Clinical Characteristics and Risk Factors for Mortality in COVID-19 Patients: A Retrospective Cohort Study
Correspondence Address :
Dr. Farzad Rahmani,
Associate Professor of Emergency Medicine, Faculty of Medicine, Tabriz University of Medical Sciences, Tabriz, Iran.
Introduction: Coronavirus Disease in 2019 (COVID-19) is globally a major factor in the mortality of patients. Hence, there is an immediate requirement to recognise the mortality predictors in the COVID-19 patients.
Aim: To identify the clinical features and risk factors for the mortality of adult patients suffering from COVID-19 in Sirjan, Iran.
Materials and Methods: In this retrospective cohort study, all demographic, clinical, laboratory data of COVID-19 patients who were admitted to hospitals of Sirjan city was collected from July to October 2020 and data was analysed in November 2020. In this period, 269 patients with COVID-19 were admitted. The findings based on the considered parameters of patients in the hospital was recorded; Univariable and multivariable logistic regression methods were applied to find the risk factors due to in hospital death.
Results: Out of 269 patients, 39 patients (14.5%) died in the hospital and the rest were discharged. A total of 152 (56.5%) patients had co-morbidity. Hypertension (HTN) was the most common underlying disease 71 (26.4%), followed by Diabetes Mellitus (DM) 55 (20.4%), cardiac disease, and Chronic Obstructive Pulmonary Disorder (COPD). The most common symptom was dyspnea 207 (77%), coughing and fever. The most common findings in the chest Computed Tomography (CT) scan of patients was ground-glass opacity with a frequency of 150 among 188 patients (79.8%) in patients with the abnormal CT scan. Multivariable regression indicated the increased odds of in hospital death associated with COPD (OR=3.20, 95% CI 1.02–10.04; p=0.046), arterial saturation of oxygen ≤93% (OR=5.70, 95% CL 2.42–13.40; p<0.001), and leukocytosis (OR=7.26, 95% CL, 3.02-17.49, p<0.001).
Conclusion: Based on the results of the present study, COPD, arterial saturation of oxygen (≤93%), and leukocytosis were risk factors for the hospital mortality of COVID-19. It might be proper for the initial determination of patients who may need life saving interventions.
Coronavirus disease 2019, Hospital mortality, Infectious diseases, Outcome
It has been more than a year since the beginning of COVID-19. This form of viral pneumonia caused by Severe Acute Respiratory Syndrome (SARS-CoV-2) was identified as a pandemic in March 2020 (1). It led to many infections and deaths around the world (2),(3),(4),(5),(5). Globally, since 27th December 2020, 79,232,555 confirmed cases of COVID-19 were observed involving 1,754,493 deaths which were reported to World Health Organisation (WHO); also, 54,693 deaths have occurred to that date because of coronavirus in Iran (5). The outbreak and mortality of COVID-19 in Iran become a considerable public health concern.
Since COVID-19 outbreak, many studies were performed on the clinical and epidemiological characteristics of COVID-19 disease (6),(7). Moreover, many risk factors were determined in terms of severe disease and death from the disease (8),(9). Symptoms of COVID-19 in the patients were different and it might be aymptomatic in nature and/or patients with mild symptoms to patients with bilateral pneumonia and failure in organs, and COVID-19 may result in death at its severe level (10),(11),(12). The symptoms first replicate a respiratory system disorder involving fever, sore throat, dyspnea, and cough. Over time, other symptoms like vomiting, abdominal pain, headache, diarrhoea, loss of taste and smell were added to the clinical features (13),(14),(15).
Moreover, Hypertension (HTN), being the foremost common disease worldwide, was predominant among the hospitalised COVID-19 patients over diverse countries, and a few meta-analysis researches have indicated a positive relationship between HTN and COVID-19 mortality (16),(17),(18),(19),(20),(21). The results of some researches revealed that diabetes increases COVID-19 severity. Furthermore, tabulated descriptive data show that the mortality rate was higher in the patients with previous diagnosis of diabetes (22),(23),(24). In meta-analysis studies, typical Computed Tomography (CT) imaging appearance for COVID-19 patient’s revealed ground-glass opacity (25),(26). Moreover, based on laboratory findings, high C-reactive Protein (CRP), declined albumin, and high Lactate Dehydrogenase (LDH), lymphopenia, and high Erythrocyte Sedimentation Rate (ESR), were reported as the most common laboratory results.
Furthermore, based on risk factors in various research, older age, underlying diseases like HTN, diabetes, cancer, cardiovascular disease are known as the risk factors for severe disease and mortality (27),(28),(29),(30),(31). Risk factors in COVID-19 disease were reported in three other similar viral infections like influenza Influenza Type A virus (H1N1), SARS, and Middle East Respiratory Syndrome (MERS) (32),(33).
To decrease the mortality in COVID-19 patients, it is vital to distinguish the clinical characteristics and risk factors related to this infection. The present study identified the clinical characteristics and risk factors for the mortality of adult patients with COVID-19 in Sirjan, Iran.
This retrospective cohort study includes all patients suspected of covid-19 who were admitted to Imam Reza and Dr. Gharazi hospitals in Sirjan / Iran between July 20, 2020 and October 22, 2020 and data was analysed in November 2020. The sampling method used was full census. In the study period, 380 suspected patients with COVID-19 who died or discharged were involved, but based on the inclusion and exclusion criteria, 269 patients were assessed. The hospitalisation of these patients was based on WHO protocol (26). The Ethical Research Committee approved this study at Sirjan University of Medical Sciences (IR.SIRUMS.REC.1399.005).
Inclusion criteria: The inclusion criteria were all COVID-19 patients with positive results on Real-Time-Polymerase Chain Reaction test (RT-PCR). A laboratory approved COVID-19 case was defined as a positive result on RT-PCR test for SARS-CoV-2 with presence in nasal and pharyngeal swab specimens.
Exclusion criteria: Patients with unapproved diagnosis,incomplete medical information in the medical records and discharges from hospital against medical advise were excluded from the study.
The checklist was a standardised data collection form, an adjusted adaptation of WHO/International Serious Intense Respiratory and Rising Disease Consortium case record form for extreme intense respiratory contaminations (3). It incorporates socio-economic and clinical characteristics, research facility discoveries, and imaging highlights. All clinical and research facility information, CT filters, therapeutic history, fundamental co-morbidities, treatment measures (antiviral treatment, corticosteroid treatment, oxygen treatment, mechanical ventilation) and results from the information of patients were enrolled for all patients. Information collection was done by two staff of the medical sciences faculty of Sirjan. Then, it was evaluated by an infectious disease specialist. Patients with incomplete data were excluded from the research. Underlying diseases were recorded based on medical reports and the patient's self-report.
Disease severity was defined based on these criteria as a moderate, severe, and critical illness: Diagnostic criteria for moderate cases involved fever, respiratory symptoms, and pneumonic changes on CT scan. Diagnostic criteria for serious cases were dyspnea with a Respiratory Rate (RR) ≥30 breaths/min, Oxygen Saturation (O2Sat) ≤ 93% at rest, and chest imaging with progression in the lesion of more than 50% within 24-48 hours. Moreover, there were symptomatic criteria for the basic cases of respiratory dyspnea with the requirement for mechanical ventilation, shock, and modified function of other organs which needed hospitalisation within Intensive Care Unit (ICU) (34). Fever was characterised as a temperature at the slightest 37.3°C. Furthermore, hypotension was characterised as blood weight less than 90 mm Hg (35). A Confusion, Uraemia, Respiratory rate, Blood pressure (CURB-65) score was calculated for all patients. CURB-65 scores range from 0 to 4. A score from 0 to 1 indicates a low risk of mortality, whereas a score of 2 or higher is related to higher mortality (36).
Data was entered into SPSS software version 19 (IBM statistics, New York, United States of America). Frequency (percentage) was utilised to explain the qualitative data. To analyse the data between two groups Chi-square or Fisher’s-exact test to assess the risk factors related to in hospital mortality of quiet univariate and multivariate calculated test were utilised. Regarding model overfitting, four variables were chosen due to past research and clinical limitations for univariate logistic tests. In all tests, a significant difference level was set as 0.05.
Demographics and clinical features of the sample are indicated in (Table/Fig 1). Thirty-nine patients (14.5%) died in the hospital, and 230 patients (85.5%) were discharged from the hospital. Near half of the patients were aged more than 50 years. Gender differences were not significant. Among all patients, 152 (56.5%) of patients had an underlying disease. HTN was the most common underlying disease, followed by DM cardiac disease, and COPD. The most common symptoms at the time of admission were dyspnea, coughing, fever, and then myalgia, fatigue, and headache, respectively. The most common finding in the chest CT scan of patients was ground-glass opacity with a frequency of 150 among 188 (79.8%) patients with abnormal CT scan and 22 from 31 (71%) among the patients who died. Twenty-nine (10.8%) patients had lymphocytopenia, and 72 (28.5%) had White Blood Cells (WBC) greater than 103/L. Out of 269 patients, 175 patients (64.9%) had moderate status, 42 (15.7%) had severe, and 52 patients (19.4%) had critical status. A totol of 170 (63.6%) patients had a CURB-65 score of 0 or 1.97 patients (36.3%) had a CURB-65 score of ≥2. All deaths had a CURB-65 score ≥2.
Association between Demographic and Clinical Characteristics and In Hospital Mortality: There was an association between age and mortality in the patients (p<0.001). Moreover, there was an association among the days of hospitalisation in the healing center and mortality in the patients (p=0.001). There was an association between COPD (p=0.001) and carcinoma (p<0.020) with hospital mortality.
Based on the symptoms, there was an association among the indications of hacking (p=0.025), myalgia (p=0.001), fatigue (p=0.002), loss of consciousness (p<0.001), and hospital mortality. There was an association among the RR more than 24 per minute (p<0.001), heart rate more than 125 per minute (p<0.001), O2Sat less than 93% (p<0.001), and blood pressure less than 90 mmHg with hospital mortality (p<0.001). There was an association among laboratory findings of leukocytosis (p<0.001), lymphocytopenia (p=0.001), and death in patients. There was an association between CURB-65 score and mortality in the patients (p <0.001).
Risk factors associated with in hospital mortality: Based on (Table/Fig 2), risk factors are related to in-hospital mortality. In univariable analysis, lymphopenia were associated with hospital mortality. The hospital mortality odds were also higher in the patients with COPD. Moreover, there was an association among the clinical symptom loss of consciousness with hospital mortality. The mortality was higher in the patients with a RR of more than 24 breaths per minute and O2 saturation less than 93%. In the multivariable logistic regression model, we found that COPD (OR=3.20, CI:1.02-10.04), O2Saturation less than 93%, and leukocytosis were associated with the increased odds of mortality.
Total 269 patient’s data were evaluated in this retrospective cohort study. Thirty-nine patients died, and the mortality rate was 14.5%. This rate is less than the meta-analysis study by Young L et al., (16.3%) but some studies showed rate more than this study (4.3%) (8),(9),(12),(15).
This retrospective cohort study identified several risk factors for death in the hospitalised COVID-19 patients in Sirjan. COPD, O2 saturation less than 93%, and leukocytosis were associated with the increased odds of the mortality of patients with COVID-19. WHO has determined COPD as the third leading reason of death in low and middle income countries (27). A meta-analysis also found that pre-existing COPD is a risk factor in predicting the adverse consequences in COVID-19 patients (28). Moreover, in a study by Nandy K et al., there was a considerable association between COPD and the occurrence of serious events in COVID-19 patients (29). In the study by Lippi G et al., the mortality rate of COPD patients with COVID-19 was over 60% (30). It is a considerable finding regarding the high prevalence of COPD worldwide. In clinical settings, necessary measures should be taken to advance patient assessment and management with COPD.
An increase in white blood cells was another risk factor that was identified. The results of a meta-analysis study by Yamada T et al., indicated that leukocytosis was associated with severe disease and leukocytosis at admission may predict severe COVID-19 and poor outcomes in these patients (31). Furthermore, in the study of Huang C et al., leukocytosis was determined as one of the risk factors for mortality in the patients with COVID-19 (13).
More than half of the patients had an underlying disease. The results were greater than the findings of another study (32). Based on recent systematic reviews, co-morbidities prevalence in COVID-19 patients was high, and these co-morbidities were associated with increased disease severity (33). In similar studies, HTN was the most prevalent disease (33),(34),(35),(36),(37),(38). There was no association between HTN and mortality in this study. While some research noted that HTN should be considered an independent risk factor for COVID-19 severity, this tip should be considered the high prevalence of HTN in critical patients with COVID-19 may be due to older individuals vulnerability to the infection of SARS-COV-2 which is affected by HTN. There is no epidemiologic evidence to indicate HTN as an independent risk factor to increase intense disease in the patients with COVID-19. Similar to this study, the study by Shibata S also reported that HTN does not constitute as a risk factor for COVID-19 (39).
In a similar research, 20% of all patients had DM, and this condition is determined after HTN as the most prevalent underlying disease (13),(40). Another research found that diabetes was associated with mortality, severity, and acute respiratory distress syndrome in COVID-19 (41). Despite being determined as the second most common underlying disease there was no association between DM and mortality in the patients with COVID-19 in the index research; and it contradicts the results of the meta-analyses that found DM is considerably associated with the mortality in COVID-19 patients (41),(42),(43). Despite this, it is recommended that patients with DM should manage their blood sugar to decrease the risk of infection.
Similar to the present research, cancer was considerably associated with mortality in other studies (27),(44). COVID-19 infected cancer patients encounter with the risk of mechanical ventilation or ICU hospitalisation 3.5 times more than the general population (45).
As in other similar studies, the most prevalent symptoms of disease in the patients were dyspnea followed by coughing, fever, myalgia, and fatigue (13),(33),(38),(46). In addition to common respiratory symptoms, the symptoms of chest pain, headache, diarrhoea, nausea, dizziness, and vomiting were also obvious in some patients. In addition to considering respiratory symptoms in patients, non respiratory symptoms should also be regarded. Other studies showed an association among the symptoms of coughing, myalgia, fatigue, loss of consciousness, and hospital mortality (1),(47),(48). In the present research, 47.2% of all patients and 51.3% of patients with mortality had fever. Fever isn’t a significant clinical symptom to COVID-19 from January 25th, 2020 (49). Similar to this research, the prevalence of ground-glass opacity in chest CT scan was higher than of the other signs of bilateral pulmonary infiltration and consolidation (33),(50). Moreover, these results were consistent with the results of meta-analysis studies by Bao C et al., and Kim H et al., (16),(51).
The mortality rate was greater in the elderly (over 70 years old). Hence, age is determined as a considerable risk factor in COVID-19 patient mortality. In fact, older age is associated with failure in different organs, which exacerbates the risk of being infected (50). More prevalence of cardiovascular diseases, HTN, and DM in older adults is related to decrease immune defense against infections (35),(40),(47). In a meta-analysis study by Starke KR et al., there was a 2.7% increased risk per age year for disease severity. The author also noted that age related diseases are more significant than age itself, and when taking preventive measures, after adjusting for age related factors, the mild impact of age on the severity of disease must be considered (52).
Furthermore, lymphopenia was observed at 38.5% in patients who died, which was significantly higher than patients who were discharged. An important association was observed between lymphocyte counts and mortality. In the research by Zhao Q et al., lymphocyte counts in COVID-19 patients were considerably lower, and in patients with lymphopenia, the risk of developing severe COVID-19 was almost tripled (53).
Inconsistent with the results by Rodriguez-Morales AJ et al., an increase in CRP in the patients was not a considerable finding in laboratory results of COVID-19 patients (33). An increase in CTnI was seen in 20.5% of patients with mortality in the index study. Cardiovascular complications due to COVID-19 have been related to cardiac failure, arrhythmia, cardiac shock, acute myocardial infarction, and myocarditis (54),(55),(56).
In this study, total 23% of all patients, 25.6% of patients with mortality, and 22.6% of discharged patients had a positive history of smoking. Another study found no considerable association between smoking and mortality (32). Nepogodiev D et al., concluded that smoking is not a risk factor for protective factor patients with COVID-19 (47). Smoking is most prevalent among young people and they usually do not have underlying diseases, the lack of an association between smoking and mortality in patients may thus be justified.
Besides, the mortality rate in men was higher than in women; similar to another systemic review (57). The reason for in the higher mortality in men may be due to behaviors which are more common in men. Men are more likely than women to engage in risky behaviors and roles, which are more likely to be present in crowded communities and environments, increasing their risk of infection and death (57). Besides, females have the stronger innate and acquired immunity against viral infections compared to males, which is one reason for less mortality rate in females (58).
First, this research was handled as a single center form, and multicenter studies are proposed. Another limitation of the research is that it was retrospective. Moreover, incomplete laboratory data in the present research must be related to retrospective analysis nature, and also some laboratory tests were not handled for patients due to resource constraints. For a limited number of mortality patients due to death in the first hours of hospitalisation in the hospital, some considerable data were not exactly recorded.
The clinical characteristics of COVID-19 patients were assessed, and also the risk factors associated with its mortality were provided. There was an association between cancer, COPD, cough and shortness of breath with hospital mortality. It was found that COPD, O2 saturation less than 93%, and leukocytosis were risk factors for in hospital mortality in patients with COVID-19. These results manage the COVID-19 disease and controlling risk factors associated with mortality from the disease.
Date of Submission: Apr 12, 2021
Date of Peer Review: May 13, 2021
Date of Acceptance: Dec 23, 2021
Date of Publishing: May 01, 2022
• Financial or Other Competing Interests: None
• Was Ethics Committee Approval obtained for this study? Yes
• Was informed consent obtained from the subjects involved in the study? Yes
• For any images presented appropriate consent has been obtained from the subjects. NA
PLAGIARISM CHECKING METHODS:
• Plagiarism X-checker: Apr 14, 2021
• Manual Googling: Sep 02, 2021
• iThenticate Software: Mar 09, 2022 (10%)
ETYMOLOGY: Author Origin
- Emerging Sources Citation Index (Web of Science, thomsonreuters)
- Index Copernicus ICV 2017: 134.54
- Academic Search Complete Database
- Directory of Open Access Journals (DOAJ)
- Google Scholar
- HINARI Access to Research in Health Programme
- Indian Science Abstracts (ISA)
- Journal seek Database
- Popline (reproductive health literature)