Epidemiological Characteristics and Mortality Risk Factors among COVID-19 Patients in Ardabil, Northwest of Iran

DOI: https://doi.org/10.21203/rs.3.rs-140018/v1

Abstract

Background: Coronavirus disease highly contagious, is prevalent in all age and sex groups infecting the respiratory system. The present study seeks to investigate the epidemiology and effective factors in mortality of patients with COVID-19 in Ardabil province, northwestern of Iran.

Methods: In a retrospective study, the hospitalized patients with laboratory diagnosed COVID-19 between February to August, 2020 were enrolled. Data registration portal was designated according to WHO recommendation. In this portal, demographic information, clinical presentation, laboratorial and imaging data were registered for patients in all hospitals in the same format. The Hosmer-Lemeshow guideline was used for variable selection in a multiple model.

Results: Of the patients involved 2812(50.3%) were male and 150 (2.7%) had a contact with a confirmed case of COVID-19 in the last 14 days. Pre-existing morbidity was reported in 1310 (23.4%) patients. Of all patients 477(8.5%) died due to COVID 19. The hospitalization in ICU had significant correlation with fever or chills, shortness of breath, aches and pains, runny nose and chest pain.

Conclusions: Hospitalization had the strongest effect on mortality followed by hospitalization in ICU, and higher age. This study showed that having some symptoms like aches and pains and headache can serve as preventive factors of mortality.

Background

Coronavirus is a group of single- stranded, enveloped RNA virus with a diameter of 120–180 nm and is divided into four groups: Alpha, Beta, Gamma and Delta. COVID-19 is a member of the Bete-coronavirus family[1, 2].This type of virus is highly contagious and infects the respiratory system. Direct contact and respiratory droplets are the most common way of transmitting the virus in the community but other ways have also been suggested [3]. Covid-19 is associated with the demographic situation of the community. The disease is prevalent in all age and sex groups, but the highest mortality is in older men with an average age of 75 years who have a history of diseases such as cardiovascular diseases, diabetes, high blood pressure, chronic respiratory diseases, cancer or previous surgery [4, 5]. According to the World Health Organization's (WHO) weekly report, as of October 4, 2020, there have been 35,347,404 confirmed cases of the disease of which 1,039,406 were mortality rate the highest number of it reported at 208,433 and 103,569 in the United States and India[6]. According to various studies, 18 to 33% of patients admitted to the hospital need mechanical ventilation, and up to 20% of patients are admitted to the ICU [710]. The most common symptoms of the disease include fever, cough, shortness of breath, fatigue and muscle pain that are observed in most patients and other symptoms such as diarrhea, headache and nausea have also been reported with a low percentage [11, 12]. Given that that no vaccine has been successfully developed to prevent COVID-19 to date, public health measures to control the infection are necessary to limit the global spread of the virus to reduce the incidence of COVID-19. It is essential to limit travel, human-to-human transmission in order to reduce secondary infections in close contact with health care personnel and to prevent further spread of the disease. Many efforts have been made to slow the progression of the disease in order to provide or buy time for better public health care systems, better description of COVID − 19 to guide public health advice and timely development of diagnosis, treatment and vaccines[1315]. However, in some countries such as Iran, the death toll is still alarmingly high. The aim of this study is to investigate the epidemiology and effective factors in mortality of patients with COVID-19 in Ardabil province, northwestern of Iran so that by identifying these factors we can provide basic proceedings for its control and prevention.

Materials And Methods

This retrospective cohort study was performed on 5587 patients in Ardabil, northwest of Iran. All patients who were admitted in the hospitals of Ardabil province from February to August 2020 were recruited in the study. During this pandemic, ten hospitals were allocated for COVID- 19 in Ardabil province. All needed data were registered in the COVID-19 case registration portal at Ardabil University of Medical Sciences. The data were obtained retrospectively from this portal. Data registration portal was designated according to WHO recommendation. In this portal, demographic information, clinical presentation, laboratorial and imaging data was registered for patients in all hospitals in the same format.

The patients who were diagnosed with the COVID-19 according to WHO guidelines has been registered in the mentioned portal. The outcome was defined as death (non-survivor) or discharge (survivor). The criteria for discharge were the improvement of the general status and respiratory symptoms, absence of fever for at least 3 days, chest CT scan improvement in both lungs, and at least one-time throat-swab or nasal-swap samples negative for SARS-CoV RNA assessment.

To perform simple statistical analysis, Chi square and Fisher’s exact test was used to evaluate the relationship among hospitalization, hospitalized in the ICU, and outcome of disease with the related factors. Univariate and multiple logistic regression models were run to examine the correlation among different variables and death due to COVID-19. The Hosmer-Lemeshow guidelines were used for variable selection in a multiple model[16]. Alpha level (p) for determining statistically significant differences was set at 0.5.

Results

The number of all registered patient were 5586. This study indicated that the mean age of the patients was indicates 52.25 ± 20.21 years. Of all patients, 2812(50.3%) were male and 150 (2.7%) had a contact with a confirmed case of COVID-19 in the last 14 days. Pre-existing morbidity was reported in 1310 (23.4%) patients. Of all patients 477(8.5%) of them died due to COVID-19.

Table 1 shows frequency of demographic characteristics and related factors to hospitalization, hospitalization in ICU and the outcome of the disease. As seen in table, hospitalization and the outcome of the disease had significant correlation with all studies variables (p < 0.05). Hospitalization in ICU was significantly was correlated with age, co morbidity, the outcome of the disease, and abnormal findings in chest radiography. However, hospitalization in ICU didn’t have a significant correlation with sex and previous contact with a confirmed case of COVID-19 (p > 0.05).

Table 1

Basic characteristics of patients according to hospitalization and disease status in Ardabil province, Northwest of Iran,2020.

Items

Hospitalization

Hospitalization in ICU

Outcome

Yes (%)

P value

Yes (%)

P value

Survive

Non survive

P value

 

 

N(%)

N(%)

Total

N=4188

 

N=124

 

N=5110

N=477

 

Age groups

 

 

 

 

 

 

 

Under 50

1509(36.0)

<0.001

37(29.8)

0.001

2432(47.6)

79(16.6)

<0.001

50 and higher

2679(64.0)

 

87(70.2)

 

2678(52.4)

398(83.4)

 

Sex

 

 

 

 

 

 

 

Male

2017(48.2)

<0.001

52(41.9)

0.082

2570(50.3)

205(43.0)

0.002

Female

2171(51.8)

 

72(58.1)

 

2540(49.7)

272(57.0)

 

Co morbidity

 

 

 

 

 

 

 

No

3025(72.2)

<0.001

77(62.1)

<0.001

3962(77.5)

315(66.0)

<0.001

Yes

1163(27.8)

 

47(37.9)

 

1148(22.5)

162(34.0)

 

Outcome 

 

 

 

 

 

 

 

Survive

3725(88.9)

<0.001

72(58.1)

<0.001

--

--

--

Non survive

463(11.1)

 

52(41.9)

 

--

--

 

Having  contact with a confirmed case of COVID 19 in last 14 days

 

 

 

 

 

 

 

No

4042(98.3)

<0.001

115(96.6)

0.568

148(3.0)

2(0.4)

0.001

Yes

68(1.7)

 

4(3.4)

 

4863(97.0)

470(99.6)

 

Abnormal findings in chest radiography

 

 

 

 

 

 

 

No

3676(87.8)

<0.001

103(83.1)

0.005

4641(90.8)

413(86.6)

0.003

Yes

512(12.2)

 

21(16.9)

 

469(9.2)

64(13.4)

 

The distribution of hospitalization, hospitalization in ICU and the outcome of the disease by clinical presentation are illustrated in Table 2. As indicated in Table 2 hospitalization have a significant correlation with all symptoms (except diarrhea). This table also shows that hospitalization in ICU have significant correlation with fever or chills, shortness of breath, aches and pains, runny nose and chest pain. This table revealed that outcome of disease has significant correlation with all symptoms except cough and sore throat.

Table 2

Clinical presentation according to the disease status in Ardabil province, Northwest of Iran,2020.

Items

Hospitalization

Hospitalization in ICU

Outcome

Yes (%)

P value

Yes (%)

P value

Survive

Non survive

P value

N = 4188

 

N = 124

 

N = 5110

N = 477

 

Fever or chills

             

No

1732(41.4)

< 0.001

46(37.1)

0.040

2432(47.6)

148(31.0)

< 0.001

Yes

2456(58.6)

 

78(62.9)

 

2678(52.4)

329(69.0)

 

Cough

             

No

1059(25.3)

< 0.001

41(33.1)

0.137

1406(27.5)

114(23.9)

0.090

Yes

3129(74.7)

 

83(66.9)

 

3704(72.5)

363(76.1)

 

Shortness of breath

             

No

1561(37.3)

< 0.001

24(19.4)

< 0.001

2299(45.0)

108(22.6)

< 0.001

Yes

2627(62.7)

 

100(80.6)

 

2811(55.0)

369(77.4)

 

Aches and pains

             

No

2844(67.9)

< 0.001

96(77.4)

0.007

3339(65.3)

352(73.8)

< 0.001

Yes

1344(32.1)

 

28(22.6)

 

1771(34.7)

125(26.2)

 

Sore throat

             

No

2463(58.8)

< 0.001

69(55.6)

0.712

2938(57.5)

262(54.9)

0.278

Yes

1725(41.2)

 

55(44.4)

 

2172(42.5)

215(45.1)

 

Headache

             

No

3460(82.6)

< 0.001

109(87.9)

0.055

4120(80.6)

419(87.8)

< 0.001

Yes

728(17.4)

 

15(12.1)

 

990(19.4)

58(12.2)

 

Runny nose

             

No

3964(94.5)

0.006

110(88.7)

0.001

4885(95.6)

429(89.9)

< 0.001

Yes

224(5.3)

 

14(11.3)

 

225(4.4)

48(10.1)

 

Diarrhea

             

No

4018(95.9)

0.130

120(96.8)

0.552

4881(95.5)

466(97.7)

0.025

Yes

170(4.1)

 

4(3.2)

 

229(4.5)

11(2.3)

 

Chest pain

             

No

3870(92.4)

< 0.001

95(76.6)

< 0.001

4792(93.8)

413(86.6)

< 0.001

Yes

318(7.6)

 

29(23.4)

 

318(6.2)

64(13.4)

 

In the univariate analysis, all possible effective factors were interred to the model. As can be seen in Table 3, older patients had higher odds of death. In addition, except having cough and sore throat, all other variables were related to death. This analysis indicated that having contact with a confirmed case of COVID-19 in last 14 days, aches and pains, headache and diarrhea have protective effect on death but other variables increase the odds of death.

Table 3

Related factors associated with death due to COVID 19 in Ardabil province, Northwest of Iran,2020.

 

Death due to COVID 19

 

Crude estimation

Adjusted estimation

Variables

OR

95%CI

P

OR

95%CI

P

Age (50 years old or higher)

4.57

3.57–5.86

< 0.001

3.11

2.39–4.06

< 0.001

Sex (being male)

1.34

1.11–1.62

0.002

1.20

0.98–1.47

0.072

Co-morbidity

1.77

1.45–2.17

< 0.001

1.25

1.00-1.56

0.055

Having contact with a confirmed case of COVID 19 in last 14 days

0.14

0.03–0.57

0.006

0.290

0.07–1.22

0.091

Having abnormal findings in chest radiography

1.53

1.16–2.03

0.003

1.00

0.74–1.35

0.996

Fever or chills

2.02

1.65–2.47

< 0.001

1.61

1.29–2.02

< 0.001

Cough

1.21

0.97–1.50

0.090

0.91

0.71–1.17

0.463

Shortness of breath

2.79

2.24–3.49

< 0.001

1.82

1.44–2.31

< 0.001

Aches and pains

0.67

0.54–0.83

< 0.001

0.71

0.57–0.89

0.003

Sore throat

1.11

0.92–1.34

0.278

--

--

--

Headache

0.58

0.43–0.76

< 0.001

0.64

0.47–0.86

0.004

Runny nose

2.43

1.75–3.37

< 0.001

1.54

1.06–2.24

0.022

Diarrhea

0.50

0.27–0.93

0.028

0.66

0.35–1.26

0.206

Chest pain

2.33

1.75–3.11

< 0.001

1.53

1.10–2.13

0.011

Hospitalization

12.28

7.19–20.99

< 0.001

5.66

3.28–9.78

< 0.001

Hospitalization in ICU

8.56

5.91–12.39

< 0.001

5.12

3.40–7.71

< 0.001

However, the result of multiple logistic regression model indicated that after adjusting for other factors, higher age (OR = 3.11), fever or chills (OR = 1.61), shortness of breath (OR = 1.82), aches and pains (OR = 0.71), headache (OR = 0.64), runny nose (OR = 1.54), chest pain (OR = 1.53), hospitalization (OR = 5.66), and hospitalization in ICU (OR = 5.12) were associated with death. In other word, among these related factors, having headache and aches and pains decreased the odds of death. However other factors are related with increased odds of death due to COVID-19 in all patients.

Discussion

In this study we reported the characteristics of all patients with COVID 19 in Ardebil province in the northwest of Iran. The clinical characteristics of these patients showed that the age (50-year-old and higher), hospitalization and hospitalization in ICU were the most important risk factors for death.

The present study also indicated that there is no gender difference in the prevalence of COVID-19 (49.7% in females vs. 50.3% in males). However, of deceased patients 43% was male. Some studies have reported greater prevalence of COVID-19 in males[1719]. A study conducted in Iran showed that males are in higher risk of mortality[20]. But, gender differences seems to have less importance as a prognostic factor for death compased with age [19]. Some studies also have indicated that the susceptibility of older males is higher than older females[21]. Anyway, in this study male gender didn’t have significant effect on death of patients in final adjusted regression logistic model.

Several studies have indicated that comorbidities are one the strongest predictors of death or sever COVID-19[2224]. Another study from Iran showed that having comorbidities had a significant effect on mortality [20]. Our findings showed that having any comorbidity was associated with hospitalization, hospitalization in ICU and outcome of disease. Also, in univariate analysis comorbidity increased the odds of death. However, this association didn’t remain significant in the final model. Further investigations are needed to assess the role of comorbidities on the mortality of COVID 19 in Iran.

Cough was to be the most common (74.7%) symptom among hospitalized patients followed by shortness of breath (62.7%). Of symptoms of the disease, we found that fever or chills, shortness of breath, aches and pains, headache, runny nose, diarrhea and chest pain were factors independently associated with mortality when adjusted for other variables. Among these symptoms, shortness of breath had the strongest effect on death (OR = 2.79). Some studies reported other frequencies for disease symptoms. For example among Italian and Spanish patients fever was reported as the most common symptom[19, 25]. Probably there are complex interactions between symptoms of COVID 19 and other independent variables like age and gender. Identifying such a complex relationship among independent variables may help to determine the portion of each symptom in death.

Our findings revealed that hospitalizing (OR = 12.28) and hospitalization in ICU (OR = 5.56) increased the odds of death among all patients. In line with our results, a study from Mexico reported that hospitalization (OR = 5.02) and hospitalization in ICU (OR = 1.79) were associated with death[26]. This could happen due to condition of patients at admission time. Patients with severe and critical conditions are more likely to hospitalized or hospitalized in ICU, resulting in a high in hospital mortality.

Conclusion

This study revealed that most of COVID-19 deceased patients were older than 50 years old. Hospitalization had the strongest effect on mortality followed by hospitalization in ICU, and higher age. This study showed that having some symptoms like aches and pains and headache can serve as preventive factors from mortality. Because of limitations in treatment and lack of medicines, proper prioritization considering risk and protective factors is very important in decreasing mortality rates.

Declarations

Acknowledgments

The authors thank Ardabil Health Central and all hospitals Stoff for enabling this study.

Authorship contribution statement

AAG and EMA: Study design, Data analysis, Writing - original draft, Writing - review & editing. DA, HG and SHA: Data analysis, Writing - review & editing. EMA and AAG: Data collection

Funding

This research was supported by a grant from Ardabil University of Medical Sciences (project No: 3899).

Ethics approval and consent to participate

The study was approved by the Ethics Committee of Ardabil University of Medical Sciences (IR.ARUMS.REC.1399.096). Permission to conduct the study was obtained from this committee.

 Consent for publication

Not applicable.

Competing interests

The authors declare no conflict of interest.

References

  1. Chan JF-W, To KK-W, Tse H, Jin D-Y, Yuen K-Y. Interspecies transmission and emergence of novel viruses: lessons from bats and birds. Trends in microbiology. 2013;21(10):544-55.
  2. He J, Tao H, Yan Y, Huang S-Y, Xiao Y. Molecular mechanism of evolution and human infection with the novel coronavirus (2019-nCoV). bioRxiv. 2020.
  3. Zhou P, Yang X-L, Wang X-G, Hu B, Zhang L, Zhang W, et al. A pneumonia outbreak associated with a new coronavirus of probable bat origin. nature. 2020;579(7798):270-3.
  4. Boccia S, Ricciardi W, Ioannidis JP. What other countries can learn from Italy during the COVID-19 pandemic. JAMA internal medicine. 2020.
  5. Lai C-C, Liu YH, Wang C-Y, Wang Y-H, Hsueh S-C, Yen M-Y, et al. Asymptomatic carrier state, acute respiratory disease, and pneumonia due to severe acute respiratory syndrome coronavirus 2 (SARSCoV-2): facts and myths. Journal of Microbiology, Immunology and Infection. 2020.
  6. Organization WH. Coronavirus disease (‎‎ COVID-19)‎‎: weekly epidemiological update. 2020.
  7. Richardson S, Hirsch JS, Narasimhan M, Crawford JM, McGinn T, Davidson KW, et al. Presenting characteristics, comorbidities, and outcomes among 5700 patients hospitalized with COVID-19 in the New York City area. Jama. 2020.
  8. Gold JA. Characteristics and clinical outcomes of adult patients hospitalized with COVID-19—Georgia, March 2020. MMWR Morbidity and mortality weekly report. 2020;69.
  9. Goyal P, Choi JJ, Pinheiro LC, Schenck EJ, Chen R, Jabri A, et al. Clinical characteristics of Covid-19 in New York city. New England Journal of Medicine. 2020.
  10. Cummings MJ, Baldwin MR, Abrams D, Jacobson SD, Meyer BJ, Balough EM, et al. Epidemiology, clinical course, and outcomes of critically ill adults with COVID-19 in New York City: a prospective cohort study. The Lancet. 2020.
  11. 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. The lancet. 2020;395(10223):497-506.
  12. Guan W-j, Ni Z-y, Hu Y, Liang W-h, Ou C-q, He J-x, et al. Clinical characteristics of 2019 novel coronavirus infection in China. MedRxiv. 2020.
  13. Xu Z, Peng C, Shi Y, Zhu Z, Mu K, Wang X, et al. Nelfinavir was predicted to be a potential inhibitor of 2019-nCov main protease by an integrative approach combining homology modelling, molecular docking and binding free energy calculation. BioRxiv. 2020.
  14. Tai DY. Pharmacologic treatment of SARS: current knowledge and recommendations. ANNALS-ACADEMY OF MEDICINE SINGAPORE. 2007;36(6):438.
  15. Chu C, Cheng V, Hung I, Wong M, Chan K, Chan K, et al. Role of lopinavir/ritonavir in the treatment of SARS: initial virological and clinical findings. Thorax. 2004;59(3):252-6.
  16. Jewell NP. Statistics for epidemiology: CRC Press; 2003.
  17. 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. Jama. 2020;323(11):1061-9.
  18. Chang D, Lin M, Wei L, Xie L, Zhu G, Cruz CSD, et al. Epidemiologic and clinical characteristics of novel coronavirus infections involving 13 patients outside Wuhan, China. Jama. 2020;323(11):1092-3.
  19. Biagi A, Rossi L, Malagoli A, Zanni A, Sticozzi C, Comastri G, et al. Clinical and epidemiological characteristics of 320 deceased CovidÔÇÉ19 patients in an Italian Province: a retrospective observational study. Journal of Medical Virology. 2020.
  20. Nikpouraghdam M, Farahani AJ, Alishiri G, Heydari S, Ebrahimnia M, Samadinia H, et al. Epidemiological characteristics of coronavirus disease 2019 (COVID-19) patients in IRAN: A single center study. Journal of Clinical Virology. 2020.
  21. Yang X, Yu Y, Xu J, Shu H, Liu H, Wu Y, et al. Clinical course and outcomes of critically ill patients with SARS-CoV-2 pneumonia in Wuhan, China: a single-centered, retrospective, observational study. The Lancet Respiratory Medicine. 2020.
  22. Chen R, Liang W, Jiang M, Guan W, Zhan C, Wang T, et al. Risk factors of fatal outcome in hospitalized subjects with coronavirus disease 2019 from a nationwide analysis in China. Chest. 2020.
  23. Li X, Xu S, Yu M, Wang K, Tao Y, Zhou Y, et al. Risk factors for severity and mortality in adult COVID-19 inpatients in Wuhan. Journal of Allergy and Clinical Immunology. 2020.
  24. Sepandi M, Taghdir M, Alimohamadi Y, Afrashteh S, Hosamirudsari H. Factors Associated with Mortality in COVID-19 Patients: A Systematic Review and Meta-Analysis. Iranian Journal of Public Health. 2020;49(7):1211.
  25. Iftime S, López-Azcona AF, Vicente-Miralles M, Descarrega-Reina R, Hernández-Aguilera A, Riu F, et al. Risk factors associated with mortality in hospitalized patients with SARS-CoV-2 infection. A prospective, longitudinal, unicenter study in Reus, Spain. bioRxiv. 2020.
  26. Carrillo-Vega MF, Salinas-Escudero G, Garcia-Peña C, Gutierrez-Robledo LM, Parra-Rodriguez L. Early estimation of the risk factors for hospitalisation and mortality by COVID-19 in Mexico. medRxiv. 2020.