The Mortality Predictors in Patients with COVID-19 referred to the Emergency Department of Shahid Mohammadi Hospital in Bandar Abbas city in 2019

doi:10.21203/rs.3.rs-2244210/v1

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The Mortality Predictors in Patients with COVID-19 referred to the Emergency Department of Shahid Mohammadi Hospital in Bandar Abbas city in 2019

https://doi.org/10.21203/rs.3.rs-2244210/v1

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Background and aim:

Identifying the predictors of Mortality in COVID-19 is a way of identifying high-risk patients. Previous studies reported comorbidities and old age as the essential components of Covid-19 Mortality. The present study aims to determine the predictors of mortality in patients with COVID-19 referred to the emergency department.

Materials and method

The present descriptive-analytical study was conducted retrospectively on patients with confirmed COVID − 19 referred to the emergency department of Shahid Mohammadi Hospital in Bandar Abbas in 2019. Patient information, including age, gender, underlying disease, history of smoking, clinical symptoms, type of treatment, and laboratory findings, were extracted from the covid registry.

Results

In this study, 2478 patients with covid 19 were examined. The average age of the study subjects was 52.57 ± 16.41 years. Among them, 1371 people (55.3%) were men. The most common clinical symptom of the patients was shortness of breath (63.2%), and the most common underlying disease was hypertension (24.3%). 16.9% of examined covid 19 patients died. According to the results of multiple logistic regression analysis, with each 1-year increase in the age of the patients, the chance of death increased by 4.7% (P < 0.001). In addition, dyspnea increased the probability of death by 2.4 times, hypertension by 1.6 times, ischemic heart disease by 1.7 times, dyslipidemia by 3.6 times, stroke by 2.9 times, and malignancy by 2.2 times. (P < 0.05). The most important predictor of Mortality was CRP 3+, which increased the probability of Mortality in Covid-19 patients by almost 25 times (OR = 25.338, with a 95% confidence interval in the range of 1.978 to 324.668, P = 0.013). In addition, with each unit increase in ESR, the chance of death in patients increased by 3.3% (P < 0.001). On the other hand, among the clinical symptoms, anorexia (OR = 0.711, with a 95% confidence interval in the range of 0.506 to 0.999, P = 0.050) and receiving Macrolides (OR = 0.212, with a 95% confidence interval in the range 0.091 to 0.492, P < 0.001) had a protective role against mortality.

Conclusion

Based on the results of this study, old age, dyspnea, hypertension, ischemic heart disease, dyslipidemia, stroke, malignancy, CRP 3+, and high ESR were identified as predictors of Mortality in Covid-19 patients. Of course, receiving Macrolide and the presence of anorexia had a protective role against mortality in these patients.

The Covid-19 viral disease, which first emerged in China in December 2019 and now affects many countries worldwide, has been officially declared a pandemic by the WHO (1). Studies on the virus, the physiopathology of the disease, the course of the disease, laboratory findings, methods of diagnosis, prevention, and treatment are still ongoing. The disease can range from a superficial infection to more severe manifestations like acute respiratory failure syndrome. On the other hand, the number of patients in the phases before the dangerous phase is relatively high. The chance of entering the respiratory failure phase in hospitalized patients is between 17 and 29% (2). Various hypotheses have been proposed for faster diagnosis and prevention from entering this phase. These hypotheses focusing on how this new virus leads to human respiratory damage include; cytokine storm, genetic predispositions, disruption of the heme chain in hemoglobin, and its relationship with blood groups (3–5). Risk factors generally associated with severe covid-19 infection and mortality can be classified into demographic information, clinical symptoms, and laboratory findings (6). Cough and diarrhea are insignificant risk factors for the severity of Covid-19 (7). Some studies have looked at the risk factors associated with covid-19 infection, among which are; old age, travel to high-risk areas and contact with someone with severe symptoms(8). Although, there are also studies stating that the susceptibility to Covid-19 in children is similar to or less than that of adults (9). Earlier studies suggested that women had a higher risk of infection than men (8–11). Several components contribute to severe covid infections. These factors include age, race/ethnicity, gender, certain medical conditions, use of certain drugs, poverty and overcrowding, certain occupations, and Covid-19 infection during pregnancy. Various research has addressed different aspects of the risk factors related to the severity of the Covid-19 infection. Some researchers believe that clinical symptoms such as fever, chills, shortness of breath, depression, and laboratory symptoms such as a decrease in lymphocytes and an increase in CRP (C-reactive protein) can predict the chance of hospitalization (6). Older age, male gender, autoimmune disease, bilateral pulmonary infiltrations, decreased arterial blood oxygen saturation, increased lactate dehydrogenase, CRP and D-dimer, and neutrophil to lymphocyte ratio (NLR) greater than 4.21 at the age of fewer than 50 years can predict intensive care unit (ICU) hospitalization (6, 12).

Even though 5.94 million COVID-19 deaths were officially reported between January 1, 2020, and December 31, 2021, researchers calculate that excess mortality caused by the COVID-19 pandemic killed 18.2 million (95% confidence interval 17.1–19.6) individuals globally during that time. The COVID-19 pandemic resulted in an excess mortality rate of 120.3 deaths (113.1-129.3) per 100,000 people worldwide, with excess mortality rates exceeding 300 per 100,000 people in 21 countries. South Asia, North Africa, the Middle East, and eastern Europe were the regions with the most significant number of additional deaths brought on by COVID-19(13). In Iran, according to a study, the overall mortality rate is reported to be 10.5% (14). The average hospitalization in ICU is 12 days, and the mortality rate is 24% (15). When infection occurs with contact with a large amount of virus, the mortality rate is higher (16). Although respiratory failure is the most common cause of death, heart damage following cytokine storm and secondary infection has also been suggested as fatal factors in this disease. Underlying cardiovascular disease also increases the chance of death. In diabetic patients, cardiovascular and renal complications caused by high blood sugar, BMI, and lack of proper blood sugar control are among the factors that affect the mortality rate caused by Covid (17). The host’s genetic characteristics can help understand the difference in susceptibility, the severity of the disease, and outcomes of Covid-19 in different populations (18). A genetic defect on the X chromosome that results in an inadequate interferon response has been associated with developing the severe disease in adult men without the underlying disease (19). A specific genetic formula, such as the Neandertal variant, may be associated with a high rate of covid infection in a specific population and the severe form of the disease. This genetic variant does not exist in Africans. Its frequency is 30% in South Asia and 8% in Europe (20). Polymorphism in ACE2 DNA also affects the rate of infection and the severity of infection with Covid-19 in different people (21).

Identifying the predictors of Mortality in COVID-19 is a way of identifying high-risk patients. Identifying these patients can help clinicians choose the best treatment order for the admissions time and decrease the progression and mortality of the disease. According to the above explanations, the present study aims to determine the predictors of mortality in patients with COVID-19 referred to the emergency department of Shahid Mohammadi Hospital in Bandar Abbas, Iran.

This research examined 2478 patients with covid-19 referred to Shahid Mohammadi Hospital in Bandar Abbas, among which 16.95% died. The frequency of males in this study was 1371 (55.3%), which constituted 57.61% of the deceased cases, and no significant Gender difference between live and dead groups was observed based on the results obtained (P = 0.300). The most common symptom in the examined patients was shortness of breath (62.3%), followed by cough (54.3%) and fever (47.5%).

The most common underlying disease was hypertension (24.3%), followed by diabetes (20.9%) and ischemic heart disease (15.3%). Although, the mortality rate in patients with hypertension, diabetes, ischemic heart disease, dyslipidemia, stroke, malignancy, renal failure, and chronic liver disease was significantly more than patients without these underlying diseases (P < 0.05). No significant difference was observed between asthma/COPD and hypothyroidism with death. Most of the patients had received Macrolide (99.7%), antiviral (99.27%), and enoxaparin/heparin (94.6%), and mortality was significantly different in patients who had taken these drugs compared to those who had not taken these drugs (P < 0.001). There was a history of smoking in 3.2% of the patients, which had a significant difference between the two groups. A positive troponin test was observed in 1.17% of patients, with a significant difference in the two groups (P = 0.002).

CRP was negative in only (0.7%) of the patients, whereas (40.2%) of patients had CRP 3+. In this study, the average ESR in the Covid-19 patients was 74.16 ± 15.76 mm/h; the average serum creatinine was 391.33 ± 0.39 milligrams per deciliter platelet count was 250412.43 ± 49706.56 per microliter, all of which were significantly different in two groups (Table 1).

As seen In Table 2, the chance of death increased by 0.047% for each one-year increase in age. In addition, shortness of breath increases the probability of death by 2.4 times, and cough decreases by 27%. Among underlying diseases, high blood pressure and ischemic heart disease increased the death probability by 62% and 72%, respectively, and the chance of death in dyslipidemia, stroke, and malignancy increased by approximately 3.6, 3, and 2 times, respectively.

In addition, with each unit increase in ESR, the chance of death in patients increased by 3.3%. On the other hand, anorexia and receiving Macrolide had a protective role against mortality.

Table 1

DEMOGRAPHICS and Clinical results of Study Patients
	Total N = 2478	Survived N (%) = 2058(83.05%)	Not-Survived N (%) = 420(16.95)	P-value
Sex (male)	1371(55.3%)	1129(54.85%)	242(57.61%)	0.3
Clinical sign [N (%)]
Fever Headache Abdominal pain Rhinorrhea Sore throat Cough Vomit Diarrhea Olfactory disorder Shortness of breath Anorexia Muscular pain Weakness and lethargy	1176 (47.5%) 287(11.6%) 112(4.5%) 24(1%) 18(0.7%) 1346(54.3%) 163(6.6%) 173(7.0%) 74(3.0%) 1565(63.2%) 442(17.8%) 909(36.7%) 339(13.7%)	994(48.30%) 245(11.90%) 99(4.81%) 19(0.92%) 16(0.78%) 1150(55.88%) 147(7.14%) 153(7.43%) 60(2.92%) 1237(60.11%) 377(18.32%) 762(37.03%) 263(12.78%)	182(43.0%) 42(10.00%) 13(3.10%) 5(1.19%) 2(0.48%) 196(46.67%) 16(3.81%) 20(4.76%) 14(3.33%) 328(78.10%) 65(15.48%) 147(35.00%) 76(18.10%)	0.063 0.266 0.123 0.585 0.754 0.001 0.012 0.05 0.647 < 0.001 0.166 0.432 0.004
Underlying diseases [N (%)]
High blood pressure Diabetes Ischemic heart disease Asthma/COPD Dyslipidemia Stroke Malignant neoplasm Renal failure Chronic liver disease Hypothyroid	602(24.3%) 517(20.9%) 378(15.3%) 107(4.3%) 29(1.2%) 40(1.6%) 53(2.1%) 123(5.0%) 18(0.7%) 73(2.9%)	415(20.17%) 374(18.17%) 245(11.90%) 83(4.03%) 17(0.83%) 16(0.78%) 35(1.70%) 86(4.18%) 2049(99.56%) 58(2.82%)	187(44.5%) 143(34.0%) 133(31.7%) 24(5.7%) 12(2.9%) 24(5.7%) 18(4.3%) 37(8.8%) 9(2.1%) 15(3.6%)	< 0.001 < 0.001 < 0.001 0.122 0.002 < 0.001 0.001 < 0.001 0.001 0.405
Type of treatment [N (%)]
Antivirus Hydroxychloroquine Macrolide Enoxaparin/heparin Colchi Sin	2460(99.27%) 1331(53.7%) 2422(99.7%) 2345(94.6%) 881(35.6%)	2041(99.17%) 1110(53.94%) 2023(98.30%) 1967(95.58%) 724(35.18%)	419(99.8%) 221(52.6%) 399(95.0%) 378(90.0%) 187(44.5%)	0.304 0.622 < 0.001 < 0.001 0.390
Smoking Status (Yes) [N (%)]	79(3.2%)	53(2.58%)	26(6.2%)	< 0.001
CRP (Yes) [N (%)] Negative + 1 + 2 + 3	18(0.7%) 186(7.5%) 1279(51.6%) 995(40.2%)	17(0.83%) 179(8.70%) 1146(55.69%) 716(34.79%)	1(0.2%) 7(1.7%) 133(31.7%) 279(66.4%)	< 0.001
Troponin-Positive [N (%)]	29(1.17%)	17(0.83%)	12(2.9%)	0.002
ESR(mm/h) [Mean (SD)]	74.16 ± 15.76	72.88 ± 15.22	80.41 ± 16.85	< 0.001
Creatinine (mg/dl) [Mean (SD)]	1.33 ± 0.39	1.31 ± 0.29	1.38 ± 0.68	< 0.001
Platelet count (\(\varvec{\mu }\varvec{L})\) \(\left[\mathbf{M}\mathbf{e}\mathbf{a}\mathbf{n} \right(\mathbf{S}\mathbf{D}\left)\right]\)	250412.43 ± 49706.56	255008.26 ± 49360.52	227892.86 ± 45087.14	< 0.001

Table 2

THE ASSOCIATION OF DEMOGRAPHIC AND CLINICAL CHARACTERISTICS, underlying diseases and type of treatment WITH DEATH RISK, SEPERATELY.
	Odds Ratio	Confidence Interval (95%)	P-value
Age	1.047	(1.036–1.058)	< 0.001
Fever Abdominal pain Cough Vomit Diarrhea Shortness of breath Anorexia Weakness and lethargy	1.073 0.507 0.726 0.541 0.794 2.465 0.711 1.081	(0.831–1.385) (0.247–1.038) (0.563–0.936) (0.287–1.023) (0.449–1.402) (1.834–3.311) (0.506–0.999) (0.706–1.537)	0.589 0.063 0.014 0.059 0.426 < 0.001 0.050 0.665
Smoking Status	1.588	(0.882–2.857)	0.123
Creatinine (mg/dl)	1.318	(0.811–2.143)	0.265
Platelet count(\(\mu L)\)	1.00	(1.00–1.00)	< 0.001
Troponin-Positive	1.065	(0.418–2.712)	0.895
ESR(mm/h)	1.033	(1.021–1.046)	< 0.001
underlying diseases
High blood pressure Diabetes Ischemic heart disease Asthma/COPD Dyslipidemia Stroke Malignant neoplasm Renal failure Chronic liver disease	1.621 1.197 1.722 1.014 3.611 2.985 2.177 0.468 2.331	(1.217–2.159) (0.892–1.604) (1.265–2.345) (0.578–1.780) (1.584–8.233) (1.452–6.138) (1.084–4.373) (0.158–1.382) (0.560–9.704)	0.001 0.230 0.001 0.961 0.002 0.003 0.029 0.169 0.245
Type of treatment
Macrolide Enoxaparin/heparin	0.212 0.523	(0.091–0.492) (0.193–1.415)	< 0.001 0.202
CRP
Negative + 1 + 2 + 3	REF 4.850 8.636 25.338	(0.346–68.062) (0.679-109.805) (1.978-324.668)	0.241 0.097 0.013

In the current study, 2478 patients with covid-19 referred to the emergency department of Shahid Mohammadi Hospital in Bandar Abbas in 2019 were examined. These patients' most common clinical symptoms were shortness of breath, followed by cough and fever. Considering the transmission of the SARS-CoV-2 virus, mainly through respiratory droplets, respiratory symptoms are more common than other symptoms in these patients. Although, different immune statuses, comorbidities, ways of virus transmission, and environmental conditions in different studies can also explain the different findings. In the current study, the most common underlying disease in the examined covid-19 patients was hypertension, followed by diabetes and ischemic heart disease. The present study identified old age, shortness of breath, hypertension, ischemic heart disease, dyslipidemia, stroke, malignancy, CRP 3 + and high ESR as the main predictors of mortality in covid-19 patients. On the other hand, receiving Macrolide and the presence of anorexia had a protective role against mortality in these patients.

The biomarkers of COVID-19 patients who survived compared to those who did not were significantly different at admission, according to a pooled study of 10 studies involving 1584 patients(22). in line with the present study, in the study of Qapanuri et al. increase in CRP was a predictor of death in patients with Covid-19 (23). Troponin, D-dimer, CRP, and WBCs levels were significantly higher in COVID-19 patients who died than in COVID-19 survivors. High troponin and WBC levels were considerably associated with families that lost more than one member compared to the unrelated COVID-19 patient control(24). In the present study, although there was no correlation between positive troponin and mortality in the multiple analysis, the mortality rate in patients with positive troponin was significantly higher than in patients with negative troponin. Enver Yüksel's study showed that The in-hospital mortality rate was considerably higher when the creatinine was most significant (25). Also, in the present study, the average creatinine was significantly higher in deceased patients. In terms of the relationship between the number of decreased platelet count and mortality, the findings of our and Homayouniyeh et al. studies are consistent. In the present study, the average number of platelets was significantly lower in the deceased patients compared to the surviving patients. There was also a significant relationship between the number of platelets and mortality in either univariate or multivariate analyses. Also, in YeşimIşler et al., In patients with COVID-19 pneumonia, platelet count, mean platelet volume, and mean platelet volume to platelet ratio may be related to mortality. (26, 27).

In most studies, in line with our findings, the same diseases, especially hypertension and diabetes, were among the most common underlying diseases in Covid-19 patients (23, 26, 28–32). In the cohort study of Mirjalili et al., cardiovascular disease, diabetes, chronic neurological disease, chronic lung disease, and malignancy increased the chance of death. Also, patients hospitalized in the ICU had a higher risk of death, and the mortality was higher in the old age group and those with underlying diseases (32). like our study, in Gozidehkar et al., age was recognized as a risk factor for death due to covid (28). Also, in most other studies like Moon et al.’s study, The highest number of deaths is related to the age groups of 66 to 70 years (29, 33). Moon et al.’s study also emphasize fever and body temperature as risk factors. However, in the case of fever, no significant relationship with mortality was seen in our study and Andriani et al.’s study (29, 34). Compared to the study of Mirjalili et al., one of the risk factors that was not investigated in the current study is the severity of Covid-19. In most of the previous studies, ICU hospitalization is also considered a measure of the severity of the disease. In terms of other predictors of mortality, the Mirjalili et al. study's results are almost consistent with this study. Also, in Tian et al.’s review study, the presence of underlying diseases such as hypertension, coronary artery disease, and diabetes had a significant relationship with mortality (35).Appleman et al. research shows that individuals with a history of CKD have significantly higher mortality and readmission rate. They also show a higher 12-week death and readmission rate of SARS-CoV-2 infected patients in nearly all CKD groups. In contrast, prior research mainly highlighted increased mortality among dialysis and KTx patients (36). In the study of Qapanuri, the frequency of chronic kidney failure, was significantly different between the deceased and survived groups (23). However, in multiple analysis, chronic renal failure was not identified as risk factors for covid-19 mortality in our study.

The mortality rate is reported to be 2.8% in men and 1.7% in women. Mortality in healthy people is 0.9% (36). The results of Albitar et al.’s and Zhang et al.’s study were consistent with the present study in terms of most of the predictors of mortality (37, 38), except for gender. In Albitar et al.’s study, the male gender was identified as a risk factor for death. However, there was no relationship between gender and death in the present study. Gender distribution in the patients investigated in these studies, the different severity of the disease in the patients of Zhang et al.’s study (the presence of mild disease in only three patients), the number of comorbidities and many other factors, including the time of the hospital visits, method of Covid-19 diagnosis. etc., are among the factors contributing to the discrepancy between studies regarding the association of gender with mortality.

In Du et al.’s study, age greater than or equal to 65 years, underlying cardiovascular or cerebrovascular disease, CD3 + and CD8 + T cell count less than or equal to 75 per microliter, and cardiac troponin I greater than or equal to 0.05 ng/ml, were associated with a significant increase in the risk of death due to Covid-19 pneumonia (34). In most terms, their outcomes are the same as ours. However, the numbers of these particular T cells were not measured in the present study, and probably the type of measured troponin, the sensitivity of the diagnostic test, and the cut point considered in Du et al.’s study are different from the current study. In addition, all patients in Du et al.’s study had covid-19 pneumonia, while in the present study, we had patients without lung involvement.

In the study of Homayouniyeh et al., among the clinical features, old age, low oxygen saturation, leukocytosis, low lymphocyte ratio, and decreased platelets were significantly associated with increased mortality. Also, a high RALE score in the initial radiograph, the presence of pleural effusion in the initial CT scan, the development of pleural effusion in the follow-up CT scan, and the deterioration of the involvement intensity score in the CT scan had a significant relationship with increased mortality (26). Another determinant of covid severity (i.e., low oxygen saturation) was proposed in this study. The severity of the disease was not assessed in our study, as mentioned above. However, the findings of this study with our study are consistent in terms of the relationship between old age and mortality.

According to the results of this study, the most common clinical symptom in the examined patients of Covid-19 was shortness of breath, and the most common underlying disease was hypertension. 16.9% of patients died. Old age, shortness of breath, hypertension, ischemic heart disease, dyslipidemia, stroke, malignancy, CRP 3+, and high ESR were predictors of Mortality in Covid-19 patients. However, receiving Macrolide and anorexia had a protective role against mortality in these patients. In future studies, imaging findings indicating the extent of lung involvement in Covid-19 patients and some other laboratory findings such as D-dimer and lactate dehydrogenase should be investigated as possible predictors of mortality in these patients.

This descriptive-analytical cross-sectional study was conducted retrospectively. In this census study, all patients over 18 years of age with confirmed covid-19 (PCR confirmation) referred to the emergency department of Shahid Mohammadi Hospital in Bandar Abbas in 2019 were included. After approving the research, receiving the code of ethics from the ethics committee of the Hormozgan Faculty of Medical Sciences (IR.HUMS.REC.1400.335) and obtaining the necessary permits by referring to the registry center for Covid-19 patients, demographic information (age/sex), clinical and laboratory findings were extracted based on a pre-designed checklist and analyzed using the SPSS version 25 software. In incomplete patient records, the cases were excluded from the study. Chi-square and Fisher’s exact tests were used to compare the qualitative variables between the deceased and survived Covid-19 patients. The Mann-Whitney test was used to compare the quantitative variables (according to the results of the Kolmogorov Smirnov test). Logistic regression was used to determine the predictors of mortality, so first, univariate logistic regression was used for each factor. Factors with a P-value less than 0.2 in univariate logistic regression were included in the final model (multiple logistic regression). A P-value less than 0.05 was considered the significance level.

Declarations

Ethics approval and consent to participate

The authors of the study certify that the study was performed in accordance with the ethical standards and was approved by the council of the Ethics Committee of Hormozgan University of Medical Sciences under the number IR.HUMS.REC.1400.335. Written informed consent was obtained from all participants and from a parent and/or legal guardian, in case the participant was not competent to make decision.

Consent for publication

NA.

Declarations

Competing interests

The authors declare that they have no competing interest.

Funding

The authors of this article would like to thank the Hormozgan University of Medical Sciences for its financial support.

Authors’ contribution

S.H. and L.A analyzed and interpreted the patient data. S.S. contributed in concept design. L.J., L.A. and S.S. contributed in data gathering and entry. S.H. and L.A. contributed in critical revision. S.H. and L.A were major contributors in writing the manuscript. All authors read and approved the final manuscript.

Acknowledgments

The authors of this article would like to thank the Hormozgan University of Medical Sciences for its financial support.

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List of abbreviations

CRP (C-Reactive Protein)

ESR (Erythrocyte Sedimentation Rate)

WHO (World Health Organization)

NLR (Neutrophil to Lymphocyte Ratio)

ICU (Intensive Care Unit)

ACE2 (Angiotensin Converting Enzyme)

COPD (Chronic Obstructive Pulmonary Disease)

WBC (White Blood Cell)

CKD (Chronic Kidney Disease)

KTx (Kidney Transplant)

RALE (Radiologic Assessment of Lung Edema)

Research constraints and solutions adopted

One of the limitations of this study was that the severity of the disease of Covid-19 in the patients was unknown. Some risk factors may not be associated with mortality in these patients but may be associated with severe disease. Covid-19 patients with severe disease who survive can also suffer from short-term or long-term complications, which highlights the importance of examining the severity of the disease.

HUMAN AND ANIMAL RIGHTS

No animals were used for studies that are the basis of this research. All the humans used were following the ethical standards of Ethics Committee of Hormozgan University of Medical Sciences.

No competing interests reported.

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The Mortality Predictors in Patients with COVID-19 referred to the Emergency Department of Shahid Mohammadi Hospital in Bandar Abbas city in 2019

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