Clinical Symptoms, Comorbidity Patterns, and Treatment Schemes in Hospitalized Patients with COVID-19 in Turkey

Abstract

This research aims to investigate the associations between comorbidities and clinical outcomes, specifically their impacts on mortality rates among COVID-19 inpatients, while also assessing the varying significance of different comorbidities. We conducted this study to understand the interplay between SARS-CoV-2 infection, socio-demographic factors, disease severity, and co-morbid conditions in a sample of 26,835 hospitalized COVID-19 cases. Our analysis extended to examining the frequency of infection symptoms, pre-existing health issues, treatment strategies, intensive care unit (ICU) and hospital stays, clinical symptoms, and radiological findings. Among the 26,883 cases analyzed, comprising 53.7% males and 53.3% females with an average age of 48.5 years, we observed mean clinical values for temperature, heart rate, respiratory rate, and blood pressure. Leveraging logistic regression modeling helped untangle the complex relationships and confounding variables influencing COVID-19 mortality. Notably, our findings underscored the significance of total length of stay, prolonged ICU stays exceeding ten days, and the presence of significant symptoms in affecting mortality rates among COVID-19 patients. These insights unveil potential trends crucial for informing future management strategies tailored to the needs of COVID-19 patients, emphasizing the importance of addressing comorbidities and optimizing care approaches for better outcomes.

1. Introduction

The coronavirus disease 2019 (COVID-19) pandemic stands as the paramount global health crisis since World War II, shaping our era profoundly. Originating in Asia in 2019, the virus swiftly traversed the globe, impacting every continent save Antarctica. Beyond its health ramifications, the pandemic has morphed into an unparalleled socio-economic crisis, leaving indelible marks on society. The profound social, economic, and political repercussions are evident, necessitating long-term recovery strategies and a commitment to leveraging the lessons learned [1].

In light of this, research efforts grounded in authentic COVID-19 data are crucial for fortifying our battle against the virus. Such endeavors serve as a cornerstone for crafting a cohesive global response, an investment essential for our collective future [2].

With this imperative in mind, our study delves into the intricate interplay between severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) infection and socio-demographic factors, disease severity, and comorbidities among 26,835 hospitalized COVID-19 patients. The investigation encompasses an array of facets, including the prevalence of symptoms, pre-existing health conditions, treatment modalities, duration of ICU and hospital stays, clinical manifestations, radiological findings, and the influence of comorbidities on disease progression.

Our primary objective is to dissect the relationships between comorbidities and clinical outcomes, with a specific focus on their impacts on inpatient mortality rates. Through this exploration, we aim to discern the varying degrees of influence different comorbidities wield on diverse outcomes, thereby enhancing our understanding of COVID-19’s complexities.

2. Materials and Methods

The study included the analysis of the data of patients admitted to six hospitals in Turkey between March 2020 and June 2022. The study included patients with positive laboratory confirmed test results and who had related symptoms for SARS-CoV-2 infection. The six hospitals from which the data was obtained from were level 3 general hospitals located in major cities of Türkiye. All hospitals were performing training and research activities in addition to healthcare services.

The analysis data included age; gender; accompanying common chronic non-communicable diseases such as cardiovascular and respiratory diseases, cancer, obesity, and diabetes; radiological findings; treatment received; daily clinical follow-up data involving the laboratory results; and the symptoms were recorded. Regarding COVID-19 symptoms, fever above 37.5 degrees Celsius (°), shortness of breath, diarrhea, vomiting/nausea, wheezing, and chest and abdominal pain were considered as symptoms of severity.

Patients without symptoms, despite confirmed positive laboratory results for SARS-CoV-2 infection, were excluded from the study.

The SARS-CoV-2 infection was diagnosed by a positive polymerase chain reaction (PCR) result for the specimen obtained from the nasal cavity.

The data were retrieved from the health information management systems of all hospitals. There are effective information management systems in these hospitals and all data on healthcare processes are recorded in the digital environment. Permission from the University and Ministry of Health and ethics committee approval from the European Commission Ethical Board (approval number: 4265850-14/08/2020) were obtained for the study. Statistical Package for the Social Sciences (SPSS) Version 24 package program was used for statistical analysis. In the collection of data, all data protection rules were applied in accordance with the personal data protection law, and all personal patient information was anonymized and masked. In addition, the data retrieved from the hospital information system, from different modules in the systems, were integrated and distributed according to the dependent and independent variables; the missing data were collected by evaluating the patient files and other hospital data collection systems one by one; and the reliability and accuracy of the data were ensured by medical staff.

3. Results

3.1. Inpatient with COVID-19’s Socio-Demographic Characteristics, Clinical Symptoms, and Morbidity Profile

The hospitalized patient profile analyzed in this paper pertains to a total of 26,883 cases, out of which 53.7% (14,332) were males and 46.3% (12,359) were females. The mean age was 48.53. Regarding age groups, depicted in Figure 1, 14.7% of the 26,883 inpatients treated in Turkey due to COVID-19 were in the 0–14 age group, while 10.5% were 15–29, 19.3% 30–49, 31.2% were 50–69, and 24.3% of them were 70 years or older.

Common symptoms observed among inpatients, apart from shortness of breath (46.1%), included cough (32.2%), fever (30.3%), anorexia (5.6%), muscle aches, sore throat, headache, fatigue/malaise, runny nose, wheezing, diarrhea, joint pain, and others. The various symptomatic expressions after contracting the infection are presented in Figure 2.

3.2. Comorbidity Among Inpatients with COVID-19

Figure 3 shows the percentage of the cases with comorbid conditions, and 10,086 (37.5%) out of 26,883 inpatient cases presented comorbidity. Age is certainly a significant variable in the comorbidity profile of inpatients with COVID-19. Regarding gender, female patients were found to have a higher load of comorbidity compared to males (38.3% vs. 37.1%).

It was found that chronic cardiac diseases, hypertension, and chronic pulmonary disease (COPD) stand out as the most common comorbid conditions among the inpatients, as presented in Figure 4. Asthma, obesity, and malignant neoplasm were also some important conditions.

As seen in

Table 1. Distribution of clinical findings among inpatients with COVID-19.

Clinical Findings	Number of Patients	Mean	Std. Deviation
Body Temperature	7166	37.4425	3.97024
Heart Rate	2401	89.2986	16.68733
Respiratory Rate	7128	21.2072	3.13834
Systolic Blood Pressure	7165	125.3097	19.08240
Diastolic Blood Pressure	7165	75.6529	14.33050
Oxygen Saturation	7168	93.2112	6.73100

, the mean age of the patients was 48.5 years old. In the distribution of some clinical findings, the mean body temperature was 37.4 °C, the mean heart rate was 89.3 beats per minute, the mean respiratory rate was 21.2 breaths per minute, the mean systolic blood pressure was 125.3 mmHg, and mean diastolic blood pressure was 75.7. mmHg. The mean oxygen saturation was recorded as 93.2%. Additionally, noninvasive was applied to 7% of cases in ICU and medical wards (n = 26,883).

When we look at the laboratory results of the patients with COVID-19 who were hospitalized in six hospitals in Turkey as listed in

Table 2. Laboratory test results among inpatients with COVID-19.

Lab Tests	Number of Patients	Mean	Std. Deviation
Hemoglobin	3690	12.76	2.886
Lymphocyte Count	1359	37.3224	151.42
Neutrophil Count	1356	45.1561	148.612
Hematocrit	6411	40.7986	25.48
Platelets	1394	295.3869	136.1
ALT_SGPT	1399	40.3593	55.6
AST_SGOT	5894	48.3524	35.3
Creatinine	1432	5.9009	18.8
Sodium	1310	139.4228	35.2
Potassium	1308	9.9469	14.4
CRP	1568	67.3245	93.2
Creatine Kinase	550	37.9328	163.7

, the hemoglobin average of the patients was 12.8 G/dL, hematocrit was 40.8%, and liver function test averages were 40.4 U/L for SGPT and 48.4 U/L for SGOT. C-reactive protein (CRP), recognized as the most sensitive laboratory test for diagnosing COVID-19, had a mean value of 67.4 mg/L (reference range: 0–5 mg/L), indicating a significantly elevated. A total of 6.5% of the patients were treated in the intensive care unit. The invasive procedures performed on patients treated in the intensive care unit and the distribution of some findings are presented in

Table 3. Interventions in ICU among inpatients with COVID-19 (n = 1749).

Interventions	Number of Patients	%
Prone positioning in ICU	1469	83.9
Invasive ventilation in ICU	841	48.0
High-flow nasal cannula oxygen therapy	195	11.7
Neuromuscular blocking agents	116	6.6
Renal replacement therapy	93	5.3
Extra corporeal life	79	4.5
Tracheostomy inserted	39	2.2

.

A total of 83.9% of the invasive procedures performed on patients treated in the intensive care unit were in the prone position, while invasive ventilation was applied to 48%, high-flow nasal cannula oxygen therapy was applied to 11.7%, renal replacement therapy was applied to 5.3%, and extra corporal life was applied to 4.5%. It is seen that a tracheostomy was carried out in 2.2% of patients.

As seen in Figure 5, the first treatment given to the COVID-19 patients hospitalized in the hospitals in Turkey between March 2020 and June 2022 was antiviral therapy (32.7%) with Ribavirin (32.3%). Corticosteroid, antifungal treatment, antibiotic, and heparin treatments followed antiviral treatments. The decisions regarding whether to start, date of the start, choice, dosage, and discontinuation of medicines were made entirely by physicians as there were no guidelines at the time, so there was a lack of consistency.

3.3. Factors Affecting Comorbidity Among Inpatients (n = 26,883)

This section examines the factors affecting comorbidity. As seen in

Table 4. Factors affecting comorbidity among inpatients (n = 28,883).

Factors	Comorbidity—Yes		Comorbidity—No		Pearson Chi-Square	p Value
	N	%	N	%
Gender
Male	5397	37.4	9016	62.9	4.538	p < 0.05
Female	4734	38.3	7620	61.7
Age group
0–14	457	11.7	3438	88.3	1.716125	p < 0.05
15–29	786	28.2	2000	71.8
30–49	1866	36.4	3257	63.6
50–69	3816	46.0	4476	54.0
70 and above	3035	47.1	3415	52.9
Outcome (n = 25,981)
Death	1759	18.0	2200	13.6	97.145	p < 0.05
Discharged	8029	37.5	13,393	62.5
Displaying symptoms
Yes	716	59.9	497	41.0	245.055	p < 0.05
No	9370	36.7	16,142	63.3
Radiology evidence related to COVID-19 (n = 7121)
No	458	15.8	2446	84.2	1518.122	p < 0.05
Yes	857	20.3	3360	79.7
Oxygen saturation
<95	992	26.8	2712	73.2	52,940	p < 0.05
>95	676	19.6	2788	80.5
Systolic blood pressure (n = 7165)
<135	4516	78.1	1264	21.9	35,311	p < 0.05
>135	978	70.6	407	29.4
Diastolic blood pressure (n = 7165)
>95	44	67.7	21	32.3	2862	p > 0.05
<95	5450	76.8	1650	23.2
Smoking
Yes	1406	14.5	841	5.2	665.271	p < 0.05
No	8287	35.0	15,379	65.0
Length of stay
<7 days	3304	36.8	5727	63.4	622.922	p < 0.05
>7 days	5040	60.4	4119	41.8
Length of stay in ICU
<10 days	207	26.8	566	73.2	21.565	p < 0.05
>10 days	144	40.6	211	59.4
Severity of hospitalization
in ICU	772	75.0	257	25.0	72.027	p < 0.05
in medical ward	9827	38.0	16,010	62.0

, the comorbidity percentages in patients with COVID-19 were found to be higher among females (38.3%) and in the 50–69 age group (46.0%) in the study group. These values are also statistically significant.

Inpatients with COVID-19 and comorbidities had a higher mortality rate compared to those without (18.0% vs. 13.6%). In patients with comorbidities, the rate of any symptoms associated with COVID-19 was 59.9%, while COVID-19 findings on tomography were found to be 20.3% in this group, and the relationship between them was found to be statistically significant.

The percentage of smoking in patients with comorbidities was more than twice as high as in those without (14.5%, 5.2%). Inpatients with COVID-19 and a chronic disease had a longer hospital stay of more than seven days compared to those without chronic disease (60.4%, 41.8%.) A total of 75.0% of patients with comorbidity were in the group of patients treated in the intensive care unit and whose disease progressed seriously.

3.4. Factors Affecting Mortality (n = 18,141)

Between March 2020 and June 2022, the mortality rate in the patients with COVID-19 who were hospitalized in six hospitals in Turkey was 15.2%, as listed in

Table 5. Distribution of some variables affecting the mortality among inpatients.

Factors	Death		Discharged		Pearson Chi-Square	p Value
	N	%	N	%
Gender
Male	2185	15.7	11,750	82.0	6193	p > 0.05
Female	1765	14.7	10,234	82.8
Age group
0–14	415	10.7	3458	88.8	468.497	p < 0.05
15–29	244	8.9	2496	89.5
30–49	620	12.5	4337	84.6
50–69	1397	17.3	6659	80.3
70 and above	1261	20.4	4916	76.2
Comorbidity
Yes	1759	17.9	8029	83.4	97.145	p < 0.05
No	2200	13.6	13,993	79.6
Radiologic evidence present
Yes	857	20.7	3283	77.8	346.319	p = 0.00
No	215	1.3	16,076
Length of stay
<7 days	1220	13.5	7811	86.5	57,770	p < 0.05
>7 days	1608	17.6	7550	82.4
Length of stay in ICU (n = 1128)
<10 days	96	12.4	677	87.6	343	p > 0.05
>10 days	33	9.3	322	90.7
Severity of hospitalization (n = 25,853)
in ICU	946	91.9	83	8.1	81.143	p < 0.05
in medical ward	3876	67.8	2107	32.2

, while this rate was 15.7% for males and 14.7% for females.

While the highest percentage of death was seen at the age of 70 and over, the percentage of death in patients with chronic diseases was 17.9%, This rate was 13.6% in those without chronic diseases, 20.7% of patients had severe COVID-19 findings on tomography, while 91.9% were treated in the intensive care unit and 12.4% stayed at the intensive care unit for more than 10 days.

3.5. Logistic Regression for the Factors Affecting Mortality Among COVID-19 Cases

A statistically significant relationship was found with many variables affecting the mortality rates of the COVID-19 patients hospitalized in six hospitals in six different regions of Turkey, as shown in Table 5. A logistic regression model was applied in order to control the interrelationships and confounding factors of the factors affecting death from COVID-19 and the results are listed in

Table 6. Logistic regression for the factors affecting mortality among inpatients.

Variables	B	SE	p Value	OR
Displaying COVID-19 symptoms	0.035	0.277	0.898	1.036
Age	−0.091	0.125	0.465	0.913
Sex	0.186	0.234	0.427	1.205
Length of stay > 7 days	0.894	1.724	0.604	2.444
Length of stay in ICU > 10 days	−0.322	1.728	0.852	0.725
Smoking	−0.071	0.356	0.842	0.931
Having Chronic Disease	−1.214	0.394	0.002	0.297
Systolic pressure > 135	0.072	0.312	0.818	1.075

B: Regression coefficient, SE: Standard error, OR: Unadjusted odds ratio.

. As a result of the model, it was found that total length of stay, length of stay in the ICU of more than ten days, and presence of any significant symptoms were significant factors affecting mortality among COVID-19 patients. If the patients stayed at the hospital for more than 7 days, the risk of dying increased 2.5 times, while being male presented a risk 1.2 times higher than being female, and, when systolic blood pressure was over 135, the risk was 1.05 times higher than for patients with normal systolic blood pressure.

4. Discussion and Conclusions

Recent studies across various countries have highlighted the correlation between comorbidities and disease outcomes. While comorbidities do not significantly affect the cure rate or mortality rate among general patients, they do exacerbate mortality and diminish cure rates among critical patients [3].

Age also emerges as a significant determinant of outcomes. Early analyses indicate that older patients, particularly those aged 65 and above with comorbidities, exhibit higher admission rates to the intensive care unit (ICU) and increased mortality rates from COVID-19 [4,5,6,7]. Studies from Ghana and Niger have underscored the adverse impact of increasing age and comorbidities, particularly high systolic blood pressure, on outcomes [8,9]. Hypertension emerges as the most prevalent comorbidity, affecting approximately 72% of patients in Ghana [8].

Similar trends of poor clinical outcomes among patients with comorbidities have been observed in early studies conducted in China and the UAE [10,11]. A study from Israel revealed that young adults with COVID-19 and co-existing conditions such as diabetes, obesity, hypertension, chronic renal failure (CRF), or chronic obstructive pulmonary disease (COPD) faced higher likelihoods of fatal outcomes compared to those without comorbidities [12]. The risk of mortality significantly increased with diabetes or hypertension in addition to CRF [13,14].

Systematic reviews and meta-analyses have identified cerebrovascular disease, cardiovascular disease (CVD), chronic lung disease, cancer, diabetes, and hypertension as the most strongly associated comorbidities with adverse outcomes [15,16,17]. Hypertension, diabetes, and respiratory diseases stand out as critical factors leading to severe and fatal cases [18,19]. HIV is also identified as a fatal comorbid condition in studies conducted in Nigeria and Africa [19,20], with females showing lower mortality rates compared to males [13,19].

Reviews also show that comorbidities linked to age, chronic inflammation, and dysregulated metabolism—such as hypertension, cardiovascular disease, and diabetes—are among the most prevalent. Chronic Kidney Disease, in particular, is strongly associated with mortality [21]. Given the interconnection of many comorbidities, patients often present with multiple conditions, necessitating multifaceted treatment approaches and inevitable polypharmacy for those with pre-existing conditions [22].

Although pre-existing health conditions or comorbidities have no direct impact on the cure rate and mortality rate of general patients, they have increased the mortality rate and reduced the cure rate of critical patients. However, it is not known which of these components has the strongest prognostic power in predicting adverse health outcomes in COVID-19, because there is a significant overlap between them. Based on the awareness stated above, we need comprehensive data to understand the complex and interrelated impact of socio-demographic factors and comorbidity on the transmission, incidence, and adverse outcomes of COVID-19.

There are significant limitations in the study. The retrospective design is one of the most important limitations, as well as the lack of a control group, which may decrease the significance of the interpretation. Nevertheless, the analysis included data from a considerably high number of cases, which might be considered an important strength.