Current Pediatric Research

Research Article - Current Pediatric Research (2018) Volume 22, Issue 1

Pattern and prevalence of common pediatric illnesses presenting in a private hospital in Onitsha, south east Nigeria: A comparative analysis.

Chinawa Josephat M*, Aniwada EC, Ugwunna NC, Eze JN, Ndu Ikenna K, Obidike EO

Department of Paediatrics, University of Nigeria Teaching Hospital (UNTH), Enugu State, Nigeria.

Corresponding Author:
Josephat Chinawa
Department of Paediatrics
University of Nigeria Teaching Hospital (UNTH)
Enugu State, Nigeria
Tel: +234 708 662 8572
E-mail: [email protected]

Accepted date: March 26, 2018

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Abstract

Background: Pattern and distribution of common pediatric illnesses are issues often reported in government and teaching hospitals, but very few are reported from private settings. Objective: To determine the pattern and prevalence of common pediatric diseases presenting at a private pediatric specialist hospital. Material and methods: This is a hospital based descriptive cross sectional study of children seen in a private hospital from March 2012-March 2014. In all, 2942 patients were studied as seen. Diagnosis of the pediatric illnesses was made based on painstaking history taking, physical examination and thorough investigations including blood film reports, full blood counts, chest X rays, blood cultures, urine microscopy and cultures when necessary and affordable. Patients were managed according to their diagnoses. Data analysis was done using SPSS version 20. Data was summarized using percentages and comparisons subjected to χ2 analysis with p at <0.05 as significant. These are presented in tables. Results: There were 1636 (55.6%) male patients and 1306 (44.4%) female patients. Most frequent presenting age group were those aged 0-12 months 1424 (48.4%). Malaria was most frequently found pediatric illness 737 (25%) followed by Reactive airway disease (RAD) 529 (18.0%), diarrhea disease 150 (5.1%), Sepsis 66 (2.2%), UTI 58 (2.0%), Pneumonia 22 (0.8%) and URTI 20 (0.7%), a good number were comorbidities and constituted 864 (29.4%) of the presentations. Conclusion: Malaria is the most prevalent illness noted in the study however early and accurate diagnosis of reactive airway disease will help to avert numerous complications that may follow its misdiagnosis and administration of wrong treatment.

Keywords

Common paediatric illnesses, Pattern, Prevalence, Disease.

Introduction

Globally, some milestone has been achieved in reducing mortality in children under 5 years of age [1]. In 2013, there was a good improvement of under 5 mortalities from 12.7 million in 1990 to 6.3 million [1]. It is however painful to know that despite this improvement, the world has failed to achieve the MDG target of a two-thirds reduction in the year 2015 [1]. Studies from most parts of Africa have still shown that infections and other communicable diseases such as malaria, pneumonias, diarrhoeal illnesses are responsible for most hospital admissions [2,3]. On the contrary, non-communicable diseases are more prevalent in developed countries and in adult population [4].

It is pertinent to note that causes of admission vary from one region to another [5]. For instance, while malaria was the commonest cause of admission from a study in a private hospital in Lagos, acute respiratory diseases were commoner in the south-south, though the spectra of constituents of the acute respiratory diseases were not ascertained in the south-south study [5].

In a study of pattern of admissions in hospitals in Hong Kong [7], respiratory disorders constituted 37.5% of all diagnoses, with upper respiratory infections and pneumonia comprising 30.1% and 20.9%, respectively. Furthermore, among all respiratory illnesses, pneumonia, bronchiolitis, rhino sinusitis made up 96.8% of them and these were the findings of other studies [8-11].

This study in a private Pediatric Specialist hospital is important, as it serves the triple roles of a primary health facility as care givers bring their wards on self-referral as well as the roles of secondary and tertiary health facilities as references from hospitals in the town it is situated and surrounding towns come to it. There is no teaching hospital in the town and the available general hospital is often without the services of a paediatrician on ground. The study is different from others because it tends to not only highlight the pattern of common childhood infections but looks critically at seasonal and where important, monthly variations of these diseases and also tries to isolate all the various types of similar diseases.

The study is therefore aimed at identifying various patterns and possible factor influencing different diseases among children who presented in the hospital over a two-year period.

Methods

The study was carried out in a private Paediatric Specialist Hospital in Mkpor, Onitsha, a commercial nerve centre in Anambra state, south east Nigeria. The hospital is situated in the heart of the city and is about 21 km from the capital, Awka. The hospital serves as the main paediatric referral centre for Onitsha residents as well as other neighbouring towns such as Oba, Nnobi, Agulu, Awka, Nibo, Nise, Ihiala and other surrounding towns.

It has a paediatric ward with 10 beds and a new-born service and full complement of nursing services, resident paediatrician and a consultant paediatrician, lab scientist. Most patients attended to be referrals; self, friends and other hospitals. The study was retrospective where all the case notes of patients admitted into the hospital over a two-year period were used.

Data analysis was done on SPSS version 20. Data was summarized using percentages and comparisons subjected to X2 analysis with p at <0.05 as significant. These are presented in tables.

Patients outside the neonatal age (28 days) with common paediatric illnesses and complete data were included in the analysis. Information extracted from the records included age, gender and month of attendance and final diagnosis.

Definition of Some Terms

Reactive airway disease (RAD) is a term most commonly used to describe a person who is wheezing or having a bronchial spasm, but who has not yet been diagnosed with asthma [12]. Its use is generated by the fact that wheezing is quite common in infants, and only about a third of those infants who wheeze ever develops true asthma [12]. Thus, rather than refer to wheezing infants, who may never really be asthmatics, many physicians have used the term "reactive airways" to refer to this group of children [12].

Pneumonia as an infection of the pulmonary parenchyma caused by various aetiologies [13]. It states that pneumonia is not a single disease but a group of specific infections, each with a different epidemiology, pathogenesis, presentation and clinical course. It is usually proven by Chest X ray and definitively by lung juice culture [13].

Upper respiratory infection: An infection of the upper part of the respiratory system which is above the lungs [14]. An upper respiratory infection can be due to any number of viral or bacterial infections [14]. These infections may affect the throat (pharyngitis), nasopharynx (nasopharyngitis), sinuses (sinusitis), larynx (laryngitis), trachea (tracheitis) or bronchi (bronchitis) [14].

Results

Table 1 shows that majority of patients were aged 0-12 months 1424 (48.4%). Slightly higher proportions were equally male 1637 (55.6%). Similar proportion of the diseases occurred in rainy 1505 (51.2%) and dry 1437 (48.8%) seasons

Socio-demographic Characteristics Frequency (n=2942) Percent
Age categories (months)
≤ 12 1424 48.4
13-24 648 22.0
25-36 295 10.0
37-48 160   5.5
49-60 110   3.7
>60 305 10.4
Mean(SD) 14.43(3.55) -
Sex
Male 1637 55.6
Female 1305 44.4
Season
Rainy 1505 51.2
Dry 1437 48.8
Disease/Diagnosis
RAD 529 18.0
Malaria 737 25.0
UTI 58 2.0
Pneumonia 22 0.75
URTI 20 0.65
Diarrhoea/Enteritis 150 5.1
Impetigo 18 0.6
Sepsis/viremia 66 2.2
Coinfection/ comorbidity## 864 29.4
Others 341 11.6
Revisit 137 4.7
Coinfection/comorbidity## 864 29.4
RAD/Malaria 35 1.2
RAD/others 18 0.6
Malaria/Others 811       27.6

Table 1: Socio-demographic characteristics of patients

Table 2 shows that there were statistically significant associations of gender with Malaria (χ2=5.314, p=0.021), Co-Infection (χ2=6.278, p=0.012), but not significant for RAD (χ2=0.870, p=0.351), UTI (χ2=1.301, p=0.254), URTI (χ2=0.260, p=0.610), Pneumonia (χ2=3.338, p=0.068), Diarrhoea/Enteritis (χ2=0.067, p=0.795), Impetigo (χ2=0.219, p=0.639), Sepsis/Viremia (χ2=0.102, p=0.749), Other diseases (χ2=0.443, p=0.506 and Well/ Revisit (χ2=1.033, p=0.310).

Variable Disease No disease χ2 p value
HAD
Male 304 (18.6) 1333 (81.4) 0.870 0.351
Female 225 (17.2) 1080 (82.8) - -
Malaria
Male 437 (26.7) 1200 (73.3) 5.314 0.021
Female 300 (23.0) 1005 (77.0) - -
UTI
Male 28 (1.7) 1609 (98.3) 1.301 0.254
Female 30 (2.3) 1275 (97.7) - -
URTI
Male 10 (0.6) 1627 (99.4) 0.260 0.610
Female 10 (0.8) 1295 (99.2)    
Pneumonia
Male 8 (0.5) 1629 (99.5) 3.338 0.068
Female 14 (1.1) 1291 (98.9) - -
Diarrhoea/Enteritis
Male 85 (5.2) 1552 (94.8) 0.067 0.795
Female 65 (5.0) 1240 (95.0) - -
Impetigo
Male 11 (0.7) 1626 (99.3) 0.219 0.639
Female 7 (0.5) 1298 (99.5) - -
Sepsis/Viremia
Male 38 (2.3) 1599 (97.7) 0.102 0.749
Female 28 (2.1) 1277 (97.9) - -
Co-infection
Male 450 (27.5) 1187 (72.5) 6.278 0.012
Female 414 (31.7) 891 (68.3) - -
Others
Male 184 (11.2) 1453 (88.8) 0.443 0.506
Female 157 (12.0) 1148 (88.0) - -
Well/Revisit
Male 82 (5.0) 1555 (95.0) 1.033 0.310
Female 55 (4.2) 1250 (95.8) - -

Table 2: Associations of sex with diseases

Table 3 shows that there were no statistically significant associations of season with RAD (χ2=0.177, p=0.674), Malaria (χ2=0.000, p=0.999), UTI (χ2=0.124, p=0.724), URTI (χ2=3.607, p=0.058), Pneumonia (χ2=1.382, p=0.240), diarrheal disease/Enteritis (χ2=2.144, p=0.143), Impetigo (χ2=3.217, p=0.073), Sepsis/Viremia (χ2=0.003, p=0.953), Co-Infection (χ2=1.111, p=0.292), Other diseases (χ2=0.079, p=0.779) and Well/Revisit (χ2=3.115, p=0.078).

Variable Disease No disease χ2 p value
HAD
Rainy 275 (18.3) 1230 (81.7) 0.177 0.674
Dry 254 (17.7) 1183 (82.3) - -
Malaria
Rainy 377 (25.0) 1128 (75.0) 0.000 0.999
Dry 360 (25.1) 1077 (74.9) - -
UTI
Rainy 31 (2.1) 1474 (97.9) 0.124 0.724
Dry 27 (1.9) 1410 (98.1) - -
URTI
Rainy 6 (0.3) 1499 (99.7) 3.607 0.058
Dry 14 (1.0) 1423 (99.0) - -
Pneumonia
Rainy 14 (0.9) 1491 (99.1) 1.382 0.240
Dry 8 (0.6) 1429 (99.4) - -
Diarrhoea/Enteritis
Rainy 68 (4.5) 1437 (95.5) 2.144 0.143
Dry 82 (5.7) 1355 (94.3) - -
Impetigo
Rainy 13 (0.9) 1492 (99.1) 3.217 0.073
Dry 5 (0.3) 1432 (99.7)    
Sepsis/Viremia
Rainy 34 (2.3) 1471 (97.7) 0.003 0.953
Dry 32 (2.2) 1405 (97.8) - -
Co-infection
Rainy 455 (30.2) 1050 (69.8) 1.111 0.292
Dry 409 (28.5) 1028 (71.5) - -
Others
Rainy 172 (11.4) 1333 (88.6) 0.079 0.779
Dry 169 (11.8) 1268 (88.2) - -
Well/Revisit
Rainy 60 (4.0) 1445 (96.0) 3.115 0.078
Dry 77 (5.4) 1360 (94.6) - -

Table 3: Associations of season with diseases

Table 4a shows that there were statistically significant associations of age in categories with Malaria (χ2=32.712, p<0.001) and diarrheal disease/Enteritis (χ2=31.682, p<0.001 but not significant for RAD (χ2=4.718, p=0.194), UTI (χ2=4.862, p=0.182), URTI (χ2=3.561, p=0.313), Pneumonia (χ2=6.290, p=0.098) and Impetigo (χ2=1.579, p=0.6641).

Variable Disease No disease χ2 p value
HAD
0-12 278 (9.5) 1146 (90.5) - -
13-36 156 (16.5) 787 (83.5) 4.718 0.194
37-60 47 (17.4) 223 (82.6) - -
>60 48 (15.7) 257 (84.3) - -
Malaria
0-12 298 (20.9) 1126 (79.1) - -
13-36 250 (26.5) 693 (73.5) 32.712 0.000
37-60 88 (32.6) 182 (67.4) - -
>60 101 (33.1) 204 (66.9) - -
UTI
0-12 24 (1.7) 1400 (98.3) - -
13-36 18 (1.9) 925 (98.1) 4.862 0.182
37-60 5 (1.9) 265 (98.1) - -
>60 11 (3.6) 294 (96.4) - -
URTI
0-12 13 (0.9) 1411 (99.1) - -
13-36 5 (0.5) 938 (99.5) 3.561 0.313
37-60 2 (0.7) 268 (99.3) - -
>60 0 (0.0) 305 (100.0) - -
Pneumonia
0-12 6 (0.4) 1418 (99.6) - -
13-36 12 (1.3) 931 (98.7) 6.290 0.098
37-60 1 (0.4) 269 (99.6) - -
>60 3 (1.0) 302 (99.0) - -
Diarrhoea/Enteritis
0-12 104 (7.3) 1320 (92.7) - -
13-36 36 (3.8) 907 (96.2) 31.682 0.000
37-60 7 (2.6) 263 (97.4) - -
>60 3 (1.0) 302 (99.0) - -
Impetigo
0-12 8 (0.6) 1416 (99.4) - -
13-36 6 (0.6) 937 (99.4) 1.579 0.664
37-60 3 (1.1) 267 (98.9) - -
>60 1 (0.3) 304 (99.7) - -

Table 4a: Associations of age in categories with diseases

Table 4b shows that there were statistically significant associations of age in categories with Co-Infection (χ2=23.870, p<0.001) and other diseases (χ2=24.768, p<0.001) but not significant for Sepsis/Viremia (χ2=2.386, p=0.496) and Well/Revisit (χ2=4.147, p=0.246)

Variable Disease No disease χ2 p value
Sepsis/Viremia
0-12 35 (2.5) 1389 (97.5) - -
13-36 23 (2.4) 920 (97.6) 2.386 0.496
37-60 4 (1.5) 266 (98.5) - -
>60 4 (1.3) 301 (98.7) - -
Co-infection
0-12 443 (31.1) 981 (68.9) - -
13-36 295 (31.3) 648 (68.7) 23.870 0.000
37-60 71 (26.3) 199 (73.7) - -
>60 55 (18.0) 250 (82.0) - -
Others
0-12 142 (10.0) 1282 (90.0) - -
13-36 108 (11.5) 835 (88.5) 24.768 0.000
37-60 30 (11.1) 240 (88.9) - -
>60 61 (20.0) 244 (80.0) - -
Well/Revisit
0-12 73 (5.1) 1351 (94.9) - -
13-36 34 (3.6) 909 (96.4) 4.147 0.246
37-60 12 (4.4) 258 (95.6) - -
>60 18 (5.9) 287 (94.1) - -

Table 4b: Associations of age in categories with diseases continued

Table 5 shows comparisons of diseases with similar presentations and that there was statistically significant difference in the proportion of those that had RAD and URTI (516.42, p<0.001), RAD and Pneumonia (510.67, p<0.001), Malaria, diarrheal disease/Enteritis and Sepsis/ Viremia (943.26, p<0.001).

Variable Disease No disease χ2 p value
RAD 529 (18.0) 2433 (82.0) 516.42 0.000
URTI 20 (0.7) 2922 (99.3) - -
RAD 529 (18.0) 2433 (82.0) 510.67 0.000
Pneumonia 22 (0.8) 2920 (99.2) - -
Malaria 737 (25.1) 2205 (74.9) - -
Diarrhoea/Enteritis 150 (5.1) 2792 (94.9) 943.26 0.000
Sepsis/Viremia 66 (2.2) 2876 (97.8) - -

Table 5: Relationship between disease conditions

Though we noted no seasonal variations among the common and serious childhood illnesses, however when commonly occurring diseases were separated in months, we noted that patients who had: RAD were mostly seen in September 68 (12.9) and the cases increased in October to 73 (13.8%): Malaria had bimodal peaks - June 91 (12.3) and November 103 (14.0). Pneumonia, July 3 (13.6%), August 5 (22.7%) and September 3 (13.6%), URTI in January 5 (25.0%) and December 4 (20.0%) and Diarrhoea in January 22 (14.7%) to March 17 (11.3%) (Table 6).

Month Diseases
HAD (n=529) Malaria (n=737) Pneumonia (n=22)
Freq (%) Freq (%) Freq (%)
January 25 (4.7) 64 (8.7) 1 (4.5)
 February 34 (6.4) 45 (6.10 2 (9.1)
March 32 (6.0) 31 (4.2) 2 (9.1)
 April 40 (7.6) 66 (9.0) 0 (0.0)
May 33 (6.2) 59 (8.0) 2 (9.1)
 June 51 (9.6) 91 (12.3) 1 (4.5
July 44 (8.3) 42 (5.7) 3 (13.6)
August 39 (7.4) 49 (6.6) 5 (22.7)
September 68 (12.9) 70 (9.5) 3 (13.6)
October 73 (13.8) 68 (9.2) 1 (4.5)
November 40 (7.6) 103 (14.0) 1 (4.5)
December 50 (0.5) 49 (6.6) 1 (4.5)

Table 6: Distribution of diseases by month

Discussion

Malaria infection is the commonest childhood infection that presented in the hospital with prevalence of 25.1 per cent. It has a male preponderance with no seasonal variation. Elechi et al. [15] noted a similar prevalence of 27% with no association with season. The observed difference is higher than the 12% reported in Tanzania study [16] and 16.9% reported by Oladosu et al. [17] in Lagos. Elechi et al. [15] also noted similar rising age-group specific prevalence as seen in this study. Furthermore, we noted that malaria increases in April and peaks in June and again in September and October and peaks in November.

Several studies have maintained that malaria has a seasonal variation. For instance, Thomson et al. [18] and Ayanlade et al. [19] agree with seasonality of malaria infection. In addition, Molta et al. [20] noted that the relatively dry northern savannah of the country demonstrates strong seasonality in malaria transmission. The results obtained from our study while not showing seasonality however shows monthly clusters that are astride the regular seasons. The reasons for this finding may be environmental and geographical differences and even the attitude and behaviours of the population where these children come from.

Several studies have noted male preponderance in malaria infection which corroborates with our finding [21,22]. This is explained by the fact that during childhood, the extra X-chromosome or absence of Y-chromosome confers inherent survival advantage in females [23]. A second explanation which may be peculiar to the eastern part of Nigeria and some parts of Asia is family male sex preference making it possible for families to seek health care for their male children earlier than for females [23,24]. Similarly, cultural practice of keeping girls indoors to do house chores even at tender ages and allowing the male child unfettered outdoor activity with its attendant exposure to disease may also contribute.

Reactive Airway Disease (RAD) is the next commonest childhood disease that was seen in the study with a prevalence of 18%. Salame et al. [25] noted a whooping prevalence of 99.9%. Though his study was among adult population in a Lebanese community and not a hospital setting. Reactive airway disease is also found to affect less than 15% of children worldwide [26]. There was however low prevalence of RAD (1-3.3%) in the children surveyed in Lucknow, Ludhiana, and Punjab, while in Delhi the prevalence was 11.6% [26]. The reason for this high prevalence could be due to genetic and environmental issues. We however noted no associations with gender but the commonest age of affectation was below 36 months. This is however different from the study of Dileep et al. [26] who noted male preponderance but with a similar age prevalence of 30 months. However, when we looked at the months individually, we noted that RAD had the highest prevalence between September and October though still averagely high in June. Ajay et al. in their study also noted high prevalence of RAD around Monsoon (usually from June to September). Reactive airway disease among children is often a neglected diagnosis among paediatricians and physicians. More often, it is diagnosed as pneumonias and URTIs. When we compared the pattern of RAD with other respiratory diseases, it showed that RAD is the commoner respiratory problem among children in this study and not pneumonias as shown in some other studies [2-4].

Diarrhoeal disease ranks third among common childhood illnesses as seen in this hospital in the years of study with a prevalence of 5.1%. This prevalence is higher among children under 1 year (7.3%) and least among children more than 4 years old (3.6%). Abdur et al. [27] noted a similar overall prevalence of 5.71% among children <5 years old. However, he noted that the highest diarrheal prevalence of 8.62% was found among children aged 12 to 23 months, followed by <1 year old children (6.25%). The lowest prevalence of diarrhoea (3.71%) was found among children aged between 36 and 47 months. Sastrya et al. [28] in Brazil, however, noted a prevalence of 19%. The difference in prevalence rates could be due to methodology issues or could be geographical and cultural. We however noted no seasonal variations in our study.

Diarrhoea prevalence was higher among the males. Some factors found to significantly influence the health care-seeking pattern were age and sex of the children, nutritional score, age and education of mothers, wealth index, and access to electronic media [28,29].

Although rainfall does not appear to have much impact on the relative incidence of diarrhoea, it has been documented that there exists a consistent reduction during July or August and resurgence on January [29]. We noted no seasonal variation in our study. However, when we analysed the monthly pattern of diarrhoea, we noted that diarrhoea occurs mainly between January and March. This agrees with the study of Alexander et al. [30] in Ghana where diarrhoea spans from January to March every year. This finding however negates that of Armah et al. [31] where diarrhoea peaks in two seasons, October to March and July to August. The differences in monthly variation could be due to climatic factors.

Pneumonia and Upper Respiratory Tract Infections (URTI) are the next disease that presented in the hospital at the year of study with frequency of 1.9 and 0.8 per cent. This low prevalence obtained in this study is different from prevalence of 39.1 percent [31] and 33.5 percent [32] obtained from other studies. Lower prevalence of 7% had been obtained in another study [7]. As earlier highlighted, reactive air way disease is often misdiagnosed as URTI or pneumonia thus possibly giving it a spurious prevalence. Correct diagnosis of RAD will indeed give a better picture of prevalence and distribution of Pneumonia. We noted no significant seasonal variations, but when we looked at the months individually, pneumonia usually peaks between July and September though with average prevalence for February, March, May and August. The views of some authors that pneumonia does not occur more in winter or during cold season and opined that most of the specific aetiologies for pneumonia, with the exception of respiratory viruses and Mycoplasma pneumonia, have no seasonal predilection [33] agree with our finding. However, when monthly prevalence is taken into consideration in our study, it would seem that it is in its lowest presentation from October to January. The numbers are however very few for valid conclusions to be made. It is surprising to note in this study that diarrhoea and URTI was seen mainly in the same monthly distribution of January and March. Weather this is a coincidence or if the same strain of viral aetiology is implicated remains conjectural.

There were no age or gender variations in our study. Teshome et al. [32] however noted a male preponderance and common affectation among the under-fives. Lieberman et al. [33] noted a significant seasonal variation with higher rates for all age groups in the winter and spring. Sepsis and Urinary Tract Infections (UTI) had very few contributions as regards frequency of presentation in this study. Majority of our patients however presented as comorbidities with prevalence of 29.4%. The 2.2% prevalence of sepsis obtained in this study is higher than 0.05% and 0.89% prevalence obtained by Tatsuya and Hartman [34,35]. The reason for the small prevalence rates in our study bothers so much on diagnostic approach used. The use of SIRS with clinical evidence of infection alone to make a diagnosis of sepsis still remains debatable when compared with actual isolation of organism by culture.

The prevalence of 2% obtained in our study on UTI is so small when compared with other studies. For instance, Shaik et al. [36] in his meta-analysis obtained a pooled prevalence of UTI as 7.0%. The pooled prevalence rates of febrile UTIs in females aged 0-3 months, 3-6 months, 6-12 months and >12 months was 7.5%, 5.7%, 8.3% and 2.1%, respectively. We noted no link between UTI and age, gender or seasons.

Our UTI cases were not as a consequence of purposeful study but were from cases where malaria treatment had seemed to have failed or where there are symptoms suggesting UTI. This could also have affected the prevalence. Majority of our patients however presented as comorbidity with prevalence of 29.4%.

Conclusion

Malaria is the most prevalent illness noted in the study however early and accurate diagnosis of reactive airway disease will help to avert numerous complications that may follow its misdiagnosis and administration of wrong treatment.

Limitation of the Study

This study will be better improved if we compare our findings with what is obtainable in a teaching hospital in a stance.

Acknowledgement

We acknowledge those in medical records for providing all information needed.

Ethical Clearance

This was sought from the Ethics Committee of the University of Nigeria Teaching Hospital, Enugu.

Author Contributions

EKO conceived and revised the article, JMC help in the write up of the article. EA analysed the data. All the author read and edited the write up.

References