of the patients in the multivariate logistic regression model.

In the study, there was no significant difference in the prevalence of chronic diseases between hospitalized and non-hospitalized patients, except for asthma-COPD, which significantly influenced the decision to hospitalize. In terms of symptoms, shortness of breath was more in the hospitalized group, while myalgia-back/joint pain was less and this difference was statis-tically significant.

Zhang et al.⁶ found that being male was a risk factor for the decision to hospitalize COVID-19 patients. Haitao et al.⁷ observed that the rates of hospitaliza-tion and disease severity were higher in males. In the study, however, no difference was found in the hospita-lization status according to the gender of the patients.

In a study conducted by Salje et al.⁸ the mean age of patients hospitalized with the diagnosis of COVID-19 in France until May 2020 was 68 years, and hospitali-zation increased with age. In the study by the CDC COVID-19 Response Team, the mean age of the hospi-talized patients was found to be higher than that of patients who were not hospitalized; in our study, the mean age of the hospitalized patients was found to be significantly lower than that of the patients who were not hospitalized. Among patients diagnosed with COVID-19, 45% of hospitalizations and 80% of deaths related to COVID-19 are in the 65 years and older group⁹. The reason for this may be that the curfew imposed on people over 65 years old and with chronic diseases as of 11.03.2020 reduced their exposure to viral load.

According to the study conducted by Stokes et al.¹⁰ common symptoms in patients diagnosed with COVID-19 included cough (50.3%), fever (43.1%), shortness of breath (28.5%), and myalgia (36.1%). Chen et al.¹¹ found fever in 83% of patients, cough in 82%, shortness of breath in 31%, and myalgia in 11%. In our study, the symptoms and percentage of patients were cough (43.6%), shortness of breath (35.5%), weakness (33.6%), myalgia-back/joint pain (14.1%), fever (14.1%), other symptoms (general mood disorder, epistaxis, headache, chest pain; 12.3%) and GIS symptoms (10.9%). Consistent with the findings of Stokes and Chen, cough was the most common symp-tom in COVID-19 patients in our study.

Rodriguez-Morales claimed that the symptoms and their incidence rates in COVID-19 patients were fever (88.7%), cough (57.6%), and dyspnea (45.6%)¹². Guan suggested that fever was seen in 88% and cough in 70% of patients with COVID-19¹³.

It is suggested that myalgia in COVID-19 may be asso-ciated with blood lactate levels and could influence the course of the disease¹⁴. Our study evaluated the symptoms of patients at the time of presentation to the COVID-19 clinic, suggesting that myalgia symptoms may have been overlooked as an indication for hospita-lization, and that hospitalized patients tended to be younger.

In Petrilli et al.'s study^15, the prevalence rates of chronic diseases in patients diagnosed with COVID-19 were as follows: 42.7%, HT; 32.5%, dyslipidemia; 22.6%, DM; 14.9%, asthma/COPD; 13.3%, KAH; 12.3%, CRF; and 7%, CHF. In our study, the prevalen-ce rates of these diseases were 50.9% HT, 31.8% DM, 18.6% KAH, 12.7% other diseases, 7.7% asthma/COPD, 6.8% cancer, 5.9% dyslipidemia, 5% CRF, and 4.5% CHF. In a study by Wei-Jie-Guan et al.^13, the most common chronic diseases were HT, DM, and CAD, and in a study by Zhou et al., 75% DM, 62% HT, and 16% CAD¹⁶. Consistent with these fin-dings, in our study, HT and DM were the most com-mon chronic diseases in COVID-19 patients, which is consistent with the prevalence of HT and DM in Turkey.

Tao et al.¹⁷ showed that anemia detected within the first 24 h after hospitalization was associated with progression to severe COVID-19. Seung et al.¹⁸ reported that anemia at the time of admission was in-dependently associated with increased odds of all-cause mortality among patients hospitalized with COVID-19. In our study, the mean hemoglobin level was significantly lower in hospitalized patients, and hemoglobin levels were negatively associated with the likelihood of hospitalization.

Guan et al.¹³ showed that lymphocytopenia and leukopenia are more common in patients with severe disease than in those without. In a study conducted by Parasher et al.¹⁹ lymphopenia was found in most patients, and it was accepted as a poor prognostic criterion. In our study, lymphocyte counts were signifi-cantly lower in hospitalized patients.

Henry et al. observed significant elevations in inflammation and coagulation markers, heart and muscle damage, and liver and kidney dysfunction in hospitalized COVID-19 patients. Parasher also found high levels of AST, ALT, LDH, and neutrophil values in hospitalized COVID-19 patients¹⁹. In our study, AST levels were found to be higher in hospitalized patients.

Analysis of 16 retrospective studies showed that inf-lammatory markers, especially CRP, PCT, interleukin-6, and erythrocyte sedimentation rate, are associated with the severity of COVID-19. CRP elevation was also found to be common in the study by Singhal et al.²¹ In a study by Chen et al.^22, a high CRP level was associated with poor prognosis and was found more frequently in patients with dyspnea. In our study, CRP levels were significantly higher in hospitalized patients.

Lorant et al.^23, in their cohort study on COVID-19 patients examined at the time of application, showed that the first thoracic CT of 5.2% of the cases was normal and the remaining 94.8% was compatible with COVID-19/viral pneumonia. In a study in which a total of 84 articles and 5,340 patients were examined, 92.6% of the patients had thoracic CT results compatible with COVID-19/viral pneumonia²⁴. In two separate studies, a picture compatible with COVID-19/viral pneu-monia was observed in 89% and 97.2% of thoracic CT scans at the time of admission^25,26. Liu et al. ²⁷ reported that 37 (92.5%) of 40 COVID-19 patients followed in the hospital were compatible with thoracic CT with viral/COVID-19 pneumonia.

Thoracic CT findings of 82.7% of the patients in our study were compatible with COVID-19 pneumonia, while 92% of these patients were hospitalized.

Limitations
Our study has limitations, including its single-center design, absence of examination of patient follow-up data, lack of weight, blood pressure, SpO2, ferritin and d-dimer in the dataset.

In our study, the most common complaint in COVID-19 patients was cough (43.6%), and the most common chronic disease was HT (50.9% (n =112). Findings compatible with COVID-19/viral pneumonia were observed in 82.7% (n =112) of the thoracic CT scans, and 92% of these patients were hospitalized. Compatibility of CT toraks with COVID-19/viral pneumonia increases hospitalization 32.43 times, asthma-COPD 5.28 times, CRP 1.25 times, and decrease in age and hemoglobin. Contrary to popular beliefs, it is recom-mended to be careful about the need for hospitalization in young patients. It may be useful to consider these parameters when evaluating hospitalization decisions in patients with suspected COVID-19.

Ethical approval: The study was approved by the Ministry of Health and Clinical Research Ethics Com-mittee of the Training and Research Hospital (decision number 2021/180 dated 21.06.2021).

Conflict of Interest: The authors declare no conflicts of interest with any institution and/or persons in this study.

Financial Disclosures: No financial support was rece-ived for this study.

REFERENCES

1) Jeon J, Baruah G, Sarabadani S, Palanica A. Iden-tification of risk factors and symptoms of COVID-19: analysis of biomedical literature and social media data. J Med Internet Res 2020; 22: e20509.

2) Health Minister of Turkiye COVID-19 Information Platform. COVID-19 Salgın Yönetimi ve Çalışma Rehberi. Covid-19 rehberi genel bilgiler epidemiyoloji ve tani. Ankara 2021.

3) Abdukahil SA, Abe R, Abel L et al. COVID-19 symptoms at hospital admission vary with age and sex: results from the ISARIC prospective multina-tional observational study. Infection 2021; 49: 889-905.

4) Larsen JR, Martin MR, Martin JD, Kuhn P, Hicks JB. Modeling the onset of symptoms of COVID-19. Front Public Health 2020; 8: 473.

5) Jain V, Yuan J-M. Predictive symptoms and co-morbidities for severe COVID-19 and intensive care unit admission: a systematic review and meta-analysis. Int J Public Health 2020; 65: 533-46.

6) Zhang J, Wang X, Jia X et al. Risk factors for disease severity, unimprovement, and mortality in COVID-19 patients in Wuhan, China. Clin Micro-biol Infect Off Publ Eur Soc Clin Microbiol Infect Dis 2020; 26: 767-72.

7) Haitao T, Vermunt JV, Abeykoon J, Ghamrawi R, Gunaratne M at al. COVID-19 and sex differences. Mayo Clin Proc 2020; 95: 2189-203.

8) Salje H, Tran Kiem C, Lefrancq N et al. Estima-ting the burden of SARS-CoV-2 in France. Science 2020; 369: 208-11.

9) CDC COVID-19 Response Team. Severe outco-mes among patients with coronavirus disease 2019 (COVID-19) - United States, February 12-March 16, 2020. MMWR Morb Mortal Wkly Rep 2020; 69: 343-6.

10) Stokes EK, Zambrano LD, Anderson KNet al. Coronavirus Disease 2019 case surveillance - Uni-ted States, January 22-May 30, 2020. MMWR Morb Mortal Wkly Rep 2020; 69: 759-65.

11) Chen N, Zhou M, Dong X et al. Epidemiological and clinical characteristics of 99 cases of 2019 no-vel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet Lond Engl 2020; 395: 507-13.

12) Rodriguez-Morales AJ, Cardona-Ospina JA, Gu-tiérrez-Ocampo E et al. Clinical, laboratory and imaging features of COVID-19: A systematic re-view and meta-analysis. Travel Med Infect Dis 2020; 34: 101623.

13) Guan Wj, Liang Wh, Zhao Y et al. Comorbidity and its impact on 1590 patients with COVID-19 in China: a nationwide analysis. Eur Respir J 2020; 55: 2000547.

14) Yükselmiş Ö. COVID-19 enfeksiyonunda miyalji şiddetinin prognoz üzerine etkisi. International Anatolia Academic Online Journal Health Scien-ces 2022; 8: 122-7.

15) Petrilli CM, Jones SA, Yang J et al. Factors associated with hospital admission and critical illness among 5279 people with coronavirus disease 2019 in New York City: prospective cohort study. BMJ 2020; 369: m1966.

16) Zhou F, Yu T, Du R et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective co-hort study. Lancet 2020; 395: 1054-62.

17) Tao Z, Xu J, Chen W et al. Anemia is associated with severe illness in COVID-19: A retrospective cohort study. J Med Virol 2021; 93: 1478-88.

18) Oh SM, Skendelas JP, Macdonald E et al. On-admission anemia predicts mortality in COVID-19 patients: A single center, retrospective cohort study. Am J Emerg Med 2021; 48: 140-7.

19) Parasher A. COVID-19: Current understanding of its pathophysiology, clinical presentation and treatment. Postgrad Med J 2021; 97: 312-20.

20) Henry BM, de Oliveira MHS, Benoit S, Plebani M, Lippi G. Hematologic, biochemical and immu-ne biomarker abnormalities associated with severe illness and mortality in coronavirus disease 2019 (COVID-19): a meta-analysis. Clin Chem Lab Med 2020; 58: 1021-8

21) Singhal T. A Review of Coronavirus Disease-2019 (COVID-19). Indian J Pediatr 2020; 87: 281-6

22) Chen G, Wu D, Guo W, Cao Y, Huang D et al. Clinical and immunological features of severe and moderate coronavirus disease 2019. J Clin Inves-tig 2020; 130: 2620-9.

23) Leonard-Lorant I, Severac F, Bilbault P, Muller J, Leyendecker P at al. Normal chest CT in 1091 symptomatic patients with confirmed Covid-19: frequency, characteristics and outcome. Eur Radiol 2021; 31: 5172-7.

24) Li J, Yan R, Zhai Y, Qi X, Lei J. Chest CT fin-dings in patients with coronavirus disease 2019 (COVID-19): a comprehensive review. Diagn In-terv Radiol 2021; 27: 621-32.

25) Long C, Xu H, Shen Q, Zhang X, Fan B et al. Diagnosis of the Coronavirus disease (COVID-19): rRT-PCR or CT? Eur J Radiol 2020; 126: 108961.

26) Falaschi Z, Danna PSC, Arioli R, Pasché A at al. Chest CT accuracy in diagnosing COVID-19 du-ring the peak of the Italian epidemic: A retrospec-tive correlation with RT-PCR testing and analysis of discordant cases. Eur J Radiol 2020; 130: 109192.

27) Liu H, Luo S, Li H, Zhang Y, Huang C et al. Clinical characteristics and longitudinal chest CT fea-tures of healthcare workers hospitalized with coronavirus disease 2019 (COVID-19). Int J Med Sci 2020; 17: 2644-52.