Quality of life among epileptic patients in Khartoum State neurological clinics, Sudan: a cross-sectional study

Abstract

Background:

Epilepsy is a chronic non-communicable disease defined as recurrent and unprovoked seizures. Epilepsy causes a wide range of challenges that affect the patient’s quality of life (QoL). This study aimed to assess the quality of life and associated factors among patients with epilepsy in Khartoum State, Sudan.

Methods:

This hospital-based cross-sectional study involved epileptic patients recruited from three neurological clinics located in Khartoum State, Sudan. The questionnaire consisted of the Short-Form Health Survey (SF-36) to assess quality of life, along with items covering the patients’ sociodemographic and clinical characteristics. The data were analyzed using SPSS v.23. The Kruskal–Wallis test, Mann-Whitney U test, and multiple logistic regression were used to analyze associations between clinical and demographic factors and QoL scores. The level of significance was set at 0.05.

Results:

A total of 106 epileptic patients were interviewed. The total mean score of QoL SF-36 in these patients was 59.8 ± 13.9. A total of 44.3% of the epileptic patients demonstrated a good quality of life. For different SF-36 subscales, the highest mean score was for the physical functioning domain (78.7 ± 21.3). All demographic and clinical characteristics were not significantly associated with the QoL score. Age, gender, and the presence or absence of workdays were found to be significantly associated with the physical functioning subscale (P = 0.003, 0.036, and 0.003, respectively), while marital status and number of outpatient visits were significantly associated with the mental health subscale (P = 0.041 and 0.038, respectively). Additionally, the presence or absence of workdays was significantly associated with the role limitation due to the physical health subscale (P = 0.023).

Conclusion:

The study findings suggested that most patients with epilepsy have a moderate-to-good quality of life. The highest score was for the physical functioning domain. A significant relationship was identified between specific socio-demographic and clinical factors and various SF-36 QoL subscales. These findings highlight the need for targeted, culturally sensitive interventions, as well as longitudinal research to address the broader determinants of quality of life in this population.

Introduction

Epilepsy is a chronic non-communicable disease characterized by recurrent, unprovoked seizures caused by sudden, brief, and excessive electrical discharges in clusters of neurons across various brain regions. The clinical presentation of seizures is influenced by the location of seizure onset, the size of the affected brain region, and the frequency of seizures^[1]. Epilepsy accounts for over 0.5% of the global disease burden. People with epilepsy often experience comorbidities, including anxiety and depression, as well as physical injuries and intellectual disabilities^[2]. In Sudan, data on the burden of epilepsy remain scarce. Only two studies have assessed the prevalence of epilepsy, both among children in Khartoum State. A study conducted in 1983 reported a prevalence of 0.9 per 1000 among school-aged children in Khartoum Province^[3]. A more recent study in 2016 found a higher prevalence of 4 per 1000 among 74 949 school children in Khartoum State^[4]. However, no epidemiological studies have been conducted among the adult population. Despite the limited data, epilepsy is estimated to account for 1.6% of annual mortality and 238.7 disability-adjusted life years (DALYs) per 100 000 population in Sudan^[5].

HIGHLIGHTS

• Patients with epilepsy in Khartoum State exhibit a moderate-to-good quality of life.

• The physical functioning domain had the highest QoL score among SF-36 subscales.

• Age, gender, and workdays were linked to physical functioning, while marital status and outpatient visits influenced mental health.

• Further qualitative research is needed to explore predictors of QoL in epileptic patients.

The diagnosis of epilepsy requires a patient to have two or more unprovoked seizures. The type of epilepsy is determined through a detailed medical history, neurological examination, EEG results, and brain imaging such as CT or MRI. Based on these findings, an appropriate treatment strategy and evaluation plan is developed for the patient^[6].

Epilepsy is classified into three levels: (i) seizure type, (ii) epilepsy type, and (iii) epilepsy syndrome. Epilepsy syndrome refers to a collection of characteristics that tend to appear together, including seizure types, EEG, and imaging features^[7]. While understanding the classification and management of epilepsy is crucial for effective treatment, it is equally important to go beyond this medical focus to explore how the condition affects patients’ quality of life.

The World Health Organization defines quality of life as “The way a person views their place in life in relation to their objectives, standards, expectations, and concerns, as well as the culture and value systems in which they live”^[8]. Epilepsy has profound effects on individuals’ lives, contributing to significant physical, psychological, and social challenges^[9,10]. Seizures, which are unpredictable, can lead to physical risks such as burns, falls, and drowning, leaving patients feeling insecure and vulnerable^[11].

In addition to these physical risks, epilepsy is strongly associated with social stigma and a lower quality of life (QoL)^[12]. Epileptic patients are more likely to experience depression, anxiety, and low self-esteem. They also face social difficulties, such as lower marriage rates, increased social isolation, and a higher likelihood of being underemployed or unemployed^[9,13]. Furthermore, the financial burden of epilepsy, including high socioeconomic and medication costs, significantly affects their quality of life^[14]. These challenges may even increase the risk of suicide among individuals suffering from epilepsy^[15].

Together, these interconnected physical, psychological, and socioeconomic factors highlight the profound and multifaceted impact of epilepsy on quality of life.

Today, QoL assessments are becoming increasingly popular as they can provide insight into epilepsy-related complaints of learning, attention, physical pain, and health-related QoL^[16]. Healthcare planners are realizing more and more that disease measures alone do not adequately determine a person’s state of health^[17]. A deeper comprehension of QoL of individuals with epilepsy who are living in different countries is crucial, as numerous cultural, ethnic, and economic distinctions influence QoL^[18].

While many studies evaluate QoL of epileptics worldwide, there are few comparable studies from developing countries, particularly Sudan. Determining the extent of the issue is essential to the methodical approach to managing epilepsy difficulties and suggesting several approaches to improve it^[19]. Thus, the purpose of this study was to assess the QoL of patients with epilepsy and its relationship with their socio-demographic and clinical characteristics in Khartoum State, Sudan.

Methods

This descriptive, cross-sectional, hospital-based study was conducted from 5 September to 13 October 2022 in three neurology clinics located in Khartoum State. The selected clinics included two governmental hospitals, one in Khartoum locality and the other in Omdurman locality, as well as one private hospital in Khartoum locality. These centers were chosen due to their high patient visit frequency. Data were collected from 106 Sudanese epilepsy patients attending follow-up visits. These patients were included through total coverage sampling of all eligible epilepsy cases based on the study’s inclusion criteria during the data collection period. The study included male and female patients aged 18 years or older, while severely ill patients and those presenting with active convulsions were excluded.

Data were collected through face-to-face interviews using a structured questionnaire that included both closed and open-ended questions. The questionnaire consisted of two sections: the first focused on socio-demographic and clinical information such as age group, gender, marital status, occupation, residence, workdays, health insurance, number of outpatient and hospital visit, number of doctors consulted, number of drugs used, and healthcare fees. The second section assessed quality of life using the standardized Short Form-36 (SF-36) model^[20]. The SF-36 provides raw scores ranging from 0 to 100 across 36 items, divided into nine health subscales: physical functioning (PF) (10 items), role limitations due to emotional problems (RE) (3 items), role limitations due to physical problems (RP) (4 items), social functioning (SF) (2 items), bodily pain (BP) (2 items), health change (1 item), emotional well-being (5 items), energy/vitality (VT) (4 items), and general health (GH) (5 items). The SF-36 is easy to use, well-accepted by patients, and meets high standards of reliability and validity. Its reliability is supported by a Cronbach’s alpha exceeding 0.85, with reliability coefficients above 0.75 across all dimensions, except for the social functioning subscale^[21].

The physical aspect of QoL is reflected in the PF, RP, and BP subscales and is associated with the GH subscale, while the mental aspect is reflected in the RE, SF, and emotional well-being subscales and is associated with the VT subscale^[22]. Unlike other studies, this study included and scored the health change subscale alongside the other eight subscales^[21]. Scoring involves a multi-step process. First, item responses are recorded according to standardized scoring algorithms to ensure that higher scores uniformly reflect better health status. This is essential, as some items are phrased positively while others are phrased negatively. For example, a low score on an item about limitations may indicate better health, while a high score on an item about vitality indicates better health. Recoding adjusts for this directionality. Following recording, items within each subscale are summed and averaged, then transformed linearly to a 0–100 scale, where 0 represents the poorest health and 100 indicates the best possible health in that domain. This allows comparability across subscales despite differing numbers of items^[23].

As an alternative approach to assess overall quality of life, the average of the nine subscale scores was calculated and categorized into four levels: poor (0 to 40), moderate (more than 40 to 60), good (more than 60 to 80), and excellent (more than 80 to 100). The study followed the updated STROCSS 2025: Strengthening the Reporting of cohort, cross-sectional and case-control studies in Surgery guidelines^[24].

Data were entered and analyzed using IBM SPSS Statistics version 23. Descriptive statistics were employed to summarize the socio-demographic and clinical characteristics of participants. Categorical variables were presented as frequencies and percentages, while continuous variables (SF-36 scores) were reported as means and standard deviations. The normality of continuous data, particularly SF-36 scores, was assessed using both the Kolmogorov-Smirnov and Shapiro-Wilk tests, which indicated a non-normal distribution.

Accordingly, non-parametric tests were applied where appropriate. The Kruskal–Wallis test was used to compare total QoL scores across multivariate data, while the Mann–Whitney U test was employed for comparisons between two groups. To identify potential predictors and adjust for confounding factors, a multiple linear regression model was constructed using the total SF-36 score as the dependent variable. Predictor variables included relevant demographic and clinical factors such as age, gender, marital status, number of outpatient and hospital visits, number of antiepileptic drugs, health insurance, and workdays. Additionally, correlations between individual QoL subscales and patient characteristics were explored using Kruskal–Wallis and Mann–Whitney U tests, depending on the nature and distribution of the data. A P value of <0.05 was considered statistically significant.

Results

Socio-demographic and clinical characteristics of epileptic patients

A total of 106 epileptic patients participated in the study. The majority were male (58.5%), with the 18–29 age group being the most represented (35.8%). Over half of the participants were married (51.9%). In terms of occupation, the largest group comprised housewives (18.9%), followed closely by freelancers (18%). Most patients resided in Omdurman City (33.9%), followed by Khartoum City (30.2%) (Table 1).

Table 1.

Socio-demographic characteristics of epileptic patients, n = 106

Variable	Category	Frequency	Percentage (%)
Age group	18–29 years old	38	35.8
	30–49 years old	33	31.1
	50 years old and above	35	33
Gender	Male	62	58.5
	Female	44	41.5
Marital status	Married	55	51.9
	Single	51	48.1
Occupation	Housewife	20	18.9
	Military soldiers	18	17
	Student	14	13.2
	Employer	18	17
	Freelancers	19	18
	Retired	17	16
Residence	Omdurman	36	33.9
	Khartoum	32	30.2
	Bahri	15	14.2
	Others a	23	21.6

^aAljazeera, Kurdofan, Shendi, Atbara, Blue Nile, Neyala, and New Halfa.

Regarding workdays, 45.3% had no workdays, while 54.7% worked at least two days per week. However, 76.4% had health insurance. In the past month, the total direct healthcare cost per person ranged from 0 SDG (covered by health insurance) to 220 000 SDG, with a mean of 54 331.6 SDG.

Regarding clinical characteristics of the patients, 38.7% of participants had no outpatient visit in the past month, while 43.4% had one visit, and only 1.9% had four visits. In terms of hospital visits, 76.4% had none, and just 0.9% had three visits. As for doctor consultations, 0.9% saw no doctors, 63.2% consulted one, 26.4% saw two, and 0.9% consulted six doctors. In terms of medication use, 67% used one drug, 24.5% used two, 7.5% used three, and 0.9% used five drugs during the past month.

Quality of life of epileptic patients

The overall mean SF-36 score among epileptic patients was 59.8 ± 13.9. Among the SF-36 subscales, the physical functioning domain recorded the highest mean score (78.7 ± 21.3), while the general health domain had the lowest mean score (31.8 ± 16.4) (Table 2).

Table 2.

Total SF-36 scale and its subscales score in epileptic patients, n = 106

Scale	Mean	SD	Minimum	Median	Maximum
Physical functioning	78.7	21.3	5	85	100
Role limitation due to emotional problem	77.9	24.9	0	75	100
Role limitation due to physical health	63.5	30.8	0	68.8	100
Social functioning	72.4	20.8	12	75	100
Pain	56.7	31.7	0	57.5	100
Health change	56.4	22.9	25	75	75
Emotional well-being	52.6	15.3	25	50	85
Energy/vitality	41.7	12.5	12.5	43.8	68.8
General health	31.8	16.4	10	35	85
Total	59.8	13.9	26.9	60.3	86.7

The study revealed that the majority of epileptic patients (44.3%, n = 47) had a good quality of life. Additionally, 40.6% (n = 43) exhibited a moderate quality of life, 9.4% (n = 10) reported a poor quality of life, and only 5.7% (n = 6) achieved an excellent quality of life (Fig. 1).

Figure 1.

Levels of quality of life of epileptic patients, n = 106.

Correlation analysis

The analysis revealed no significant associations between the QoL score and any of the demographic or clinical characteristics, including age, gender, marital status, workdays, health insurance, number of outpatient visits in the last month, hospital visits in the last month, doctors consulted in the last month, number of antiepileptic drugs taken in the last month, and total healthcare fees for the last month, as assessed using the Mann-Whitney test and Kruskal–Wallis test (Table 3).

Table 3.

Relationships between total QoL-SF36 score and demographic and clinical characteristics, n = 106

Characteristic	Means	Test statistic (H or U)	P value
Ageb		H = 5.861	0.053
18–29	62.69
30–49	61.27
50 years and above	55.26
Gendera		U = 1203.0	0.30
Male	60.86
Female	58.29
Marital statusb		H = 2.265	0.519
Single	61.24
Married	58.97
Divorced	59.72
Widowed	48.59
Workdaysa		U = 1663.5	0.085
Had workdays	62.00
Didn’t have workdays	57.14
Health insurancea		U = 1128.0	0.39
Insured	60.40
Uninsured	57.84
Number of outpatient visitsb		H = 3.921	0.207
None	60.75
Once	59.28
Twice	55.90
More than two times	67.58
Number of hospital visitsb		H = 4.828	0.185
None	61.37
Once	54.28
Twice	55.90
More than two times	60.14
Number of doctors consultedb		H = 1.998	0.736
One	60.72
Two	58.80
Three	59.25
More than three	52.85
Number of AEDb		H = 2.029	0.278
Monotherapy	60.82
Polytherapy	57.71
Total healthcare feesb		H = 5.621	0.229
0–10 000	56.79
10 001–50 000	63.39
50 001–100 000	61.88
100 001–200 000	54.93
>200 000	63.10

^aMann–Whitney test (U).

^bKruskal–Wallis test (H).

Further evaluation using multiple linear regression to determine the adjusted effects of these clinical and demographic factors also yielded a statistically insignificant model (P = 0.097), providing insufficient evidence to reject the null hypothesis (Table 4).

Table 4.

Multiple linear regression model to assess the adjusted effect of epilepsy patients’ factors on their QoL score, n = 106

Factors	Unstandardized coefficients		Standardized coefficients
	B	Std. error	Beta	t	P value
(Constant)	64.4	6.106		10.545	0.00
Marital status	.034	3.118	.001	.011	0.99
Gender	2.517	2.869	.090	.877	0.38
Age in years	−.169	.090	−.222	−1.871	0.06
Total healthcare fee in the past month	3.736E-5	.000	.147	1.370	0.17
Health Insurance	5.163	3.489	.159	1.480	0.14
Number of outpatient visits in the past month	.449	1.593	.029	.282	0.78
Number of hospital visits in the past month	−3.353	2.385	−.137	−1.406	0.16
Number of doctors consulted for epilepsy in the past month	−2.487	1.466	−.170	−1.696	0.09
Number of drugs used in the past month	−1.644	1.954	−085	−.842	0.40
Number of workdays in the past month	.644	.625	.107	1.031	0.31
Model R2; significance	150; F = 1.68; P = 0.097

A correlation analysis was conducted to examine the associations between the demographic and clinical characteristics of the patients and QoL SF-36 subscales. These subscales included Physical Functioning, Role Limitation due to Emotional Problems, Health Change, General Health, Social Functioning, Vitality, Mental Health, Bodily Pain, and Role Limitation due to Physical Health.

Significant findings are summarized in Table 5. Age, gender, and the presence or absence of workdays in the last month were significantly associated with the Physical Functioning subscale (P = 0.003, 0.036, and 0.003, respectively). Marital status and the number of outpatient visits in the last month showed significant associations with the Mental Health subscale (P = 0.041 and 0.038, respectively). Additionally, the presence or absence of workdays was significantly linked to the Role Limitation due to Physical Health subscale (P = 0.023).

Table 5.

Significant correlations between patients’ personal and clinical data with different QOLIE subscales. n = 106

Variable (subscale)	Patient characteristic	Groups compared	Test statistic (H or U)	P value
Physical functioning	Agea	18–29, 30–49, and 50+	H = 11.73	0.003c
Physical functioning	Genderb	Male female	U = 1038.5	0.036c
Mental health	Marital status a	Single, married, divorced, and widowed	H = 8.24	0.041c
Physical functioning	Workdaysb	No workdays	U = 1849.0	0.003c
		Had workdays
Role limitation due to physical health	Workdaysb	No workdays	U = 1742.5	0.023c
		Had workdays
Mental health	Number of outpatient visitsa	None, once, twice, and more than twice	H = 8.45	0.038c

^aKruskal–Wallis test (H).

^bMann–Whitney test (U).

^cSignificant association at P = 0.05. QOLIE, quality of life in epilepsy.

Discussion

Epilepsy is not only a neurological condition but also a significant determinant of patients’ overall well-being, influencing various aspects of their physical, emotional, and social lives. This study aimed to assess the quality of life among epileptic patients in Khartoum State’s neurological clinics, providing insights into the factors that shape their experiences and outcomes. Improving quality of life is a primary goal of epilepsy treatment^[25], as it encompasses more than just seizure control – it addresses the broader impact of the condition on daily functioning and social integration. Previous studies have shown that epileptic patients in the Middle East^[26] and Africa^[26,27] face significant sociocultural and healthcare disadvantages compared to their counterparts in Western societies^[28,29]. Despite these challenges, there remains a scarcity of QoL research from these regions, underscoring the importance of exploring this issue to inform culturally appropriate interventions and improve patient outcomes.

Various socio-demographic and clinical characteristics were assessed in this study to detect their possible impact on quality of life. The age range of the participants was 18–85 years, with 64.2% aged 30 years and above, and more than half of them were male 58.5% in alignment with the study conducted in Ethiopia^[30]. Half of the participants were married 51.9%, and 52% of them had an occupation; this is a good percentage compared to the fact that epileptic patients are at greater risk of problems concerning marriage and employment status^[31].

To assess quality of life, researchers typically rely on direct patient interviews or standardized questionnaires^[32]. In this study, the overall quality of life among epileptic patients, as measured by the SF-36 scale, was moderate. This finding is consistent with studies conducted in Ethiopia using the WHOQOL-BREF scale and in rural Kenya, both of which reported similar results^[33,34]. However, these outcomes differ from a study in Iraq, where patients reported substantially lower QoL scores using the SF-36 survey^[35]. These variations may be attributed to differences in healthcare accessibility, cultural perceptions of epilepsy, or social and economic conditions.

Regarding the SF-36 subscales, physical functioning, role limitation due to the emotion domain, and social functioning had the highest scores, indicating better performance in these areas. This suggests that despite living with epilepsy, many patients can maintain reasonable physical capacity, social interactions, and emotional roles, likely due to family or community support systems. These findings align with studies in the Netherlands and Canada, where similar domains scored the highest^[36,37]. Moreover, the physical and social domain scores in our study were higher than those reported in a previous Sudanese study conducted in 2009^[38]. That earlier study was carried out in three cities – Khartoum, Wad Medani, and Atbara – while our study was limited to Khartoum, the capital. This difference may reflect better access to healthcare services, stronger social support networks, and improved public awareness in the capital city compared to other regions. The exclusion of other cities may have contributed to the higher scores observed in our findings.

Conversely, the general health domain recorded the lowest scores, highlighting patients’ ongoing concerns about their overall health and well-being. This result is comparable to findings from Iraq, suggesting that the perception of general health remains a challenge for epileptic patients across various settings^[35].

Previous studies on QoL among individuals with epilepsy have consistently reported that their QoL is lower than that of the general population^[1,18,37]. However, our findings revealed that only 9.4% of patients had poor QoL, while approximately 40.6% had moderate QoL. This discrepancy may be explained by differences in the age distribution, sample size, and geographical context of the study. QoL in epileptic patients is influenced by numerous factors, including seizure frequency, which is itself affected by patient compliance, access to antiepileptic drugs, and the quality of medical care. Patients with uncontrolled seizures tend to have significantly lower QoL scores^[39].

Our data showed that age, gender, marital status, and workdays had no significant impact on the overall QoL. This demonstrates the contradictory information about the association between QoL and many sociodemographic factors, including age, education level, marital status, employment status, and some clinical characteristics of epileptic patients^[32]. Additionally, we found that the number of antiepileptic drugs used was not associated with the quality of life score, this is consistent with a previous study which found that the treatment modality had no impact on QoL^[16] and contrasts the other which suggested that the use of polytherapy is correlated with lower QoL^[9].

In previous studies, age has been highlighted as a significant determinant of QoL in epilepsy. For instance, a study in South Korea by Choi-Kwon et al identified age as an important factor influencing QoL^[40]. However, other researches suggest that older individuals may not always experience poorer QoL compared to younger patients^[41,42]. In this study, age was significantly correlated with the physical functioning subscale, aligning with previous findings that older adults are more likely to experience reduced physical capacity, fatigue, and lower energy levels^[41].

Interestingly, our study found that younger patients reported slightly lower QoL scores. This could be attributed to a recent diagnosis of epilepsy combined with challenges in proper medication management. Another study, however, had shown no significant differences in overall QoL between older and younger patients^[43].

The observed association between gender and physical functioning in this study is consistent with findings from previous research. A study conducted in India reported that females generally have worse quality of life compared to males^[44], due to biological and social factors. Women often face a higher burden of physical health issues such as fatigue and musculoskeletal conditions, coupled with societal roles that increase their caregiving responsibilities, which can negatively impact their physical well-being. These disparities highlight the need for gender-sensitive approaches in healthcare to address the unique challenges faced by women and improve their quality of life.

Additionally, the mental health subscale was significantly associated with marital status and the number of outpatient visits in the past month. Married individuals generally report greater life satisfaction and better psychological health, which may be due to the support provided by their spouses in managing their condition^[45]. Outpatient visits often serve as a proxy for the severity of a condition or access to healthcare. Frequent visits may indicate poorer mental health due to chronic health issues or psychological stress related to the condition. Conversely, individuals with fewer or no visits might report better mental health, as they may have less severe conditions or better coping mechanisms. Patients with epilepsy often require frequent and long-term follow-up care, which can significantly impact various aspects of their quality of life domains. Furthermore, a significant correlation was identified between the presence or absence of workdays and the subscales assessing role limitations due to physical health and physical functioning. This may be attributed to the impact of seizures, which can drain energy levels. Even when seizures are fully controlled with medication, side effects such as fatigue or drowsiness can hinder or prevent individuals from carrying out daily tasks effectively.

This study, however, has certain limitations. First, as a cross-sectional study, it lacked a follow-up component, making the results prone to recall bias. Second, important disease-related factors, such as severity, seizure frequency, comorbid psychiatric conditions, and access to treatment, were not examined or controlled for, which may have influenced the reported quality of life outcomes.

Conclusion

Our study concluded that the majority of patients with epilepsy exhibit a moderate to good QoL compared to the general population, which contrasts with findings from other studies. Only a small proportion of patients were identified as being at risk for poor QoL. The highest scores were observed in the physical functioning domain while the general health domain had the lowest score.

Additionally, the study found no significant association between overall QoL scores and socio-demographic or clinical characteristics of epileptic patients. However, a significant relationship was identified between specific socio-demographic and clinical factors and various SF-36 QoL subscales. We recommend implementing culturally appropriate interventions aimed at improving the general health perception among epileptic patients, enhancing access to consistent outpatient care, and addressing gender-specific needs, particularly for women who may experience lower physical functioning. Efforts should also focus on supporting younger patients in managing new diagnoses and treatment plans, as well as promoting employment opportunities for individuals with epilepsy to enhance their physical and social functioning. Additionally, further longitudinal studies are warranted to assess the impact of seizure frequency, treatment adherence, and comorbidities on quality of life and to guide evidence-based policies and clinical practices tailored to the Sudanese context.

Ethical approval

Ethical approval for the study was granted by the Community Medicine Department Review Board at the Faculty of Medicine, University of Khartoum, as part of the graduation thesis process. The research was conducted under the department’s supervision, ensuring adherence to ethical standards throughout all stages of the study. The approval was obtained on 4 September 2021.

Consent

Written informed consent was obtained from all study participants for publication and any accompanying images. A copy of the written consent is available for review by the Editor-in-Chief of this journal on request.

Sources of funding

There was no funding or grant.

Author contributions

D.R.H.A.: conceptualization, investigation, methodology, project administration, writing – original draft, writing – review & editing; N.S.H.E.: formal analysis, validation, visualization, writing – original draft, writing, writing – review & editing; S.A.B.: supervision, investigation, writing – original draft, writing – review & editing; R.H.A.B., S.O.M.E., O.D.M.H.A., L.M.O., R.M., S.E., and A.B.M.A.: investigation, writing – original draft, writing – review & editing.

Conflicts of interest disclosure

The authors declare that they have no competing interests.

Guarantor

Doaa Rabeie Hassan AbdEldaim.

Research registration unique identifying number (UIN)

Not applicable.

Provenance and peer review

Not commissioned, externally peer-reviewed.

Data availability statement

The datasets generated during and/or analyzed during the current study are available from the corresponding author on reasonable request.