Atherogenic indices in preeclamptic and eclamptic patients in North-Central Nigeria

Abstract

Microvascular, placental, haematological and lipid studies suggest striking similarities between preeclampsia/eclampsia and atherosclerosis.

Objective

To determine the lipid profile and atherogenic indices in preeclamptic/eclamptic patients and compare with normal pregnant women.

Methodology

Comparative cross-sectional study conducted in North Central Nigeria. The study population was preeclamptic/eclamptic patients and normal pregnant women. A total of 192 women, comprising 96 pregnant women with preeclampsia/eclampsia and an equal number of normotensive controls were recruited consecutively by purposive sampling. Lipid profiles were estimated and atherogenic indices were calculated.

Result

Coronary heart disease risk ratio (CRR) and atherogenic index of plasma (AIP) showed significantly increased atherogenic potentials in subjects compared to controls. Mean ± SD CRR of subjects was 0.28 ± 0.17, Mean ± SD CRR of controls was 0.44 ± 0.24 (p = 0.001); Mean ± SD AIP of subjects was 0.32 ± 0.42 and mean ± SD AIP of controls was 0.16 ± 0.26 (p = 0.003).

Conclusion

Atherogenic indices show increased atherogenic potentials in preeclamptic/eclamptics.

Keywords

Hyperlipidemia atherogenic indices preeclampsia eclampsia

Introduction

Hypertensive disorders in pregnancy are a major cause of maternal and perinatal morbidity and mortality.^1–3 Globally, preeclampsia occurs in about 5–10% of all pregnancies.^1,2,4,5 In the United States, preeclampsia occurs in 5–7% of pregnancies annually and accounts for 18% of maternal deaths.⁵ Rates from several African countries vary from 1.8% to 7.1%.^4,6 In Nigeria, the reported prevalence ranges between 2% and 16.7%.^4,6–9

The occurrence of eclampsia is a reflection of the availability, utilization, and effectiveness of maternity care. In most of Western Europe and North America, the incidence is 2–3 per 10,000 deliveries compared to 13 per 1000 deliveries in developing countries.^1,5,10

Preeclampsia and eclampsia together contribute about 13% to the overall maternal mortality rate with high perinatal morbidity and mortality rates.^4–13

Preeclampsia is defined as systolic blood pressure of 140 mmHg or higher and/or diastolic blood pressure of 90 mmHg or higher measured on at least two different occasions, 4–6 h apart, occurring after 20 weeks of gestation in a woman whose blood pressure has previously been normal with proteinuria of 0.3 g or more in a 24-h urine specimen.^14,15 Eclampsia is the onset of generalized tonic-clonic convulsions in a woman with preeclampsia during pregnancy, labour or within 7 days of delivery that cannot be attributed to epilepsy or other convulsive disorders.^1–3,14,15

Studies have linked preeclampsia with the development of maternal cardiovascular disease later in life.^16–18 This could be a result of similar pathophysiology in them, which includes endothelial dysfunction, inflammatory response, metabolic syndrome and hypercoagulability. Significantly elevated low-density lipoprotein (LDL) and triglycerides are known to be particularly atherogenic and have been described in patients with coronary heart disease and women with preeclampsia.^16–18

Several studies have shown complex changes in lipid metabolism during normal pregnancy.^19–21 These changes are not considered atherogenic, and are believed to be under hormonal control. In pregnancies complicated by preeclampsia however, there is a disruption in the normal physiologic hyperlipidaemia evident by significantly elevated serum lipids.^19–21 Pregnancy is characterised by several changes including increased lipogenesis, lipolysis with resultant synthesis of very low-density lipoproteins (VLDL) and triglycerides, increase in hepatic lipase activity and decrease in lipoprotein lipase activity, which causes VLDL to remain in circulation longer leading to the accumulation of LDL.^19–23

A review of histological changes in spiral arteries of women with preeclampsia revealed characteristic atherosclerotic plaques, which is due to oxidized LDL taken up preferentially by macrophages to form lipid-laden macrophages or foam cells.^1–3

Pre-eclampsia and atherosclerosis have both been associated with dyslipidemia, endothelial dysfunction, and an increase in the circulating levels of pro-inflammatory cytokines, such as interleukin-6 and tumour necrosis factor-α.^19–28 The mechanisms involved in the induction of endothelial cell dysfunction are poorly understood. The relative placental ischemia has been associated with the production of reactive oxygen free radicals, raised oxidative stress, and hence uncontrolled lipid peroxidation.^{1–3,27–30} It also causes the production of toxic metabolites especially reactive aldehydes such as malondialdehyde, capable of causing widespread endothelial damage.^{1–3,27–30}

Evidence evaluating the contribution of each lipid parameter has been conflicting and there may be difficulty in interpreting the significance of each elevated lipid parameter.^27–31 This led to the use of lipid ratios, which calculate the true atherogenic potentials, and this is a more reliable and reproducible tool in predicting the development and outcome of the disease. Ratios such as atherogenic index of plasma (AIP),^29,31–33 coronary heart disease risk ratio (CRR) are strong markers in predicting the risk of atherosclerosis and coronary heart disease and they reflect the true relationship between protective and atherogenic lipoprotein.^32,33

Other indices developed include: atherogenic coefficient (AC), Castelli's risk Index-I (CRI-I), and Castelli’s risk Index-II (CRI-II).^29,32,33

This pathology is currently inadequately explored in developing countries that paradoxically bear the greatest disease burden. The contentious possible relationship between increased atherogenic potentials and gestational proteinuric hypertension forms the justification for this study. This study seeks to describe the relationship between increased atherogenic potentials and gestational proteinuric hypertension, and if present, to determine its contribution to disease severity and outcome.

Materials and method

This was a comparative cross-sectional study conducted over six months at the Obstetrics and Gynaecology Emergency Unit and the antenatal clinics of the University of Ilorin Teaching Hospital (UITH), Nigeria after obtaining ethical approval from the same institution.

The study population for the cases consisted of all women admitted into the Obstetric unit with a diagnosis of preeclampsia/eclampsia. The controls were healthy pregnant women who attended the antenatal clinic at the same hospital, whose age, gestational age, and BMI matched with the recruited subjects. Patients excluded from the study were those with chronic hypertension, diabetes, renal disease, autoimmune disorders, women who used lipid-lowering drugs (statins, fibrates, cholestyramine) in the preceding 1 year, obese patients with BMI >30 kg/m², pregnancy non-proteinuric hypertension and pregnancy below 20 weeks of gestation.

A sample size of 96 participants in each study group was determined by Andrew-Fischer's formula,³⁴ and they were recruited consecutively by purposive nonprobability sampling.

A case of preeclampsia was defined as hypertension (blood pressure ≥140/90 mmHg measured on two occasions at least 4 h apart), or a single systolic reading ≥ 160 mmHg or single diastolic reading ≥110 mmHg, with significant proteinuria of > 300 mg in the 24-h urine sample or ++ or more on urine dipstick that occurs after 20 weeks of gestation in a previously normotensive and non-proteinuric woman.^1–4

Severe preeclampsia was defined as systolic blood pressure ≥ 160 mmHg or diastolic blood pressure ≥ 110 mmHg with proteinuria of > 5 g in a 24-h urine sample, or presence of headache, dizziness, blurring of vision, epigastric pains, jaundice, bleeding diathesis, severe anaemia, HELLP syndrome, pulmonary edema.^1–4

Eclampsia was defined as the onset of generalized tonic-clonic convulsions in a woman with preeclampsia that cannot be attributed to other causes.^1–4

Approval for the study was obtained from the University of Ilorin Teaching Hospital Ethical Review Committee and the study was conducted according to the World Medical Association Helsinki Declaration.

Patients who satisfied the inclusion criteria were approached and counselled and informed consent was obtained. A copy of the consent form was given to patients who wished to participate in the study for their perusal and signature/thumb printing. For unconscious patients, the counselling was to the attending relative preferably the husband, who signed on their behalf. A pre-tested questionnaire was administered to the patient/relative by the investigator or assistants who had received appropriate training on the study protocol. Information was collected on age, social class, parity, gestational age of pregnancy, weight, height, and BMI. A general physical examination for oedema, anaemia, jaundice, and petechial haemorrhages was done on each patient followed by systemic examination using the data collection tool. Blood pressure was measured using a mercury sphygmomanometer, using the standard protocol.^14,15

A volume of 5 ml of venous blood was collected from a prominent vein on the dorsum of the hand. The blood sample collected was centrifuged in a benchtop centrifuge at 3000 rpm for 3 min. The serum obtained was transferred into another plain bottle and stored at −20 °C until analyzed. Non-fasting samples were used in all participants as previous studies done did not find significant differences in the parameters in both fasting and non-fasting samples.^35,36 The non-fasting state predominates in most of a 24-h cycle and better reflects the true atherogenic lipoprotein levels, hence, newer recommendations are to sample in the non-fasting state.^35,36 Additionally for this particular study, it is almost impractical to get a 6–8 h of fasting uniformly from all the pregnant women, and admission for severe preeclampsia/eclampsia occur as emergencies.

The serum was analyzed for total serum cholesterol, triglycerides, LDL cholesterol, and high-density lipoprotein (HDL) cholesterol using MAPADA® Spectrophotometer (Shanghai Mapada, 2012) and total cholesterol assay kit (fluorometric).

The CRR and the AIP were calculated using the formula: HDL/TC (Inverse Castelli index); and Log (TG/HDL-C) respectively.^31–33

The inverse ratio used in this study has been found to have identical predictive values although in the reverse order while emphasizing the HDL (Protective) component as a proportion.^32,33

Dangerous CRR is <0.12; high CRR is 0.12–0.18; average CRR is 0.19–0.27; while values ≥ 0.28 are considered below average risk.³² AIP values above 0.24 are associated with high cardiovascular risk, values under 0.11 are associated with low risk of CVD; while values between 0.11 and 0.21 are associated with intermediate risks.³¹

Data was analyzed using the statistical package for social sciences software SPSS (version 20, 2011, SPSS Inc., Chicago, Illinois). Data collected on the proforma was entered into a master sheet using numerical codes. The adequacy of matching of subjects and controls was verified using comparisons of age, gestational age, and BMI between both groups for statistical significance. Frequency distribution tables and cross-tabulation of variables were generated. Measures of central tendency and dispersion of quantitative variables such as mean, median, standard deviation, and interquartile range, as well as the proportion for qualitative variables, were also determined. A thematic approach was used to analyse some qualitative variables such as disease severity. The chi-square and student t-tests were used to identify significant differences between categorical and continuous variables respectively. Data were subjected to the analysis of variance test to identify significance where more than two continuous variables are being compared. Yates correction and Fischer's exact tests were used as appropriate. The correlation coefficient was used to show a linear association between relevant variables. Logistic regression models were used to define significant associations between relevant variables. Variables that were statistically significant on a univariate analysis were plugged into the relevant regression model and odd's ratio (95% CI) and Beta (β) coefficient were described. A p-value of <0.05 was considered significant.

Results

One hundred and ninety-two pregnant women met the inclusion criteria, consisting of 96 pregnant women with preeclampsia/eclampsia and an equal number of pregnant women without preeclampsia/eclampsia as controls. The socio-demographic characteristics of the subjects are as depicted in Table 1. The mean age of the subjects was 29.07 ± 5.74 while that of the controls was 29.40 ± 5.84. Almost all the subjects were married, majority of the study participants were Yoruba, 65 (67.7%) of the subjects had attained tertiary education while of the controls, 73 (76.0%) had tertiary education (χ2 = 8.06, p = 0.045). In terms of occupational distribution, 47.9% of the subjects and 36 (37.5%) of the controls are employed as skilled professionals.

Table 1.

Socio-demographic characteristics of subjects and controls.

Characteristics	Subjects (n = 96)	Controls (n = 96)	t/χ2	p-value
Age (years)	n (%)	n (%)
≤ 19	4 (4.2)	4 (4.2)	0.000	1.000
20–24	23 (24.0)	23 (24.0)
25–29	18 (18.8)	18 (18.8)
30–34	33 (34.4)	33 (34.4)
≥ 35	18 (18.8)	18 (18.8)
Mean ± SD age (years)	29.07 ± 5.74	29.40 ± 5.84	−0.386	0.700
Marital status
Single	0 (0.0)	1 (1.0)	1.005	0.999*
Married	96 (100.0)	95 (99.0)
Ethnicity
Yoruba	80 (83.3)	83 (86.5)	2.228	0.328
Ibo	9 (9.4)	4 (4.2)
Others	7 (7.3)	9 (9.4)
Education
None	0 (0.0)	3 (3.1)	8.060	0.045
Primary	1 (1.0)	3 (3.1)
Secondary	30 (31.2)	17 (17.7)
Tertiary	65 (67.7)	73 (76.0)
Occupation
Professionals	1 (1.04)	6 (6.3)	10.06	0.039
Non-academic professionals	46 (47.9)	36 (37.5)
Non-manual skilled workers	10 (10.4)	14 (14.6)
Manual skilled workers	14 (14.6)	24 (25.0)
Unemployed	25 (26.0)	16 (16.7)

χ2: Chi square, SD: standard deviation; *: Fisher's exact.

Of the cases, 25% did not receive any antenatal care in the index pregnancy (unbooked), and 15.6% had a previous history of preeclampsia/eclampsia

The mean ± SD systolic blood pressure of the subjects was significantly higher at 172.7 ± 12.94 mmHg compared to 113.1 ± 13.00 mmHg among the controls (p = 0.001). Similarly, the mean ± SD diastolic pressure was significantly higher among subjects than controls (p = 0.001)

Significant proteinuria (2 + or more) was present in all subjects and absent in all controls (p = 0.001).

Clinical characteristics of the study population

The common symptoms were: headache (76.0%), blurred vision (46.9%) and dizziness (29.2%). Others were as shown in Figure 1.

Figure 1.

Symptoms at presentation among subjects.

Disease severity among subjects

Regarding severity of preeclampsia/eclampsia, 8 (8.3%) had mild preeclampsia, 78 (81.3%) had severe preeclampsia and 10 (10.4%) had eclampsia as shown in Figure 2, and analysis shows that there was no statistically significant difference in the distribution of gestational age groups across the three disease severity groups (p = 0.886).

Figure 2.

Distribution of cases by severity.

All patients with mild preeclampsia received regular antenatal care (booked), compared to 62 (79.5%) of those with severe preeclampsia and none of those with eclampsia (p = 0.001). Almost all the women with eclampsia were primigravidae (90.0%), compared to 27 (34.6%) of those with severe preeclampsia and two (25.0%) of mothers with mild preeclampsia. These differences were statistically significant (p = 0.012).

Lipid samples were taken at the point of diagnosis in all the cases, and the gestational ages at the point of sample collection was matched with normotensive pregnant women from the antenatal clinic. Ten participants (five subjects and five controls who were matched for age, gestational age and BMI) had sampling done at less than 28 weeks gestational age, 63 participants in each study arm had blood sampling done at 28 to 36 weeks gestational age and 28 participants in each study arm had blood sampling done beyond 36 weeks gestational age.

Table 2 shows the mean values for the individual lipid parameters. The difference in serum triglyceride levels was statistically significant (p = 0.013). Similarly, mean serum HDL cholesterol was significantly lower among subjects than the controls (p = 0.001).

Table 2.

Serum lipid profile among pre-eclamptic and normotensive women.

Serum lipids	Subjects	Controls	t	p-value
Total cholesterol (mmol/L)	4.79 ± 1.46	4.69 ± 2.05	0.423	0.673
Triglycerides (mmol/L)	2.41 ± 0.92	2.74 ± 0.92	−2.51	0.013
HDL cholesterol (mmol/L)	1.27 ± 0.71	1.73 ± 0.73	−4.48	0.001
LDL cholesterol (mmol/L)	2.85 ± 1.32	2.83 ± 1.48	0.10	0.917

Table 3 shows the mean ± SD CRR was lower among the subjects compared to the controls (p = 0.001). Similarly, the AIP was significantly higher among the subjects compared to the controls (p = 0.003).

Table 3.

Atherogenic indices among pre-eclamptic/eclamptics and normotensive pregnant women.

Serum lipids	Subjects	Controls	t	p-value
Serum lipids	(n = 96)	(n = 96)	t	p-value
Coronary heart disease risk ratio
Mean ± SD	0.28 ± 0.17	0.44 ± 0.24	−5.33	0.001
Range	0.02–0.73	0.11–1.19
Atherogenic index
Mean ± SD	0.32 ± 0.42	0.16 ± 0.26	3.03	0.003
Range	−0.37–1.57	−0.32–0.87

Categorizing the subjects and controls based on CRR into four risk groups, 18 (18.8%) and 17 (17.7%) of the subjects belonged to dangerous and high CHD risk groups respectively compared to four (4.2%) and four (4.2%) belonging to the same groups respectively among the controls. The difference in the distribution of the subjects and controls across the CHD risk groups was statistically significant (p = 0.001). Similarly, the categories of risk assigned based on AIP are as shown in Table 4.

Table 4.

Coronary heart disease risk ratio/atherogenic index of plasma risk groups among preeclamptics/eclamptics and normotensive pregnant women.

Parameters	Subjects N = 96 (%)	Control N = 96 (%)	χ2	p-value
Coronary heart disease risk ratio groups
– Dangerous CHD risk	17 (17.7)	4 (4.2)	23.13	0.001
– High CHD risk	18 (18.8)	4 (4.2)
– Average CHD risk	19 (19.8)	20 (20.8)
– Below average	42 (43.8)	68 (70.8)
Atherogenic index of plasma risk groups
– High cardiovascular risk	48 (50.0)	35 (36.5)	4.23	0.121
– Intermediate cardiovascular risk	9 (9.4)	8 (8.3)
– Low cardiovascular risk	39 (40.6)	53 (55.2)

A majority of the subjects (50.0%) belonged to the high cardiovascular risk group while a majority of the controls (55.2%) belongs to the low cardiovascular risk group, however this difference in distribution was not statistically significant as shown in Table 4 (p = 0.121).

A multinomial logistic regression model with CRR categories as the dependent parameter and the parameters (age, gestational age, BMI, weight, parity, and being a subject or control) is shown in Table 5. The model tested the listed parameters to determine their influence in increasing or reducing the odds of a pregnant woman being in either of the CRR categories. The low CHD risk CRR category was the reference category against which the other CRR categories were compared. The model was statistically significant (p = 0.003) with pseudo-R2 (Nagelkerke) of 0.20 indicating the model explained 20.0% of the variance of the dependent variable. Having preeclampsia/eclampsia increased the odds of belonging to the dangerous risk CRR category (OR, 95% CI 6.77, 2.08–22.01) and the high risk category (OR, 95% CI 7.24, 2.28–22.96). None of the other parameters significantly influenced the odds of belonging to any of the CRR categories (Table 5).

Table 5.

Multinomial logistic regression analysis of coronary heart disease risk categories and selected clinical parameters.

Categories^a	Parameters	B	OR(95% CI)	p
Dangerous risk	Age	−0.06	0.94 (0.84–1.06)	0.311
	Gestational age	0.17	1.18 (0.99–1.40)	0.056
	BMI	0.02	1.02 (0.90–1.15)	0.800
	Weight	0.03	1.03 (0.95–1.12)	0.422
	Parity	0.28	1.32 (0.85–2.05)	0.220
	Subject	1.91	6.77 (2.08–22.01)	0.001
High risk	Age	−0.03	0.97 (0.87–1.08)	0.588
	Gestational age	0.07	1.08 (0.93–1.25)`	0.345
	Body mass index	0.01	1.01 (0.89–1.14)	0.902
	Weight	−0.01	0.99 (0.92–1.08)	0.852
	Parity	0.15	1.16 (0.75–1.80)	0.501
	Subject	1.98	7.24 (2.28–22.96)	0.001
Average risk	Age	0.07	1.07 (0.98–1.16)	0.128
	Gestational age	0.05	1.05 (0.93–1.18)	0.425
	Body mass index	−0.04	0.97 (0.88–1.06)	0.441
	Weight	0.03	1.03 (0.96–1.10)	0.409
	Parity	−0.18	0.84 (0.57–1.24)	0.374
	Subject^b	0.44	1.55 (0.73–3.26)	0.252

Below average risk category was the reference category.

Subject compared to control.

A multinomial logistic regression model with AIP risk categories as the dependent parameter and the parameters (age, gestational age, BMI, weight, parity and being a subject or control) as independent variables. The model tested the listed parameters to determine their influence in increasing or reducing the odds of a pregnant woman being in either of the AIP defined cardiovascular risk categories. The low cardiovascular risk AIP category was the reference category against which the other AIP defined cardiovascular risk categories were compared. The model is statistically significant (p = 0.001) with pseudo-R2 (Nagelkerke) of 0.38 indicating the model explained 38.0% of the variance of the dependent variable. Weight (OR, 95% CI 0.92, 0.86–0.98), BMI (OR, 95%CI 1.38, 1.25–1.53) and having preeclampsia/ eclampsia (OR, 95% CI 2.42, 1.17–4.99) significantly influenced the odds of being categorized into the high cardiovascular risk category compared to the low risk.

Discussion

Preeclampsia/eclampsia remains one of the three most important causes of maternal and perinatal morbidity and mortality contributing to 13% of maternal mortality in Nigeria.^4,6–9 Studies have implicated elevated maternal serum lipid, atherosclerotic changes and endothelial damage, either as primary etiologic factors or as a consequence of disease process.^{1–3,20–22}

The mean age of women with preeclampsia/eclampsia in this study of 29.07 ± 5.74 is similar to the mean age found in other studies.^4,6,7 This is a reflection of the peak age of these disorders in Nigerian pregnant women.^4,6,7

The mean BMI in the subjects and controls were 21.57 ± 4.69 and 21.75 ± 4.43 respectively, and there was no significant difference between the two groups, which is in agreement with previous studies done.³⁷ This also ensures that BMI which is a major confounder would not be a source of heterogeneity.

Preeclampsia/eclampsia is most common among primigravidae in this study, which is consistent with findings from other studies.^4,6–9

A larger proportion of the subjects in this study (81%) had severe preeclampsia. This is in keeping with earlier works done by Akaba et al., Awoyesuku et al. and Onoh et al.^4,7,8 Considering the recognized limitations of interpreting lipid profile values, the atherogenic indices of CRR and AIP provide an accurate and reliable summary measure of the tendency to acute atherosis.^29,31–33 In the current study, the CRR (HDL/total cholesterol) among subjects was lower than controls. A lower CRR indicates increased atherogenic potential of blood.^29,31–33 The heightened risk for arteriosclerosis found in this study is similar to some reports.^31,38,39 The imbalance of increased atherogenic potential and reduced protective potential exemplified by a reduction in the inverse Castelli ratio (HDL/total cholesterol) used in this study supports the theory of atherosis in the placental bed being contributory to the occurrence of the syndrome of preeclampsia.^29,31–33 This inverse ratio has been found to have identical predictive values although in the reverse order while emphasizing the HDL (Protective) component.^32,33

The AIP values, on the other hand, bears a direct relationship with the risk for atherosis.³¹ The AIP values were elevated in the subjects compared to the controls, which is similar to findings from other studies.^31,39 The AIP, as an indicator, may be an improvement over CRR as it incorporates serum triglycerides which have been predominantly implicated in preeclampsia.³¹

Compared to being normotensive, preeclamptic pregnant women have a 6.8 (odds ratio = 6.77, 95% confidence interval = 2.08–22.01) fold increase in odds of being in the dangerous CRR category (CRR < 0.12). The odds of being preeclamptic are also increased for mothers in the high CRR group in the current study (odds ratio = 7.24, 95% confidence interval = 2.28–22.96). Singh et al.³⁹ reported similar findings in which belonging to the dangerous risk category increased the odds of being preeclamptic by 5.8 fold (odds ratio 5.785, 95% confidence interval = 2.400–13.945). Aksonova et al. reported similar findings.³² This strongly supports the theory of dyslipidemia playing a role in preeclampsia.

A similar relationship was demonstrated with AIP in the current study in which having preeclampsia/eclampsia and higher BMI are associated with increased odds of being in the high cardiovascular risk categories. Singh et al.³⁹ reported similar findings in their study. This supports the above assertion of dyslipidemia playing a role either as a cause or consequence of preeclampsia. Considering several longitudinal studies have shown that increased lipid levels in the first trimester predict subsequent occurrence of preeclampsia, it does suggest a causative role.^19,20 There will be a need for further research to clarify the significance of these findings.

Conclusion

CRR and AIP show significantly increased atherogenic potentials in the subjects compared to the normotensive controls.

Study limitations

The limitation to this study is the inability to do serial assessment of lipid parameters in order to fully establish a possible longitudinal relationship between hyperlipidaemia and disease occurrence and progression.

Footnotes

Acknowledgements

We would like to thank Dr Abdulkadir MB, Dr Biliaminu SA, of University of Ilorin Teaching Hospital, for their immense contributions towards the completion of the project and data analysis.

Contributorship

Dr Abdulkadir ZA and Dr Adebara IO researched the literature and conceived the study. Prof Ijaiya MA was involved in protocol development and gaining ethical approval. Dr Abdulkadir ZA and Dr Adebara IO conducted patient recruitment and data analysis. Dr Abdulkadir ZA wrote the first draft of the manuscript. Prof Ijaiya and Dr Adebara IO reviewed and edited the manuscript and approved the final version of the manuscript.

Declaration of conflicting interests

The authors declared no potential conflicts of interest with respect to the research, authorship, and/or publication of this article.

Ethical approval

Full ethical approval was granted by the institution's IRB prior to commencement of the study.

Funding

The authors received no financial support for the research, authorship, and/or publication of this article.

Guarantor

Dr ZA Abdulkadir.

Informed consent

Written informed consent was sought from each subject in this study.

ORCID iD

Zainab Ajoke Abdulkadir

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