Bioscience Biotechnology Research Communications

An International  Peer Reviewed Refereed Open Access Journal

P-ISSN: 0974-6455 E-ISSN: 2321-4007

Bioscience Biotechnology Research Communications

An Open Access International Journal

Nuha A. Abdelmutalab,1 Sitalnesa Abdelhafeez,2 Atyah Y. Alzahrani,3 Fawziah
Ayed Alsawatd, Roua S. Baty,5 Abubakr Eltom6 and Omaima Nasir*7

1Department of Infection Control, King Faisal Medical Complex. P.O. Box.2265, Taif 21944. Saudi Arabia

2Department of Communicable Diseases Control Directorate, Taif, 21944, Saudi Arabia.

3Department of Family Medicine, Shehar Primary Health Care, Taif, 21944, Saudi Arabia

4Department of Planning and Transformation, Directorate of Health Affairs, P.O. Box 26537, Taif,21944, Saudi Arabia.

5Department of Biotechnology, College if Science, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.

6Department of General and Geriatric Medicine, St. Helens and Knowsley NHS, L35 5DR, United Kingdom.

7Department of Biology, Turabah University College, Taif University, P.O. Box 11099, Taif 21944, Saudi Arabia.

Corresponding author email:

Article Publishing History

Received: 17/02/2022

Accepted After Revision: 24/04/2022


Coronavirus 2019 (COVID 19) is one of the pandemics registered for 2020, with the entire world affected. COVID 19 disease is diagnosed based on symptoms and risk factors, and both swab and RT-PCR tests are available to confirm the disease. The aim of this study was to the underlying health issues which might be connected to development of severe COVID19.A retrospective study was carried out in a tertiary hospital (Corona center) in Saudi Arabia from August 2020 to December 2020 to identify the risk factors of mortality in ICU admitted COVID-19 patients and to assess the underlining sociodemographic and medical conditions that may lead to the development of severe COVID-19. Data was collected from patients’ medical records. In this study, 174 subjects were recruited and 71.3% of the population is male and 28.7% as female.

Survival was 52%, whereas non-survivors was 48%. The average age was 57.7±16.0 years old.  The most common clinical manifestations were shortness of breath (75.9%), cough (67.8%), and fever (64.9%). T2DM was one of the highest co-morbidities was documented. Binary logistic regression analysis confirmed both the age and fever showed the positive association (p<0.05) and the serum parameters such as CRP, d dimer, neutrophils and lymphocytes showed the elevated levels and positive association (p<0.05).  In conclusion, the current study results confirmed HTN, CKD, and heart disease comorbidities all played a substantial impact in the development of COVID-19, and that older age (>60 years) also played a role in COVID 19 patients. Saudi Arabia is one of the nations that has successfully managed the COVID 19.


COVID 19, Comorbidities, Serum Parameters, Survivors and Non-Survivors.

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Abdelmutalab N. A, Abdelhafeez S, Alzahrani A. Y, Alsawatd F. A, Baty R. S, Eltom A, Nasir O. Assessment of Risk Factors for Severe Coronavirus Disease -19 in Taif Province, Saudi Arabia. Biosc.Biotech.Res.Comm. 2022;15(2).

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Abdelmutalab N. A, Abdelhafeez S, Alzahrani A. Y, Alsawatd F. A, Baty R. S, Eltom A, Nasir O. Assessment of Risk Factors for Severe Coronavirus Disease -19 in Taif Province, Saudi Arabia. Biosc.Biotech.Res.Comm. 2022;15(2). Available from: <a href=”“></a>

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The story of the coronavirus begins at the end of 2019 in China, in a well-known location known as the Wuhan market (Farasani, 2021). Because of the threat to the entire human population, the World Health Organization (WHO) has declared coronavirus 2019 (COVID19) a pandemic (Daniel, 2020). Severe acute respiratory syndrome Coronavirus 2 (SARSCoV-2), the seventh human coronavirus, has been discovered. As a result of this, the virus has spread throughout the entire world (Ciotti et al., 2020). Coronaviruses (also known as Coronavirinae/CoV) are enclosed, single-stranded, positive-sense RNA viruses. It’s likely that the CoVs genome, which ranges from 26 to 32 kilobases in length, is the biggest viral RNA yet discovered. CoVs have historically been recognized to cause disease in humans, and there are currently six identified CoVs of which two falls into the low pathogenic and two falls into the highly pathogenic category.

Between 10-30% of all upper respiratory tract infections are caused by CoVs that have a low pathogenicity, including 229E, HKU1, OC43, and NL63. In contrast, CoVs with high pathogenicity, such SARS and MERS, primarily infect the lower respiratory system and produce deadly pneumonia (Han et al., 2020). SARS-CoVs has a diameter of ~50–200 nm, ranging from 26-32 kb. SARS-CoV-2 is a β-coronavirus that contains a single positive RNA strand. Its 60-140 nm diameter envelope provides it with a square, elliptical form. In its genome, there are special parts derived from 9 Wuhan patients that consist of a close-knit 29,903 basis pair of single stranded RNA pairs (88%) of β-coronavirus isolated bats. The untranslated area (UTR) of the SARS-CoV-2 genome is composed of 50 leader sequence, 1a/b free reading frame genes, spike protein, the protein envelope, protein membrane/ matrix and auxiliary protein, nucleoprotein and sequenced 3´UTR (Farasani, 2020).

The most typical symptoms of COVID 19 are fever, cough, and weariness. One of the first signs is a loss of taste or scent. Shortness of breath, muscle aches, headache, runny nose, nausea, vomiting, diarrhea, and rashes are the remaining symptoms. These factors, such crowding, literacy levels, and health care employees, are all involved in increasing the likelihood of infection and infection is often a problem in the elderly, men, and those with preexisting conditions (Rashedi et al., 2020).

Because of community transmission, the risk of COVID 19 in the general population is currently very high. COVID-19 harm to the population with established risk factors for severe illness outcome and COVID-19 can cause serious disease in people of any age who have specific underlying medical issues. COVID-19 is a newly discovered disease. COVID-19 can affect anyone, and the disease can cause mild to severe symptoms. Some persons may be more likely than others to suffer from severe disease because they have qualities or medical conditions that put them at risk.

There is currently little evidence and information available about the impact of underlying medical disorders and if they raise the risk of severe disease from COVID-19. Based on what we know at this time, it is extremely vital to recognize the persons at high risk of serious disease from COVID-19, as well as those who live with them, in order to protect yourself from obtaining COVID-19. If you have COVID-19, you are more likely to be admitted to the hospital or ICU if you have certain risk factors.

Knowing the risk factors connected with COVID-19 is important because it can help people who are at high risk take further precautions. Almost 98% of COVID-19 cases from Saudi Arabia has recovered and 1% of the mortality cases was documented and only <1% of active cases were listed. Limited studies in the Saudi Arabia has performed with the risk of developing with severe form. Therefore, the current study was aimed to investigate the underlying health issues which might be connected to development of severe COVID-19.


This is a retrospective and hospital-based study that was conducted at King Faisal Medical Complex hospital in Taif Province from August to December 2020. Following authorization from the Ministry of Health, clinical details, personal and family history data were gathered from medical records of patients admitted to Intensive Care Unit. This rationale study will address one of the most important questions to address the currently unfolding pandemic: “what are the risk factors for severe illness or death and will allow us to understand the risk factors for disease severity providing a comprehensive picture of the characteristics of COVID-19 patients.”

The inclusion criteria of the cases were patients diagnosed with COVID 19 in any nationality and the patients without COVID-19 infection can be considered as exclusion criteria of the enrolled subjects. In this study, we have selected 174 cases in which 50 females and 124 males were involved. In this study, 77 non-Saudi and 97 Saudi subjects were involved. Both the symptoms and comorbidities details were recorded in all the enrolled patients.

Biochemical parameters: In this study, serum blood was collected from all the patients who have involved and used for c-reactive protein (CRP), lymphocytes, neutrophils and d dimer tests.

Statistical analysis: Statistical analysis was performed with SPSS software and we have analyzed both the numerical and categorical variables with frequency and percentages. Binary logistic regression analysis was performed with the obtained data. P values less than 0.05 is considered as statistically significant (p<0.05) (Khan et al., 2019).


In this hospital-based study, we have opted 28.7% of women and 71.3% of men. The mean age of the 174 participants were found to be 57.7±16.0. The age was categorized into <35 (8.6%), between 36-59 (43.7%) and >60 (47.7%) years of age. Saudi subjects (44.3%) were found to be higher than non-Saudi participants in this study (55.7%). Table 1 presents information on sociodemographic, symptoms, and comorbidities. The general COVID 19 symptoms such as high in SOB (75.9%), cough (67.8%), fever (64.9%), diarrhea (13.2%), fatigue (8.6%) and headache (8%). Type 2 diabetes mellitus (T2DM; 47.7%), hypertension (HTN; 39.7%), heart disease (15.5%), chronic kidney disease (CKD, 12.1%) and bronchial asthma (BA, 8.6%) were among the comorbidities revealed in this studied participant. According to Figure 1, 48% of hospitalized patients were determined to be alive, while the remaining 52% were confirmed to be dead. Table 2 shows the survival and non-survival rates of participants infected with COVID-19 who were admitted to the Taif hospital in the ICU.

Figure 1: Status of COVID 19 patients admitted into ICU

Table 1. Clinical and sociodemographic characteristics of COVID 19 patients hospitalized to the ICU

           Gender Frequency Percent
Female 50 28.7
Male 124 71.3
           Age (Mean ± SD) 57.7 ± 16
           Age group < 35 15 8.6
36 – 59 Y 76 43.7
≥ 60 83 47.7
           Nationality Non-Saudi 77 44.3
Saudi 97 55.7
           SOB No 42 24.1
Yes 132 75.9
           Cough No 56 32.2
Yes 118 67.8
           Fever No 61 35.1
Yes 113 64.9
           Diarrhea No 151 86.8
Yes 23 13.2
           Myalgia or fatigue No 159 91.4
Yes 15 8.6
           Headache No 160 92
Yes 14 8
          Type 2 DM No 91 52.3
Yes 83 47.7
          Hypertension No 105 60.3
Yes 69 39.7
          Heart disease No 147 84.5
Yes 27 15.5
          Chronic kidney disease No 153 87.9
Yes 21 12.1
         Asthma, Bronchial Asthma (BA) No 159 91.4
Yes 15 8.6

Table 2. Shows the survival and non-survival rates of COVID 19 patients hospitalized to the ICU.

Variable Survivor Non- Survivor Total P-value
Gender N (%)
     Female 21(23.3%) 29(34.5%) 50 (28.7%) 0.131
     Male 69(76.7%) 55(65.5%) 124(71.3%)
Age N (MIN – MAX) 90(14 – 82) 84(23 – 92) 174(14 – 92)
Age (mean ±SD) 51 ±14 65 ±14 57.7 ± 16
Age group
     ≤ 35 13(14.4%) 2(2.4%) 15(8.6%)
     36 – 59 Y 51(56.7%) 25(29.8%) 76(43.7%) 0.00
     ≥ 60 26(28.9%) 57(67.9%( 83(47.7%)
   Dyspnea SOB 61(67.8%) 71(84.5%) 132(75.9%) 0.013
   Cough 54(60%) 64(76.2%) 118(67.8%) 0.02
   Fever 49(54.4%) 64(76.2%) 113(64.9%) 0.004
   Diarrhea 14(15.6%) 9(10.7%) 23(13.2%) 0.37
   Myalgia or fatigue 6(6.7%) 9(10.7%) 15(8.6%) 0.4
   Headache 8(8.9%) 6(7.1%) 14(8%) 0.7
  Type 2 DM 38(42.2%) 45(53.6%) 83(47.7%) 0.17
    Hypertension 26(28.9%) 43(51.2%) 69(39.7%) 0.003
    Bronchial Asthma,     (BA) 9(10%) 6(7.1%) 15(8.6%) 0.5
  Chronic kidney disease 5(5.6%) 16(19%) 21(12.1%) 0.006

Heart disease

7(7.8%) 20(23.8%) 27(15.5%) 0.003

Table-2 shows the list of COVID-19 survivors and non-survivors admitted to the ICU. Males were found to be higher than females in both categories among survivors and non-survivors (p=0.13). The survivors’ minimum and maximum ages were determined to be 14-82 years old, whereas the non-survivors’ minimum and maximum ages were found to be 23-92 years old. The mean ages of survivors and non-survivors were reported to be 51±14 and 65±14, respectively, with a non-significant association (p>0.05). Among survivors, the majority of the age groups was found to be high in between 36-59 years of age with 56.7%, followed by 28.9% in 60 and above years of age and 14.4% in below 30 years of age, while in non-survivors, 67.9% was found to be high in below 60 years of age, followed by 29.8% in between 36-59 years of age, and only 2.4% in above 35 years of age with the statistical association (p<0.05).

Among the symptoms, dyspnea SOB, cough, and fever were found to be more prevalent in non-survivors when compared to survivors and showed a significant association (p<0.05), whereas in survivors, both diarrhea and headache were found to be more prevalent when compared to non-survivors with a non-significant association (p>0.05), and fatigue prevalence was found to be more prevalent in non-survivors when compared to survivors (p=0.7). T2DM and BA were shown to have a non-significant association when compared between survivors and non-survivors (p>0.05) in the comorbidities. Other comorbidities, such as HTN, CKD, and heart disease, were found to be substantially associated when comparing survivors to non-survivors (p<0.05).

Binary logistic regression analysis among the survival subjects of independent factors was defined in Table-3. In this study, numerous variables such as age, gender, fever, cough, fatigue, dyspnea, diarrhea, headache, T2DM, HTN, BA, CKD and heart disease were involved in the survivor subjects and only the age (OR-5.48 [95%CI:2.54-11.81]; p=0.001) and fever (OR-3.15 [95%CI:1.10-8.97]; p=0.03) variables was associated. The other variables were found to be non-significant when performed the logistic regression analysis (p>0.05).

Table 3. Binary logistic regression survival status and independent factors



OR 95% C. I P-value
Lower Upper
Age 5.48 2.541 11.815 0
Gender 0.675 0.3 1.517 0.341
Fever 3.15 1.105 8.979 0.032
Cough 1.22 0.418 3.562 0.717
Myalgia or fatigue 3.676 0.888 15.212 0.072
Dyspnea 1.426 0.534 3.809 0.479
Diarrhea 0.569 0.194 1.669 0.304
Headache 0.506 0.13 1.973 0.326
Type2DM 0.504 0.212 1.194 0.119
Hypertension 1.654 0.701 3.905 0.251
Bronchial Asthma (BA) 1.195 0.3 4.759 0.8
Chronic kidney disease 3.195 0.865 11.799 0.081
Heart disease 1.977 0.676 5.781 0.213

Table 4 shows the biochemical parameters such as CRP, lymphocytes, neutrophils, and d dimer in COVID-19 survivors admitted to the ICU. When compared to survivors, the elevated levels were found to be higher in non-survivors, indicating a positive association. CRP levels were found to be increased in non-survivors at 98.6% and survivors at 83.3% (p=0.001). The aberrant lymphocyte counts were 73.8% and 58.3% in non-survivors and survivors, respectively (p=0.05). The number of increased neutrophils was 44.6% in non-survivors and 57.4% in survivors (p=0.004). The enlarged levels of d dimer in non-survivors were 93.2% and 80.3% in survivors (p=0.001).

Table 4. Lab abnormalities of COVID 19 patients admitted to ICU

Variables Survivor Non- Survivor Total* P-value
C Reactive Protein
     Elevated 60(83.3%) 70(98.6%) 130(90.9%) 0.001
     Normal 12(16.7%) 1(1.4%) 13(9.1%)
     Lymphopenia 35(58.3%) 45(73.8%) 80(66.1%) 0.05
     Normal 25(41.7%) 16(26.2%) 41(33.9%)
     Elevated 19(31.7%) 35(57.4%) 54(44.6%) 0.004
     Normal 41(68.3%) 26(42.6%) 67(55.4%)
D dimer
     Elevated 57(80.3%) 55(93.2%) 112(86.2%) 0.001
     Normal 14(19.7%) 4(6.8%) 18(13.8%)

*Total is differing for each test according to number of patients tested


The purpose of this study was to investigate at the underlying health issues associated with demographic information, symptoms, and comorbidities among hospitalized patients in the ICU with COVID-19 in the Taif city of Saudi Arabia. The current study results confirmed the significant association with age group, documented symptoms such as Dyspnea SOB, cough, fever and other comorbidities such as HTN, CKD and heart disease (p<0.05).  Binary logistic regression analysis revealed the positive association with age and fever (p<0.05) and all the biochemical parameters such as CRP, lymphocytes, neutrophils and d dimer showed the statistical association (p<0.05).

There have been no studies conducted in Saudi Arabia among COVID-19 patients admitted to the ICU, and this is the first research study was carried out in the Saudi population from Taif city. T2DM, HTN, BA, CKD, and heart disease were among the comorbidities studied in our study. Unfortunately, due to the pandemic crisis, we did not record body mass index values to categorize obesity levels, despite the fact that obesity is one of the known risk factors for COVID-19. One of the meta-analysis and systematic reviews discovered that HTN, DM, and cardiovascular disease (CVD), along with age and being male, are all highly connected to severe COVID-19 and can provide a better estimate of risk for severe COVID-19 (Matsushita et al., 2020). Another systematic reviews and meta-analysis studies found that those over the age of 65, men, HTN, CVD, diabetes, and cancer were all more likely to die from COVID-19 infection. Patients with a poor prognosis could be identified based on these data (Parohan et al., 2020).

The immune system varies with age in a similar manner to the differences in immunological response related to sex. It is thought that as people age, their immune systems become chronically inflamed, which makes them more vulnerable to infection and tissue damage. Aging is related with comorbidities and a lower reserve capacity in essential organs, resulting in greater frailty and increased risk of mortality and infection with COVID-19 when infected. In this study, age was divided into three categories: (a) <35 years, (b) 36-59 years, and (c) >60 years, with 47.7% being >60 years, 43.7% being 36-59 years, and 8.6% being <35 years of age. A positive association was observed among the three age groups compared between the survivors and non-survivors (p=0.001). Our study was found to be in association with the previous studied results (Pijls et al., 2021).

Similar studies have been conducted in different regions of Saudi Arabia based on our current study. From the beginning of the pandemic crisis to current scenario, WHO has strongly recommended to follow three rules to avoid the COVID-19 infections: social distance, sanitization and wearing a mask. All countries have rigorously enforced and extra lockdown was performed to stop the infection rate, and Saudi Arabia is one of the countries that has successfully controlled the COVID-19.

Until September 5th, 2021, the overall number of infected cases was 545,243, the number of recovered cases was 534062, and the total mortality was 8579, with 2602 active cases. Apart from Saudi Arabia, there are other countries which have been successfully managed the infection. Ministry of Health from Saudi Arabia has played a pivotal role in controlling the infections and proper measures have been taken, as well as residents of the kingdom received a couple of doses of free vaccines.

Aside from RT-PCR, biochemical markers were important in COVID-19 patients. A recent review supported the importance of CRP and d dimer levels in identifying COVID-19 patients (Farasani, 2021). In our study, additionally with CRP and d dimer, we have screened lymphocytes and neutrophils levels in the COVID-19 patients and unfortunately, all the elevated levels were confirmed in the non-survivors and all the parameters showed the significant association (p<0.05). Strong evidence suggests that neutrophils play a crucial role in pathogenesis, particularly in COVID 19 patients (Reusch et al., 2021).

One of the limitations of this study was not incorporating the RT-PCR details. Additionally, clinical details were not incorporated. The other limitations of our study were to skip the severe forms of diagnosis which is mandatory, but due to COVID-19, we couldn’t document the data. The strength of this study was to involve the 174 subjects who were infected with COVID-19. Although the sample size was small but we have managed to enroll the limited subjects during the pandemic situations.


The current study shows that HTN, CKD, and heart disease comorbidities all played a substantial impact in the development of COVID-19, and that older age (>60 years) also played a role in COVID-19 patients. Developing a unique multi-item scale method to predict COVID-19 patients is indicated as a future proposed study.


We acknowledge Taif University Researchers Supporting Project number (TURSP-2020/269), Taif University, Taif, Saudi Arabia.

Special thanks to Mashael Abdullrahman Alamri, Doaa Althomaly, Razan AlGhamdi and Shmokh Aljafary for their contribution in data collection.

Ethical Approval: Research and Studies Department, Directorate of Health Affairs – Taif, Health Ministry, Saudi Arabia, IRB Registration Number with KACST, KSA: HAP-02-T-067, Approval Number: 395.

Funding of study: This work was supported by Taif University Research Supporting Project number (TURSP-2020/269), Taif University, Taif, Saudi Arabia

Declarations: Author(s) declare that all works are original and this manuscript has not been published in any other journal.

Data Availability: All data sheet available on request from corresponding author.

Author Contributions:

Conceptualization: Nuha A. Abdelmutalab, Sitalnesa Abdelhafeez, Atyah Y.Alzahrani,

Fawziah Ayed Alsawat, Roua S.Baty and Omaima Nasir.

Data curation: Nuha A. Abdelmutalab, Sitalnesa Abdelhafeez and Atyah Y.Alzahrani.

Methodology: Nuha A. Abdelmutalab Sitalnesa Abdelhafeez and Atyah Y.Alzahrani.

Data Collection: Mashael Abdullrahman Alamri, Doaa Althomaly, Razan AlGhamdi and Shmokh Aljafary

Data analysis: Sitalnesa Abdelhafeez, Nuha A. Abdelmutalab and Omaima Nasir.

Writing – original draft: Nuha A. Abdelmutalab Sitalnesa Abdelhafeez, Atyah Y.Alzahrani

Fawziah Ayed Alsawat, Roua S.Baty, Abubakr Eltom and Omaima Nasir.

Reviewing & Editing: Nuha A. Abdelmutalab, Sitalnesa Abdelhafeez, Atyah Y.Alzahrani,

Fawziah Ayed Alsawat, Roua S.Baty, Abubakr Eltom and Omaima Nasir.

Abbreviations: ICU, Intensive Care Unit, DM, Diabetes Mellitus, T2DM, Type 2 Diabetes Mellitus, CRP, C Reactive Protein, CVD, Cardiovascular disease, HTN, Hypertension, CKD, chronic kidney disease, RT-PCR, Real Time polymerase Chain Reaction, RNA, Ribonucleic Acid, SOB, Shortness of Breath, BA, Bronchial Asthma, SPSS, Statistical Package for the Social Sciences.


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