We conducted the present multicenter, retrospective study to assess the epidemiological, clinical, laboratory, and radiological characteristics associated with critical illness among patients with COVID-19 from Egypt.
The present study was a multicenter, retrospective study that retrieved the data of all Egyptian cases with confirmed COVID-19 admitted to hospitals affiliated to the General Organization for Teaching Hospitals and Institutes (GOTHI) through the period from March to July 2020. The diagnosis of COVID-19 was based on a positive reverse transcription-polymerase chain reaction (RT-PCR) laboratory test.
This retrospective study included 2724 COVID-19 patients, of whom 423 (15.52%) were critically ill. Approximately 45.86% of the critical group aged above 60 years, compared to 39.59% in the non-critical group (p = 0.016). Multivariate analysis showed that many factors were predictors of critically illness, including age >60 years (OR = 1.30, 95% CI [1.05, 1.61], p = 0.014), low oxygen saturation (OR = 0.93, 95% CI [0.91, 0.95], p<0.001), low Glasgow coma scale (OR = 0.75, 95% CI [0.67, 0.84], p<0.001), diabetes (OR = 1.62, 95% CI [1.26, 2.08], p<0.001), cancer (OR = 2.47, 95% CI [1.41, 4.35], p = 0.002), and serum ferritin (OR = 1.004, 95% CI [1.0003, 1.008], p = 0.031).
In the present report, we demonstrated that many factors are associated with COVID-19 critical illness, including older age groups, fatigue, elevated temperature, increased pulse, lower oxygen saturation, the preexistence of diabetes, malignancies, cardiovascular disease, renal diseases, and pulmonary disease. Moreover, elevated serum levels of ALT, AST, and ferritin are associated with worse outcomes. Further studies are required to identify independent predictors of mortality for patients with COVID-19.
Citation: Omran D, Al Soda M, Bahbah E, Esmat G, Shousha H, Elgebaly A, et al. (2021) Predictors of severity and development of critical illness of Egyptian COVID-19 patients: A multicenter study. PLoS ONE 16(9): e0256203. https://doi.org/10.1371/journal.pone.0256203
Editor: Andreas Zirlik, Medizinische Universitat Graz, AUSTRIA
Received: January 1, 2021; Accepted: May 3, 2021; Published: September 23, 2021
Copyright: © 2021 Omran et al. This is an open access article distributed under the terms of the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original author and source are credited.
Data Availability: The data underlying the results presented in the study are available from the database of the Egyptian general organization of teaching hospitals and institutes (GOTHI) but cannot be shared publicly due to local restrictions. Interested researchers may contact Dr. Ahmed Abdel Salam (email@example.com; +201551475160) or the corresponding author, Dr. Dalia Omran.
Funding: This research work received no fund.
Competing interests: All authors declare no conflict or competing interest.
Since the discovery of the initial cluster of cases in Wuhan, China, the coronavirus disease 2019 (COVID-19) outbreak has emerged as one the greatest health threat and was declared as a pandemic by the World Health Organization (WHO) on March 11, 2020 [1, 2]. By the end of October 2020, the COVID-19 outbreak has affected more than 200 countries in various regions of the world; according to the WHO situation reports, the number of COVID-19 confirmed cases reached more than 41,571,000 cases and 1,135,000 related deaths worldwide . In the past few months, the COVID-19 pandemic landscape has changed with a dramatic shift in the apex of the number of confirmed cases from China to the United States (US), Europe, and Eastern Mediterranean Region (EMR) [4, 5]. In the EMR, the number of confirmed cases is approaching three million cases by October 2020, with a fatality rate of 2.6% . While the causative agents and mode of transmission remained ambiguous during the early day of outbreaks, it is now clear that COVID-19 is a highly contagious disease that is caused by Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2), which is transmitted mainly by respiratory droplets [7, 8]. Besides, the current body of evidence demonstrates that the infection can be transmitted by both symptomatic and asymptomatic cases leading to the dramatic spread of the outbreak within the community .
The presentation and outcomes of COVID-19 vary substantially, with clinical features ranging from asymptomatic/mild symptoms to fatal respiratory distress and multi-organ failure [10, 11]. Previous reports demonstrated that symptomatic patients usually present with flu-like symptoms that resolve completely by the end of the disease course ; nonetheless, a subset of the patients can present with severe forms of the disease, including severe pneumonia, acute respiratory distress syndrome (ARDS), sepsis, thromboembolic manifestations, acute myopericarditis, septic shock, multi-organ failure, and eventually death [13–16]. While the exact pathogenic mechanisms underlying the development of severe forms have not been fully elucidated yet, recent experiments highlighted that patients with severe COVID-19 exhibit exaggerated inflammatory process and release of inflammatory cytokines, which in rerun induce a cytokine storm and organ damage .
Recent studies confirmed that the COVID-19 outbreak does not exert an equal toll amongst the different regions affected, with wide variation in the proportion of patients with severe disease and mortality . While the adequacy of healthcare services may play a role in such inconsistencies , multicenter reports highlighted that patient-specific factors are major determinants of the presentation and outcomes of COVID-19. Old age, male gender, comorbidities, and immunocompromised status were reported to be associated with severe presentation and poor disease outcomes [20, 21]; besides, predisposing genetic factors may play a role in determining an individual’s susceptibility to infection and disease course as well [22, 23].
Being a frequent destination of tourism, international traffic and a densely populated country, Egypt observed an increasing spread of COVID-19 since March 5; the official figures demonstrated the number of confirmed cases was nearly 108,000 by the end of October 2020 with a fatality rate of 5.8% . Besides, the mortality rate among hospitalized patients with COVID-19 in Egypt was reported to be 6.7% , which rises to 40% in severe and critically-ill cases . Such a fatality rate is notably higher than in other countries in the EMR, which can be attributed to the potential role of patient-specific characteristics. Thus, we conducted the present retrospective study to assess the epidemiological, clinical, laboratory, and radiological characteristics associated with critical illness development among patients with COVID-19 from Egypt.
2. Materials and methods
The present study was initiated after obtaining the protocol approval from the General Organization for Teaching Hospitals and Institutes (GOTHI) responsible ethics committees in Egypt (IRB:HAM00122). The preparation of the present manuscript runs in compliance with the recommendations of the STROBE statement .
2.1. Study design and population
The present study was a multicenter, retrospective study that retrieved the data of all Egyptian cases with confirmed COVID-19 admitted to hospitals affiliated to the GOTHI through the period from March to July 2020 The diagnosis of COVID-19 was based on a positive reverse transcription-polymerase chain reaction (RT-PCR) laboratory test.
2.2. Data collection and operational definitions
We retrieved epidemiological, clinical, laboratory, and radiological data of all eligible patients. The epidemiological characteristics included age, gender, and smoking, while the clinical data included the COVID-19 symptoms and the associated comorbidities. The laboratory and radiological data included complete blood count (CBC) with differential count, C-reactive protein (CRP), serum ferritin, liver function tests, renal function tests, coagulation profile, D-Dimer level, arterial blood gas analysis, and chest imaging. The data were collected at the first day of hospitalization of each patient.
According to Chinese guidelines for the management of COVID-19; Severe COVID-19 was defined as the presence of radiological evidence of more than 50% lung infiltrate plus one of the following: respiratory rate of ≥ 30 breaths per minute; oxygen saturation (SaO2) <94% while breathing ambient air at rest; or ARDS that is defined as arterial oxygen partial pressure (PaO2) to a fraction of inspired oxygen (FiO2) (PaO2: FiO2) of ≤300 mmHg. In addition, critical COVID-19 was defined as respiratory failure requiring ventilator support either invasive or none, septic shock, and/or any organ dysfunction that needs supportive treatment in ICU .
2.3. Statistical analysis
Data were analyzed using the software Stata 16 for Windows. Categorical variables were summarized by frequency counts and percentages. Continuous variables were represented as means and standard deviations. Comparison between moderate and severe cases to critically-ill cases was done through univariate analysis as follows: categorical variables were assessed with the Chi-square test, whereas continuous variables were assessed using the Mann-Whitney test. Multivariate analysis was also done to determine factors associated with patients’ deterioration. The odds ratio (OR) was calculated by using stepwise logistic regression modeling. Accordingly, the regression equation was used to calculate predicted probabilities of patients’ deterioration. Multivariate regression was validated using the Hosmer-Lemeshow goodness-of-fit test.
3.1. Demographic characteristics
This retrospective study included 2724 COVID-19 patients, of whom 423 (15.52%) were critically ill. Approximately 45.86% of the critical group aged above 60 years, compared to 39.59% in the non-critical group (p = 0.016). There was no significant difference between both groups in terms of gender (p = 0.655) and smoking (p = 0.218), Table 1.
3.2. COVID-19 symptoms
Regarding the history of contact with infected persons, 25.06% of the critical group’s patients had a contact history, compared to 18.47% in the non-critical group (p = 0.002). Our analysis demonstrated no significant difference between both groups in regards to the presence of fever (p = 0.163), cough (p = 0.212), dyspnea (p = 0.390), sore throat (p = 0.283), hemoptysis (p = 0.055), headache (p = 0.298), diarrhea (p = 0.171), nausea (p = 0.703), vomiting (p = 0.646), abdominal pain (p = 0.972), loss of taste (p = 0.151), and loss of smell (p = 0.239). On the other hand, prevalence of fatigue (32.15% vs. 23.73%, p<0.001), anorexia (5.44% vs. 2.96%, p = 0.009), arthralgia (13.71% vs. 6.48%, p<0.001), and myalgia (16.31% vs. 8.52%, p<0.001) was significantly higher in the critical group compared with non-critical group, respectively (Table 1).
Patients with critical illness were associated with higher prevalence of diabetes (39.72% vs. 27.86%, p<0.001), cancer (4.49% vs. 1.91%, p = 0.001), hypertension (33.57% vs. 27.03%, p = 0.006), coronary artery diseases (12.53% vs. 6.95%, p<0.001), chronic renal insufficiency (7.09 vs. 2.74%, p<0.001), and asthma (1.42% vs. 0.78%, p = 0.006), Table 1.
3.4. CT findings
Interestingly, there was no significant difference (p = 0.566) between critical and non-critical groups in terms of CT findings, including consolidation (3.07% vs. 2.39%), Crazy paving (1.18% vs. 1%), and Ground Glass Opacity (39.95% vs. 44.89%), Table 1.
3.5. Vital signs and O2 saturation
There was no significant difference between both groups in terms of systolic and diastolic blood pressure (p = 0.762 and p = 0.577, respectively). On the other hand, the mean value of the pulse (p = 0.006), temperature (p<0.001), and respiratory rate (p<0.001) was higher in critically ill patients compared to the non-critical group. Moreover, the FiO2 was significantly (p = 0.004) higher in the critical group (35.5±33.91) compared to the non-critical group (20.71±28.08). In terms of oxygen saturation, critically ill patients were associated with lower O2 saturation (85.73±10.6 vs. 91.04±6.23, p<0.001) and partial pressure of O2 (64.43±26.09 vs 55.22±25.04, p<0.001). The Glasgow coma scale was significantly (p<0.001) lower in the critical group (14.10±2.33) than the non-critical group (14.80±0.78), Table 2.
3.6. Laboratory investigations
Critically ill patients were associated with higher serum levels of CRP (p<0.001), Serum ferritin (p = 0.003), TLC (p<0.001), INR (p<0.001), serum potassium (p = 0.023), HCO3 (p = 0.029), and Moreover, total bilirubin (p<0.001), direct bilirubin (p<0.001), serum albumin (p = 0.001), ALT (p = 0.008), AST (p<0.001), and serum creatinine (p = 0.007) were higher in critically ill patients, Table 2.
3.7. Univariate logistic regression
Our analysis demonstrated a significant association between many variables and critical illness. In terms of demographic variables age >60 years and history of contact were observed to increase the risk of critically illness (OR = 1.29, 95% CI [1.04, 1.59], p = 0.016) and (OR = 1.47, 95% CI [1.15, 1.88], p = 0.002), respectively. Regarding the COVID-19 symptoms, critically illness was significantly associated with hemoptysis (OR = 3.65, 95% CI [1.02, 12.99], p = 0.046), fatigue (OR = 1.52, 95% CI [1.21, 1.91], p<0.001), anorexia (OR = 1.88, 95% CI [1.16, 3.06], p = 0.010), arthralgia (OR = 2.29, 95% CI [1.66, 3.17], p<0.001), and myalgia (OR = 2.09, 95% CI [1.55, 2.82], p<0.001). In terms of co-morbidities, patients with diabetes (OR = 1.71, 95% CI [1.38, 2.12], p<0.001), cancer (OR = 2.41, 95% CI [1.39, 4.17], p = 0.002), hypertension (OR = 1.36, 95% CI [1.09, 1.70], p = 0.006), and coronary artery diseases (OR = 1.91, 95% CI [1.37, 2.66], p<0.001) were associated with higher risk of critical illness, Table 3.
3.8. Predictors of critical illness
Multivariate analysis was performed based on four models; 1) demographic and clinical symptoms; 2) vital signs; 3) Co-morbidities; and 4) laboratory investigations. Model 1 showed that age >60 years (OR = 1.30, 95% CI [1.05, 1.61], p = 0.014), fatigue (OR = 1.30, 95% CI [1.02, 1.65], p = 0.029), arthralgia (OR = 1.75, 95% CI [1.20, 2.54], p = 0.003), and myalgia (OR = 1.51, 95% CI [1.08, 2.11], p = 0.015) can be considered as independent predictors for COVID-19 critical illness. Model 2 demonstrated that high pulse (OR = 1.01, 95% CI [1.009, 1.03], p<0.001), temperature (OR = 1.25, 95% CI [1.04, 1.48], p = 0.012), low oxygen saturation (OR = 0.93, 95% CI [0.91, 0.95], p<0.001), and low Glasgow coma scale (OR = 0.75, 95% CI [0.67, 0.84], p<0.001) are significant predictors for COVID-19 critical illness. According to model 3, critical COVID-19 can be predicted based on the presence of the following co-morbidities: Diabetes (OR = 1.62, 95% CI [1.26, 2.08], p<0.001), cancer (OR = 2.47, 95% CI [1.41, 4.35], p = 0.002), coronary artery diseases (OR = 1.56, 95% CI [1.09, 2.22], p = 0.014), and chronic renal insufficiency (OR = 2.81, 95% CI [1.79, 4.43], p<0.001). Regarding model 4, only ALT (OR = 1.12, 95% CI [1.0092, 1.24], p = 0.033), AST (OR = 1.13, 95% CI [1.00, 1.28], p = 0.036), and Serum ferritin (OR = 1.004, 95% CI [1.0003, 1.008], p = 0.031) can be used as predictors for COVID-19 critical illness, Table 4.
3.9. Gender disparity amongst the studied population
Male patients were more likely to be smokers (p <0.001), had a history of close contact with positive cases (p = 0.043), being asymptomatic (p = 0.043), S1 Table.
The landscape of the COVID-19 pandemic has changed over the past few months. The number of confirmed cases in the EMR rose sharply to more than 1,534,000 cases by the end of July 2020, with about 40,000 deaths reported, resulting in a 2.6% mortality rate . Growing evidence shows that the different distributions of epidemiological characteristics between the affected countries may influence mortality rates. In addition, the clinical spectrum of COVID-19 disease appears to be broad, ranging from asymptomatic infection, mild upper respiratory tract disease, respiratory failure to severe viral pneumonia or death. The assessment of risk factors and predictors of the severity of the disease and the possibility of death is a very important issue for the prediction of the possible outcome.
In this study, we highlighted many risk factors that can be used as independent predictors for the severity of COVID-19. Age, especially patients older than 60 years, were significantly associated with worse outcomes of COVID-19. It has been observed that older age groups are more susceptible to infection and severe presentation, with higher mortality rates than younger patients, since the initial COVID-19 case clusters were reported . While it was initially unclear whether the difference between age groups reflects the lower risk of severe disease or lower susceptibility to infection, recent reports demonstrated that the young population had similar susceptibility to older age groups; which, in return, highlights that the difference between age groups stems from the ability to fight the infection . Several studies proposed many pathogenic mechanisms behind the critical illness in the elderly population, including low levels of angiotensin-converting enzyme 2 (ACE2) in the elderly , age-dependent difficulty in removing particles from small airways , excessive release of inflammatory mediators in elderly “inflammaging” , incompetent immune response, and high frequency of comorbidities in the elderly population . Recent retrospective studies from Egypt , Iran , and Pakistan  demonstrated that older age groups were more susceptible to severe disease and death from COVID-19. This was in line with other reports from outside of EMR countries [36, 37].
Recent surveillance had shown that male patients were more susceptible to serious infection and mortality with COVID-19 , and this gender-specific difference had been observed in previous outbreaks of SARS . In contrast, our study showed an insignificant difference between both genders in terms of COVID-19 severity. This observation was different from what was reported in the other reports from EMR countries [25, 34, 35]. This can be explained as we here investigate the risk of severity, not mortality. Similarly, Nasiri et al. showed that there was no significant difference between males and females in terms of ICU admissions . Another Egyptian study of 260 patients with COVID-19 showed that there was no significant association between male gender and the risk of critical illness (OR = 1.84, 95% CI [0.80, 4.48], p = 0.156) . In Italy, Ciceri et al.  reported that there was no significant association between female gender and risk of critical illness (OR = 1.09, 95% CI [0.69, 1.72], p = 0.70).
It is well documented that comorbidities in COVID-19 patients are major contributors to serious presentation and death. For example, poorly controlled diabetes was found to significantly increase the risk of composite adverse outcomes, including death, among COVID-19 cases . Likewise, malignancies and chronic renal diseases were reported to be significant predictors of COVID-19 critical illness and mortality . The preexistence of cardiovascular or chronic lung diseases worsens the outcomes of COVID-19 as well [45, 46]. In our study, diabetes mellitus, cardiovascular diseases, chronic renal disease, and cancer were significantly associated with a higher risk of critical illness. In a large cohort from China, hypertension, diabetes, and chronic obstructive pulmonary diseases were prevalent among severe COVID-19 cases . Patients with preexistent comorbidities, such as diabetes and cardiovascular diseases, were more likely to suffer from the severe disease in another report of COVID-19 cases .
Low Oxygen saturation is one of the most important clinical features of COVID-19 patients. Our study showed that lower oxygens saturation was significantly associated with an increased risk of critical illness. In agreement, Petrilli et al.  showed that patients with deficient oxygen saturation (less than <88%) were associated with increased risk of critical COVID-19 (OR = 3.67, 95% CI [2.78, 4.8], p<0.001). Also, we found that patients with elevated temperature and increased pulsation were associated with an increased risk of critical illness. In contrast, Petrilli et al. could not find any significant association between elevated temperature and critical illness .
In our study, the critically ill patients showed significant leukocytosis. Similarly Zhao et al found that elderly patients with co-morbidities showed significant leukocytosis . Patients with COVID-19 have a blood picture characterized by normal or low WBC count and decreased lymphocyte level . Similarly, the elevation of CRP levels was observed in the majority of COVID-19 patients. Moreover, high levels of CRP and inflammatory biomarkers are considered one of the main characteristics of COVID-19 patients . It was reported that early elevation of CRP has the strongest association with mechanical ventilation or mortality . Furthermore, liver changes were one of the most common findings in the COVID-19 infected subjects. Liver injury may happen in COVID-19. It had been reported that that 14.8–53.1% of COVID-19 patients had elevated liver enzymes and bilirubin. Moreover, the degree of liver damage is proportional to the severity of COVID-19 [53, 54]. In patients with COVID-19, the serum level of ferritin was significantly elevated in critically ill patients. Similarly, it had been reported that serum level of ferritin increase with case deterioration and was significantly elevated in non-survivors compared with survivors . Shoenfeld reported that the ferritin H-chain played a role in stimulating macrophages to increase inflammatory cytokine secretion. Thus, it became apparent to understand the pathogenesis of hyperferritinemia syndrome, including COVID-19 infection . Our findings showed that ALT, AST, and serum ferritin could be used as a significant predictor for COVID-19 severity. Interestingly, our findings demonstrated that there was no significant association between the level of D-dimer and the severity of COVID-19. This finding was also observed by Ramadan et al. in another Egyptian study .
This article is one of the first reports about the predictors of COVID-19 severity in Egypt. However, we acknowledge that the present study had some limitations. First, data of the present study were collected retrospectively with some potential biases, such as case ascertainment bias and misclassification. Second, we might have overestimated the importance of chronic disease at risk of hospital admission due to the substantial heterogeneity among the included patients. Third, our patients were from a single geographical area, treated within a single health system; so factors correlated with poor outcomes might differ elsewhere. The lack of medical history at baseline was an additional limitation, recent reports highlighted that some medications, such as angiotensin-converting enzyme (ACE) inhibitors and angiotensin II receptor blockers (ARBs), may facilitate severe infection . Besides, a high frequency of obesity among patients admitted with sever COVID-19 ; however, there were no available data concerning obesity in the present study.
In conclusion, COVID-19 is a growing pandemic with an unprecedented spread rate and profound impact on the health of specific subsets of affected patients. In the present report, we demonstrated that many factors are associated with COVID-19 critical illness, including older age groups, fatigue, elevated temperature, increased pulse, lower oxygen saturation, the preexistence of diabetes, malignancies, cardiovascular disease, renal diseases, and pulmonary disease. Moreover, elevated serum levels of ALT, AST, and ferritin are associated with worse outcomes. Further studies are required to identify independent predictors of mortality for patients with COVID-19.
- 1. (WHO) WHO. Rolling updates on coronavirus disease (COVID-19).
- 2. Mahalmani VM, Mahendru D, Semwal A, Kaur S, Kaur H, Sarma P, et al. COVID-19 pandemic: A review based on current evidence. Indian Journal of Pharmacology. Wolters Kluwer Medknow Publications; 2020. pp. 117–129. pmid:32565599
- 3. World Health Organization. Weekly Operational Update on COVID-19 October 23, 2020. WHO. 2020. Available: https://www.who.int/publications/m/item/weekly-update-on-covid-19—23-october
- 4. Ahmed H, Sayed A, Munir M, Elberry MH, Sayed IM, Kamal MA, et al. A Clinical Review of COVID-19; Pathogenesis, Diagnosis, and Management. Curr Pharm Des. 2020;26. pmid:33355050
- 5. Ebada MA, Allah AW, Bahbah E, Negida A. An Updated Review on COVID-19. Infect Disord Drug Targets. 2020. pmid:33327924
- 6. World Health Organization (WHO). Coronavirus disease 2019 Situation Report 193. World Heal Organ. 2020. Available: https://www.who.int/docs/default-source/coronaviruse/situation-reports/20200731-covid-19-sitrep-193.pdf?sfvrsn=42a0221d_4
- 7. Ji W, Wang W, Zhao X, Zai J, Li X. Cross-species transmission of the newly identified coronavirus 2019-nCoV. J Med Virol. 2020;92: 433–440. pmid:31967321
- 8. Jayaweera M, Perera H, Gunawardana B, Manatunge J. Transmission of COVID-19 virus by droplets and aerosols: A critical review on the unresolved dichotomy. Environmental Research. 2020. pmid:32569870
- 9. Rothe C, Schunk M, Sothmann P, Bretzel G, Froeschl G, Wallrauch C, et al. Transmission of 2019-NCOV infection from an asymptomatic contact in Germany. New England Journal of Medicine. 2020. pp. 970–971. pmid:32003551
- 10. Symptoms of Coronavirus | CDC.
- 11. Hui DS, I Azhar E, Madani TA, Ntoumi F, Kock R, Dar O, et al. The continuing 2019-nCoV epidemic threat of novel coronaviruses to global health—The latest 2019 novel coronavirus outbreak in Wuhan, China. International Journal of Infectious Diseases. Elsevier B.V.; 2020. pp. 264–266. pmid:31953166
- 12. Chen N, Zhou M, Dong X, Qu J, Gong F, Han Y, et al. Epidemiological and clinical characteristics of 99 cases of 2019 novel coronavirus pneumonia in Wuhan, China: a descriptive study. Lancet. 2020;395: 507–513. pmid:32007143
- 13. 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. Lancet. 2020;395: 497–506. pmid:31986264
- 14. Coperchini F, Chiovato L, Croce L, Magri F, Rotondi M. The cytokine storm in COVID-19: An overview of the involvement of the chemokine/chemokine-receptor system. Cytokine and Growth Factor Reviews. Elsevier Ltd; 2020. pp. 25–32. pmid:32446778
- 15. Zhang C, Wu Z, Li JW, Zhao H, Wang GQ. Cytokine release syndrome in severe COVID-19: interleukin-6 receptor antagonist tocilizumab may be the key to reduce mortality. Int J Antimicrob Agents. 2020;55. pmid:32234467
- 16. Inciardi RM, Lupi L, Zaccone G, Italia L, Raffo M, Tomasoni D, et al. Cardiac Involvement in a Patient With Coronavirus Disease 2019 (COVID-19). JAMA Cardiol. 2020 [cited 31 Mar 2020]. pmid:32219357
- 17. Xie P, Ma W, Tang H, Liu D. Severe COVID-19: A Review of Recent Progress With a Look Toward the Future. Frontiers in Public Health. 2020. pmid:32574292
- 18. European Centre for Disease Prevention and Control. Situation update worldwide, as of 6 March 2020 08:00. 2020.
- 19. Lipsitch M, Donnelly CA, Fraser C, Blake IM, Cori A, Dorigatti I, et al. Potential biases in estimating absolute and relative case-fatality risks during outbreaks. PLoS Neglected Tropical Diseases. Public Library of Science; 2015. pp. 1–16. pmid:26181387
- 20. Guan W-J, Ni Z-Y, Hu Y, Liang W-H, Ou C-Q, He J-X, et al. Clinical Characteristics of Coronavirus Disease 2019 in China. N Engl J Med. 2020; 1–13. pmid:32109013
- 21. Verity R, Okell LC, Dorigatti I, Winskill P, Whittaker C, Imai N, et al. Estimates of the severity of coronavirus disease 2019: a model-based analysis. Lancet Infect Dis. 2020;3099: 1–9. pmid:32240634
- 22. Cao Y, Li L, Feng Z, Wan S, Huang P, Sun X, et al. Comparative genetic analysis of the novel coronavirus (2019-nCoV/SARS-CoV-2) receptor ACE2 in different populations. Cell Discov. 2020;6: 4–7. pmid:32025334
- 23. Chen Y, Shan K, Qian W. Asians do not exhibit elevated expression or unique genetic polymorphisms for ACE2, the cell-entry receptor of SARS-CoV-2. 2020; 1–13.
- 24. Egypt Cares. [cited 4 Nov 2020]. Available: https://www.care.gov.eg/EgyptCare/Index.aspx
- 25. Ghweil AA, Hassan MH, Mohamed AK, Mohamed AO, Mohammed HM, Abdelazez AA, et al. Characteristics, Outcomes and Indicators of Severity for COVID-19 Among Sample of ESNA Quarantine Hospital’s Patients, Egypt: A Retrospective Study. Infect Drug Resist. 2020;Volume 13: 2375–2383. pmid:32765012
- 26. Ramadan HKA, Mahmoud MA, Zakaria M, Aburahma, Elkhawaga AA, El-Mokhtar MA, et al. Predictors of severity and co-infection resistance profile in COVID-19 patients: First report from upper Egypt. Infect Drug Resist. 2020;13: 3409–3422. pmid:33116660
- 27. Elm E Von Altman DG, Egger M Pocock SJ, Gøtzsche PC Vandenbroucke JP, et al. The Strengthening the Reporting of Observational Studies in Epidemiology (STROBE) Statement: Guidelines for reporting observational studies *. Int J Surg. 2014;12: 1495–1499. pmid:25046131
- 28. Lin L, Li TS. Interpretation of “Guidelines for the Diagnosis and Treatment of Novel Coronavirus (2019-nCoV) Infection by the National Health Commission (Trial Version 5).” Zhonghua Yi Xue Za Zhi. 2020;100: E001. pmid:32033513
- 29. Perrotta F, Corbi G, Mazzeo G, Boccia M, Aronne L, D’Agnano V, et al. COVID-19 and the elderly: insights into pathogenesis and clinical decision-making. Aging Clinical and Experimental Research. Springer; 2020. p. 1. pmid:31721096
- 30. Bi Q, Wu Y, Mei S, Ye C, Zou X, Zhang Z, et al. Epidemiology and Transmission of COVID-19 in Shenzhen China: Analysis of 391 cases and 1,286 of their close contacts. medRxiv. 2020; 2020.03.03.20028423.
- 31. Alghatrif M, Cingolani O, Lakatta EG. The Dilemma of Coronavirus Disease 2019, Aging, and Cardiovascular Disease: Insights from Cardiovascular Aging Science. JAMA Cardiology. 2020. pmid:32242886
- 32. Svartengren M, Falk R, Philipson K. Long-term clearance from small airways decreases with age. Eur Respir J. 2005;26: 609–615. pmid:16204590
- 33. Aw D, Silva AB, Palmer DB. Immunosenescence: Emerging challenges for an ageing population. Immunology. Wiley-Blackwell; 2007. pp. 435–446. pmid:17313487
- 34. Jalili M, Payandemehr P, Saghaei A, Sari HN, Safikhani H, Kolivand P. Characteristics and Mortality of Hospitalized Patients With COVID-19 in Iran: A National Retrospective Cohort Study. Ann Intern Med. 2020 [cited 4 Aug 2020]. pmid:32687717
- 35. Chaudhry A, Ikram A, Baig MA, Salman M, Ghafoor T, Hussain Z, et al. Mortality Analysis of COVID-19 Confirmed cases in Pakistan. medRxiv. 2020; 2020.06.07.20121939.
- 36. Petrilli CM, Jones SA, Yang J, Rajagopalan H, O’Donnell L, Chernyak Y, 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. pmid:32444366
- 37. Zhou F, Yu T, Du R, Fan G, Liu Y, Liu Z, et al. Clinical course and risk factors for mortality of adult inpatients with COVID-19 in Wuhan, China: a retrospective cohort study. Lancet. 2020;395: 1054–1062. pmid:32171076
- 38. Aly MH, Rahman SS, Ahmed WA, Alghamedi MH, Al Shehri AA, Alkalkami AM, et al. Indicators of Critical Illness and Predictors of Mortality in COVID-19 Patients. Infect Drug Resist. 2020;Volume 13: 1995–2000. pmid:32617010
- 39. Karlberg J, Chong DSY, Lai WYY. Do Men Have a Higher Case Fatality Rate of Severe Acute Respiratory Syndrome than Women Do? Am J Epidemiol. 2004;159: 229–231. pmid:14742282
- 40. Nasiri MJ, Haddadi S, Tahvildari A, Farsi Y, Arbabi M, Hasanzadeh S, et al. COVID-19 Clinical Characteristics, and Sex-Specific Risk of Mortality: Systematic Review and Meta-Analysis. Frontiers in Medicine. 2020. pmid:32793620
- 41. Ramadan HK-A, Mahmoud MA, Aburahma MZ, Elkhawaga AA, El-Mokhtar MA, Sayed IM, et al. Predictors of Severity and Co-Infection Resistance Profile in COVID-19 Patients: First Report from Upper Egypt. Infect Drug Resist. 2020;Volume 13: 3409–3422. pmid:33116660
- 42. Ciceri F, Castagna A, Rovere-Querini P, De Cobelli F, Ruggeri A, Galli L, et al. Early predictors of clinical outcomes of COVID-19 outbreak in Milan, Italy. Clin Immunol. 2020;217: 108509. pmid:32535188
- 43. Zhu L, She ZG, Cheng X, Qin JJ, Zhang XJ, Cai J, et al. Association of Blood Glucose Control and Outcomes in Patients with COVID-19 and Pre-existing Type 2 Diabetes. Cell Metab. 2020. pmid:32369736
- 44. Sanyaolu A, Okorie C, Marinkovic A, Patidar R, Younis K, Desai P, et al. Comorbidity and its Impact on Patients with COVID-19. SN Compr Clin Med. 2020; 1. pmid:32838147
- 45. Yahia F, Zakhama L, Ben Abdelaziz A. COVID-19 and cardiovascular diseases. Scoping review study. Tunisie Medicale. 2020. pp. 283–294. pmid:32395790
- 46. Zhao Q, Meng M, Kumar R, Wu Y, Huang J, Lian N, et al. The impact of COPD and smoking history on the severity of Covid-19: A systemic review and meta-analysis. J Med Virol. 2020 [cited 4 Aug 2020]. pmid:32293753
- 47. Guan WJ, Liang WH, Zhao Y, Liang HR, Chen ZS, Li YM, et al. Comorbidity and its impact on 1,590 patients with Covid-19 in China: A nationwide analysis. Eur Respir J. 2020;55.
- 48. Guan W, Ni Z, Hu Y, Liang W, Ou C, He J, et al. Clinical characteristics of coronavirus disease 2019 in China. N Engl J Med. 2020;382: 1708–1720. pmid:32109013
- 49. Zhao K, Li R, Wu X, Zhao Y, Wang T, Zheng Z, et al. Clinical features in 52 patients with COVID-19 who have increased leukocyte count: a retrospective analysis. Eur J Clin Microbiol Infect Dis. 2020;39: 2279–2287. pmid:32651736
- 50. Li X, Wang L, Yan S, Yang F, Xiang L, Zhu J, et al. Clinical characteristics of 25 death cases with COVID-19: A retrospective review of medical records in a single medical center, Wuhan, China. Int J Infect Dis. 2020. pmid:32251805
- 51. Wu Y, Potempa LA, El Kebir D, Filep JG. C-reactive protein and inflammation: Conformational changes affect function. Biological Chemistry. 2015. pmid:26040008
- 52. Petrilli CM, Jones SA, Yang J, Rajagopalan H, O’Donnell LF, Chernyak Y, et al. Factors associated with hospitalization and critical illness among 4,103 patients with COVID-19 disease in New York City. medRxiv. 2020.
- 53. Wong SH, Lui RN, Sung JJ. Covid‐19 and the digestive system. J Gastroenterol Hepatol. 2020;35: 744–748. pmid:32215956
- 54. Peiris JSM, Lai ST, Poon LLM, Guan Y, Yam LYC, Lim W, et al. Coronavirus as a possible cause of severe acute respiratory syndrome. Lancet. 2003. pmid:12711465
- 55. Shoenfeld Y. Corona (COVID-19) time musings: Our involvement in COVID-19 pathogenesis, diagnosis, treatment and vaccine planning. Autoimmunity Reviews. 2020. pmid:32268212
- 56. Soria Arcos F, Romero Puche A, Vicente Vera T. Controversy regarding ACE inhibitors / ARBs in COVID-19. Rev Española Cardiol (English Ed. 2020;73: 516. pmid:32371022
- 57. Simonnet A, Chetboun M, Poissy J, Raverdy V, Noulette J, Duhamel A, et al. High Prevalence of Obesity in Severe Acute Respiratory Syndrome Coronavirus-2 (SARS-CoV-2) Requiring Invasive Mechanical Ventilation. Obesity. 2020;28: 1195–1199. pmid:32271993