INTRODUCTION:

HIV/AIDS has killed more than 25 million people since it was discovered in 1981 making it one of the most destructive epidemics in recorded history (UNAIDS Report, 2006). The total number of people living with HIV/AIDS is an estimated 40.3 million (UNAIDS/WHO, 2005) with majority of them living in the developing world (World Wide HIV/AIDS Epidemic Statistics, 2006). HIV infection in Cameroon has progressively risen from 0.4% in 1992 to about 1.2% in 1990 (Garcia – Calleja et al, 1992) and from 4% in 1992 to about 7% in 1997 to 11% in 2000 (Sentinel Surveillance, 2000) and in 2004 it stood at 5.5% (Institute Nationale de la Statistique Enquete, 2004).

This shows a steady rise in the prevalence in Cameroon. HIV causes progressive impairment of the body’s cellular immune system leading to increased susceptibility to tumors and the fatal conditions known as acquired immunodeficiency syndrome (AIDS) (Cheesbrough, 2007). Patients with HIV are prone to develop a wide range of infections during their lifetime due to progressive decline in immune response. These infections are called ‘opportunistic infections’ (OIs) (Kanabus et al, 2006). Opportunistic infections therefore constitute a major cause of mortality and morbidity in patients living with HIV (Iroezindu et al, 2013). Prevention of such opportunistic infections, early identification for those presenting with opportunistic infections as well as identifying the risk factors for opportunistic infections is compelling. This study therefore evaluated the occurrence and risk factors opportunistic infections in HIV patients attending the Bamenda Regional hospital, Cameroon.

MATERIALS AND METHODS:

Study Area:

This descriptive cross – sectional hospital based design was conducted at the Bamenda Regional hospital located in the North West Region of Cameroon. This hospital acts as a referral hospital in the region with a well – constructed and functional Day hospital for HIV infected in – patient management.

Study Population:

160 HIV patients attending the Bamenda regional hospital were selected using a systematic sampling technique.

Data Collection:

A structured questionnaire and an observational guide were used to collect data on socio – demographic, clinical, laboratory findings and risk factors. For each participant, detailed history and physical examinations were carried out to identify features suggestive of OIs. Depending on the clinical diagnosis of OI made, appropriate investigations such as sputum acid fast bacilli (AFB), chest x – ray, cerebrospinal fluid analysis and stool microscopy were carried out by the laboratory technician to confirm the diagnosis where possible. The laboratory results were captured as soon as they were available.

Criteria for diagnosing OIs:

The diagnosis of OIs was made according to standard guidelines and were confirmed by physicians involved in HIV care and management.

Kaposi’s sarcoma was diagnosed on clinical grounds evidenced by hyper – pigmented or nodule skin lesions.

Herpes zoster was detected by the presence of painful skin eruptions with dermatomal distribution.

Oral candidiasis was detected by direct observation of the oral cavity showing redness and inflammation of the mucosa with or without patches of white plaques as well as difficulty in swallowing.

Fungal nail infection was diagnosed based on clinical grounds.

Cryptococcal meningitis was diagnosed based on clinical evidence of meningitis with demonstration of cryptococcal yeast cells in the cerebrospinal fluid by Indian ink staining.

Cytomegalovirus was diagnosed clinically from retinitis.

Cerebral toxoplasmosis was detected from signs and symptoms of fever, headaches, confusion or altered mental status.

Pulmonary tuberculosis (TB) was diagnosed after patient had verbalized one of the three screening symptoms of coughing, night sweat and fever for 3 weeks and the demonstration of acid fast bacilli in two or more sputum samples and/or chest x – ray features compatible with TB.

Infective diarrhea greater than one month was diagnosed by patient’s verbalization.

Data Analysis:

Data obtained was analyzed using SPSS version 17.0 and results represented in tables and figures.

Ethical considerations:

Authorization for this research was obtained from the Regional Delegation of Public Health for the North West Region of Cameroon (Reference №: 331/NWR/RDPH/CEA -3). The importance of the study was explained to the participants and participation was voluntary. Full confidentiality and participant’s rights were maintained.

RESULTS AND DISCUSSION:

Demography of the patients living with HIV/AIDS:

Out of the 160 patients, majority were in the age range of 33 – 50 years (80.0%) with a mean age of 41.1 ± 11 years. This is comparable to the mean age of 41.1 ± 10 years reported by Iroezindu et al (2013). There were 53 males (33.1%) and 107 females (66.9%) with a male: female ratio of 1: 2. This is similar to the report by the African Region Gender Team in 2000 who found that in Cameroon, more women are infected with HIV/AIDS than men. Also, Jude and Gloria in 2007 stated in their review at the policy level in Cameroon, the government of Cameroon has drawn up plans to reduce the high prevalence of HIV/AIDS amongst women. In this study, most of the participants were married (48.1%) and majority of them had secondary level of education (43.1%). This is in line with the study of Iroezindu et al (2013) who reported that 59.3% of the people living with HIV/AIDS in their study were married but however reported a higher percent of participants with secondary level of education (73.1%). Most of the participants in our study were employed (73.7%) compared to the 26.3% that were unemployed.

Table 1: Demographic characteristic of the people living with HIV/AIDS

Age range (in years)

15 – 32

33 – 50

51 – 68

25 (15.6)

128 (80.0)

7 (4.4)

Sex

Male

Female

53 (33.1)

107 (66.9)

Marital status

Single

Married

Divorced

Widow/widower

45 (28.1)

77 (48.1)

12 (7.5)

26 (16.3)

Level of education

No formal education

Primary

Secondary

Tertiary

8 (5.0)

65 (40.6)

69 (43.1)

18 (11.3)

Occupation

Unemployed

Employed

42 (26.3)

118 (73.7)

Prevalence of opportunistic infections amongst people living with HIV/AIDS:

The prevalence and the number of opportunistic infections amongst people living with HIV/AIDS are shown on figure 2 and 3. Out of the 160 patients, 83 were diagnosed of opportunistic infections giving a prevalence of 51.9%. This is comparable to the 57 – 69% prevalence of opportunistic infection previously reported in HAART – naïve HIV infected patients in Nigeria (Salami et al, 2006; Saidu et al, 2009; Daniyam et al, 2011). The prevalence observed in this study is however lower than the 88.9% reported by Bayeh et al (2010) but higher than the 22.4% reported by Iroezindu et al (2013) and the 30% reported by Srirangaraj and Venkatesha (2011). These differences could be attributed to difference in HIV stage and the sample size. There were a total of 121 opportunistic infections diagnosed in the 83 patients. Eighty three (68.6%) had single opportunistic infection, 29 (24.0%) had dual opportunistic infections, 8(6.6%) had triple opportunistic infections while one (0.8%) had greater than four opportunistic infections.

Figure 1: Prevalence of opportunistic infections amongst people living with HIV/AIDS

Figure 2: Distribution of the number of opportunistic Infections occurring in people living with HIV/AIDS

Common opportunistic infections in people living with HIV/AIDS:

The common opportunistic infections observed in this study were categorized into four groups; fungal, protozoal, viral and bacterial. The most common observed was protozoal infection (37.2%) while viral, fungal and bacterial had the following occurrence 23.1%, 20.7% and 19.0% respectively (figure 3). Overall, the most frequent opportunistic infections seen in the patients were infective diarrhea greater than one month (32.2%), oesophageal candidiasis (16.5%), tuberculosis (16.5%) and Herpes zoster virus (14.9%). Similar findings were also observed in other studies Sun et al (2006); Mzileni et al (2008); Iroezindu et al (2013). However, Moges and Kassa (2014) reported that this spectrum might be because their diagnosis is relatively easy to identify from patients than other opportunistic infections. It is worth mentioning that unlike most of the studies above, tuberculosis was not the commonest opportunistic infection amongst patients in this study despite the well - known high burden of tuberculosis in most developing countries.

Figure 3: Categories of Opportunistic infections amongst people living with HIV/AIDS

Figure 4: Common Opportunistic infections amongst people living with HIV/AIDS

Risk factors for opportunistic infections:

In developing countries, emphasis on the risk factors for opportunistic infections has largely been on clinical parameters which has led to baseline CD₄ cell count and post treatment CD₄ cell count being acknowledged as the strongest predictor of HIV related opportunistic infection (Kaplan et al 2001). Risk factors associated with the occurrence of opportunistic infections amongst HIV patients were assessed in this study. Accordingly, advanced baseline WHO stage III and IV (68.8%), non – adherence to ART (61.3%), overcrowding (Household number > 5) (46.9%), CD₄ cell count less than 200 cells/µl (36.2%) and duration of HIV diagnosis ≤ 3 years (21.3%) were found to be associated factors for opportunistic infection occurrence. Similar studies have shown that advanced WHO clinical stage at baseline is an independent risk factor for the occurrence of opportunistic infections (Lawn et al, 2005; Srirangaraj and Venkatesha, 2011; Iroezindu et al, 2013). Overcrowding and poor hygiene have been suggested as contributory factors to high burden of HIV related opportunistic infections in developing countries (Srirangaraj and Venkatesha, 2011). Previous studies have also shown that ART drug adherence is associated with the occurrence of opportunistic infections (Lawn et al, 2005; Iroezindu et al, 2013). In our study, the adherence was low (38.7%) which may account for the high prevalence of opportunistic infections observed (51.9%). Another explanation also could be that the high non – adherence to ART (61.3%) in this study decreased CD₄ cells to below 200 cells/µl (36.2%) which in turn increased the risk for new opportunistic infections.

Table 2 : Risk factors for OIs amongst people living with HIV/AIDS

Adherence to ART

Non – adherent

Adherent

98 (61.3)

62 (38.7)

CD₄ cell count (Cells/µl)

>200

<200

102 (63.8)

58 (36.2)

WHO clinical staging

Stage III and IV

110 (68.8)

Duration of HIV diagnosis

<3years

34 (21.3)

Household number (overcrowding)

1 – 4

85 (53.1)

75 (46.9)

CONCLUSION:

In conclusion, the findings of this study suggest that opportunistic infections remain a challenge amongst people living with HIV/AIDS in Cameroon with a 51.9% occurrence of opportunistic infections. The leading common opportunistic infections being infective diarrhea greater than one month (32.2%), oesophageal candidiasis (16.5%), tuberculosis (16.5%) and Herpes zoster virus (14.9%). We therefore suggest that early detection of opportunistic infections should be intensified to improve the quality of life of the people living with HIV/AIDS as well as constant follow up of these patients to ensure a high level of adherence to ART which will also improve the CD₄ cell count and thus improve clinical outcomes.

LIMITATIONS:

This study was cross – sectional and also results may not be generalized because the sample size was not representative. Facilities to diagnose some opportunistic infections were not available and also the fact that some opportunistic infections were diagnosed based on symptoms may be misleading.

ACKNOWLEDGEMENT:

We thank the patients for participating in this study. We are also grateful to the Regional Delegate of Public Health for the North West Region of Cameroon, the director of the Bamenda Regional Hospital and the clinical and administrative staff of the Bamenda Regional Hospital

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Received on 01.11.2014 Modified on 18.11.2014

Int. J. Nur. Edu. and Research 2(4): Oct.- Dec. 2014; Page 381-384