Prevalence of renal dysfunction and associated risk factors among HIV patients on ART at the Bamenda Regional Hospital,Cameroon

Abstract

Since the advent of the management of HIV/AIDS using combination antiretroviral therapy (ART), the leading causes of morbidity and mortality in people living with HIV (PLWH) have changed from infectious to non-infectious causes with kidney disease increasingly emerging as being significant. Despite the introduction of the ‘test and treat’ strategy in Cameroon, there are still few data available on the effect of ART on renal function. Thus, this study aimed to determine the prevalence of renal dysfunction among PLWH on ART and its associated risk factors. We conducted a hospital-based comparative cross-sectional study involving PLWH naïve to ART and those on ART. Spectrophotometry was used to quantify renal markers. Glomerular filtration rate was estimated by the creatinine clearance (CrCl) method. Participants with CrCl <60 ml/min/1.73 m² were considered to have renal dysfunction. A total of 136 participants were recruited of which 97 (71.3%) were females. The mean age was 39.5 ± 9.2 years. Each study category had the same number of participants (68 each). Both had a prevalence of proteinuria of 50%. Of the total study population, 26 (19.1%) had CrCl <60 ml/min/1.73 m². About 82.4% of the participants on ART were on tenofovir-based regimens with a mean duration of treatment of 6.95 ± 3.74 years. The ART-experienced group had a prevalence of renal dysfunction of 26.5% and the ART-naïve group 11.8%. The difference in mean CrCl between the study groups was not statistically significant. There was no association between renal dysfunction and the ART regimen, duration on treatment, or adherence to treatment. Our study demonstrated a high prevalence of renal dysfunction among PLWH that was associated with increasing age. Decreased CD4 cell count increased the risk of proteinuria.

Keywords

Combination antiretroviral therapy treatment AIDS HIV renal

Background

Impaired renal function is an emerging public health problem with adverse outcomes of end stage kidney disease, cardiovascular disease, and death.¹ A systematic review conducted in sub-Saharan Africa concluded that chronic kidney disease (CKD) is a prevalent and potentially escalating disease across sub-Saharan Africa, with both communicable and non-communicable risk factors.² Rao et al.³ first reported on the association of HIV and decreased renal function on a series of HIV-1 seropositive patients who developed a renal syndrome characterized by progressive renal failure and proteinuria. Since then, several researchers have become interested in the mechanism involved. HIV management involves a life time administration of a cocktail of antiretroviral drugs some of which have been reported for their nephrotoxic effect.⁴ Since the introduction of antiretroviral therapy (ART) in the mid-1990s, there has been a drastic drop in the number of AIDS-related deaths.⁵ The kidney actively participates in the metabolism and excretion of drugs and the proximal tubule is very sensitive to drug toxicity. Antiretroviral drugs (ARVs) may increase the risk of kidney damage as some of them have been noted to be nephrotoxic.⁶ Tenofovir disoproxil fumarate (TDF), which is commonly prescribed, is considered the most nephrotoxic molecule among all the ARVs.⁷ Decreased renal function maybe a direct or indirect consequence of a variety of factors including HIV infection, HIV-induced inflammation, comorbid diseases, as well as drugs such as ARVs.⁸ Despite the increasing access to ART over the years, there are still few regional data available on the prevalence of renal impairment among people living with HIV (PLWH) on highly active antiretroviral therapy (HAART). In Cameroon, researchers have worked on the prevalence of CKD and its associated risk factors but many have failed to consider ART as a risk factor.⁹ The aim of this study was therefore to determine the prevalence of renal dysfunction among PLWH on ART and those not yet on ART and to evaluate the associated risk factors. This study will provide baseline data for more research on the implementation of the ‘test and treat’ strategy in Cameroon.

Method

Study area

This study was conducted at the Day Clinic of the Bamenda Regional Hospital. Bamenda Regional Hospital is the leading tertiary care hospital in the region, providing care and treatment to over 5000 PLWH as of 2016. The North West Region was ranked third (5.8%) in the CAMPHIA 2017 HIV prevalence in adults (15–49 years) ranking in Cameroon.¹⁰

Study design and study population

This was a comparative cross-sectional study involving PLWH on ART and those not yet on ART. Participants were recruited between March and June 2016. Participants were recruited chronologically from PLWH who came for their refills or routine check-ups, and newly-diagnosed individuals at the Clinic during this study period. Participants were recruited under two study groups (ART-naive and ART-experienced groups).

Inclusion and exclusion criteria

Participants aged 21–60 years who consented were recruited into the study. This was because according to the Cameroon code for the classification of adults, adulthood begins at the age of 21 years. Also, there are reports of a higher risk of having reduced renal function among adults older than 60 years.¹¹ Therefore, in an effort to reduce confounders due to age, only participants younger than 60 years were considered in this study. However, participants who had a blood pressure (BP) >140/90 mmHg and/or fasting blood sugar (FBS) >120 mg/dl were excluded. Participants who were obese; suffering from urinary tract infection or any other acute disease; had history of kidney transplant or dialysis; or those with known kidney, liver, or heart diseases as well as pregnant women were not considered for the study. Participants on long-term medications other than ART were also not included.

Sample size determination

The estimated sample size for this study was calculated as follows using the prevalence of CKD in Bamenda of 7.4%¹²

n = \frac{Z^{2} p (1 - p)}{e^{2}}

Administration of questionnaires

Data on the participants’ socio-demographic characteristics and medical history were collected using structured questionnaires. Participants residing in cities or towns were considered ‘urban’ and from the villages considered as ‘rural.’ Participants with education level above secondary (college) level were considered under tertiary. Participants were considered as consumers of alcohol if they had consumed at least one glass of alcohol per week within the past five years. Participants’ hospital records were also reviewed to obtain information on latest CD4 cell count (within the past two months), type of ARV regimen, and duration of treatment. Patients were considered adherent to treatment if they did not miss more than two doses per month.

Sample collection and analysis

A One touch Ultra glucometer was used to measure the participants’ FBS after an over-night fasting (screening for diabetes) after which the participants were asked to bring a single on-spot urine sample (50 ml). The urine sample was used for urinalysis as a screening tool for urinary tract infection (positive nitrite and leucocytes). Recruited participants were then given graduated 5L containers containing small amounts of preservative for a 24-h urine sample after the collection process had been explained to them in details. The 24-h urine sample was used for the quantification of protein and creatinine. About 2 ml venous blood was collected in dry tubes from each participant following standard procedures. The blood samples were allowed to coagulate at room temperature and sera prepared by centrifugation at 3000 r/min for 5 min. Serum creatinine and urea were analyzed using Erma Biochemical Analyzer (Erma Inc., Tokyo, Japan, Model AE-600N). Urine protein was measured using a 3000 EVOLUTION spectrophotometer. Creatinine clearance (CrCl) and blood urea nitrogen (BUN) were calculated from creatinine and urea concentrations.

Renal impairment was classified according to the National Kidney Foundation clinical practice guideline based on the GFR determined by the CrCl method. Accordingly, CrCl ≥ 90, 60–89, 30–59, 15–29 ml/min/1.73 m² and <15 ml/min/1.73 m² were interpreted as normal, mild, moderate, severe, and kidney failure.¹³ Renal dysfunction was defined as CrCl <60 ml/min/1.73 m². Reference ranges for renal function tests were set as follows: BUN 10–20 mg/dl, BUN–creatinine ratio 10–20, and urine protein <150 mg/24 h.

Data management and statistical analysis

Codes were assigned to each participant so as to observe strict confidentiality. The lab results were entered in a secured logbook. Data were then entered into Microsoft Excel version 10, cross checked for errors, and then transferred into the Statistical Package for Social Sciences version 21 for analysis. Independent Student’s t-test was used to compare mean values of continuous variables, Chi square for categorical variables, and Pearson’s correlation analysis for the correlation with the quantitative risk factors. A p value < 0.05 was considered statistically significant.

Results

Demographic characteristics of participants

A total of 136 participants were enrolled into the study, out of which 36 (28.4%) were males and 100 (71.6%) females. The participants had mean age of 39.5 ± 9.2 years. The majority of the participants 50 (36.8%) were within the age group of 41–50 years. About 72.8% of the study participants resided in the urban setting and 75% were employed. Equal numbers of participants (68 each) were enrolled in both the ART experienced and ART-naïve groups. Participants on ART had a higher mean body mass index (BMI), BP, and FBS as well as CD4 cell count. Table 1 presents the characteristics of the study participants.

Table 1.

Socio-demographic characteristics of the study participants.

Socio-demographic characteristics	ART-naïve	ART-experienced	Total
Socio-demographic characteristics	Number (%)	Number (%)	Number (%)
Gender
Male	22 (32.4)	14 (20.6)	36 (28.4)	P = 0.120
Female	46 (67.6)	54 (79.4)	100 (71.6)	P = 0.120
Age (years)
21–30	19 (27.9)	8 (11.8)	27 (19.9)	P = 0.019
31–40	25 (36.8)	18 (26.5)	43 (31.6)
41–50	19 (27.9)	31 (45.6)	50 (36.8)
50–60	5 (7.4)	11 (16.2)	16 (11.8)
Marital status
Married	36 (52.9)	34 (50.0)	70 (51.4)	P = 0.736
Single	22 (32.4)	20 (29.4)	42 (30.9)
Divorced	1 (1.5)	3 (4.4)	4 (2.9)
Widowed	9 (13.2)	11 (16.2)	20 (14.8)
Employment status
Employed	52 (76.5)	50 (73.5)	102 (75)	P = 0.687
Unemployed	16 (23.5)	18 (26.5)	34 (25)	P = 0.687
Level of education
Primary	30 (44.1)	41 (60.3)	71 (52.2)	P = 0.060
Secondary	27 (39.7)	21 (30.9)	48 (35.3)
Tertiary	11 (16.2)	6 (8.8)	17 (12.5)
Residence
Urban	52 (76.5)	47 (69.1)	99 (72.8)	P = 0.334
Rural	16 (23.5)	21 (30.9)	37 (27.2)	P = 0.334
Alcohol
Yes	42 (61.8)	35 (51.5)	77 (56.6)
No	26 (38.2)	33 (48.5)	59 (43.4)	P = 0.227
Age (mean, years)	36.6 ± 9.2	42.4 ± 8.0	39.5 ± 9.2	P < 0.001
Body mass index (kg/m2)	24.2 ± 3.5	25.0 ± 3.9	24.6 ± 3.7	P = 0.210
Systolic blood pressure (mmHg)	108.3 ± 14.2	116.3 ± 14.2	112.3 ± 14.3	P = 0.001
Diastolic blood pressure (mmHg)	71.0 ± 10.9	78.5 ± 9.7	74.8 ± 10.5	P < 0.001
Fasting blood sugar	105.0 ± 4.2	106.3 ± 4.0	105.7 ± 4.1	P = 0.067
CD4+ T-cell count (cells/µl)	281.66 ± 222.1	566.72 ± 229.4	251.9 ± 225.8	P < 0.001

ART: antiretroviral therapy.

The distribution of participants on the various ART regimens is described in Figure 1. A majority of the participants on ART (82.4%) were on TDF-based regimens and had a mean duration on treatment of 6.95 ± 3.74 years.

Figure 1.

Distribution of the ART group according to the ART regimen. AZT: zidovudine; EFV: efavirenz; LPV/r: lopinavir/ritonavir; NVP: nevirapine; TDF: tenofovir; 3TC: lamivudine.

Prevalence of renal dysfunction

Renal dysfunction was determined by both proteinuria and CrCl. The participants in the ART-naïve group demonstrated a higher mean urine protein of 243.7 mg/24h. Half of the total study population (68) had proteinuria. About 50% of the participants in either study group demonstrated a urine protein concentration higher than normal. Table 2 shows the prevalence of renal dysfunction among the study participants. Of the total study population, 26 (19.1%) had decreased CrCl. The ART-experienced group had a higher prevalence of renal dysfunction (26.5%) than the ART-naïve group (11.8%).

Table 2.

Prevalence of renal dysfunction in the study groups.

	ART-naïveFrequency (%)	ART-experiencedFrequency (%)	Chi square
Creatinine clearance (ml/min/1.73 m²)
≥60	60 (88.2)	50 (73.5)	P = 0.030
<60	8 (11.8)	18 (26.5)	P = 0.030
Proteinuria (mg/24 h)
≥150	34 (50.0)	34 (50.0)	P = 1.000
<150	34 (50.0)	34 (50.0)	P = 1.000

ART: antiretroviral therapy.*The P values in bold are the significant p values.

Association between ART and renal function

This study demonstrated a significantly higher mean BUN among the ART-experienced participants than the ART-naïve participants (P value of <0.001). Although the ART-experienced group demonstrated a higher mean urine protein and a lower CrCl when compared to the ART-naïve group, these differences were not statistically significant. These associations are presented in Table 3.

Table 3.

Association between ART and renal function.

Study group	BUN (mg/dl)Mean ± SD	Serum creatinine (mg/dl)Mean ± SD	CrCl (ml/min/1.73 m²)Mean ± SD	Urine protein (mg/24 h)Mean ± SD
ART-naïve	14.8 ± 5.3	0.91 ± 0.23	92.599 ± 34.60	243.7 ± 287.4
ART experienced	18.2 ± 6.3	0.97 ± 0.18	82.090 ± 32.11	190.7 ± 185.1
Student’s t-test	P = 0.001	p = 0.114	p = 0.068	p = 0.203

BUN: blood urea nitrogen; CrCl: creatinine clearance; ART: antiretroviral therapy.

Association of kidney function with age

In order to ascertain whether age could affect renal function, the means of the renal markers were compared among age categories of the study participants as shown in Table 4. It was demonstrated that only the mean serum creatinine and mean CrCl were significantly different among the age groups (p-values were 0.029 and <0.001, respectively). Although the ‘51–60’ age group had a significantly higher mean serum creatinine (p = 0.034) when compared to the ‘21–30’ age group, the positive correlation demonstrated by serum creatinine as against age was not significant (r = 0.12, p = 0.180).

Table 4.

Comparison of renal function test among age groups.

Age groups (years)	BUN (mg/dl)Mean ± SD	Serum creatinine (mg/dl)Mean ± SD	CrCl (ml/min/1.73 m²)Mean ± SD	Urine proteins (mg/24 h)Mean ± SD
21–30 (n = 59)	14.7 ± 4.1	0.88 ± 0.20	104.18 ± 34.38	250.9 ± 243.9
31–40 (n = 60)	16.2 ± 5.7	0.99 ± 0.27	88.08 ± 30.02	222.5 ± 350.4
41–50 (n=64)	17.2 ± 7.2	0.91 ± 0.15	79.59 ± 25.87	193.9 ± 147.2
>50 (n = 18)	17.7 ± 5.7	1.02 ± 0.17	93.70 ± 35.80	221.1 ± 115.4
ANOVA	P = 0.290	P = 0.029	p< 0.001	p = 0.800

ANOVA: analysis of variance; BUN: blood urea nitrogen; CrCl: creatinine clearance.

Association between renal function and CD4 cell count

The association between renal markers and CD4 cell count was also analyzed and presented in Table 5. The ‘>500’ category had a significantly higher mean BUN when compared to the other categories (p = 0.048). Although the ‘<200’ category had the lowest CrCl and highest urine protein among the categories, these differences were not statistically significant.

Table 5.

Comparison of kidney function tests between CD4 categories.

CD4 (cells/µl)	BUN (mg/dl)Mean ± SD	Serum creatinine (mg/dl)Mean ± SD	CrCl (ml/min/1.73 m²)Mean ± SD	Urine protein (mg/24 h)Mean ± SD
<200 (n = 29)	14.61 ± 4.41	0.91 ± 1.0	82.60 ± 29.73	286.57 ± 168.01
200–500 (n = 58)	15.36 ± 5.45	0.92 ± 1.3	86.66 ± 35.35	238.09 ± 295.70
>500 (n = 49)	17.23 ± 4.60	0.94 ± 0.9	96.70 ± 35.71	184.36 ± 138.22
ANOVA	p = 0.049	p = 0.070	p = 0.199	p = 0.143

ANOVA: analysis of variance; BUN: blood urea nitrogen; CrCl: creatinine clearance.

Association between renal function and adherence/type of regimen/duration of treatment

This study demonstrated that the renal markers were not associated with the type of regimen, duration of treatment, and patients’ adherence to treatment. Pearson’s correlation showed a weak negative correlation between duration on ART and CrCl but this was not statistically significant. CD4 cell count was negatively correlated with urinary protein. CD4 cell count had a significant positive correlation with BUN (r = 0.200, p = 0.020).

Discussion

Prevalence of renal dysfunction

Decreased renal function in HIV maybe a direct or indirect consequence of a variety of factors including HIV infection, HIV-induced inflammation, comorbid diseases, as well as drugs such as ARVs.⁸ This study examined the kidney profile of adult PLWH on ART excluding other comorbidities and determined the associated risk factors of CKD. Our study demonstrated a prevalence of renal dysfunction among ART-naïve patients of 11.8 and 26.5% among ART-experienced patients. A global systematic review on the prevalence of CKD among PLWH by Ekrikpo et al.¹⁴ reported a high prevalence in Africa with a burden on West Africa (9.2–22.0%) irrespective of the estimation equation used. Although the pooled prevalence reported using the modification of diet in renal disease (MDRD) (7.4%) and the Chronic Kidney Disease Epidemiology Collaboration (7.0%) estimation equations was lower than the prevalence demonstrated in this study, our report was in line with the 13.7% reported using the Cockroft–Gault equation in the same review.¹⁴ However, Kahsu et al.¹¹ in Ethiopia reported a higher prevalence among ART-naïve patients of 30.1%. This difference could have been because hypertensive and diabetic patients were included in the Kahsu et al. study, hence the higher prevalence. The prevalence of renal dysfunction among PLWH on ART of 26.5% in this study was similar to the 29% reported in a Tanzanian cohort by Mpondo et al.¹⁵ Nonetheless, this prevalence was higher than the 14.3% reported by Nsagha et al.¹⁶ This discrepancy could be due to the differences in the method used to estimate the GFR. Nsagha et al. used the MDRD equation to estimate the GFR. The high prevalence of renal dysfunction recorded in this study may also be due to the fact that most of the patients were on tenofovir-based regimens. Furthermore, participants on ART were older and had been on treatment for long which could indicate a longer history of HIV. All these could have affected the prevalence of renal dysfunction in this group of participants.

Association between ART and renal function

In this study, the mean CrCl was lower in PLWH on ART when compared to those not yet on ART but this was not significant. Our results were not in line with those of Nsagha et al. who reported ART to be nephrotoxic.¹⁶ However, we had similar observations as Obirikorang et al.¹⁷ who reported non-significant changes in renal function in HIV infection and over the course of ART. The ART-experienced patients had a higher mean BUN when compared to the ART-naïve patients. This result was different from the report of Kahsu et al.¹¹ who also demonstrated a higher mean BUN among participants on ART. This study demonstrated a prevalence of proteinuria among the ART-naïve patients of 50%, which was higher than the 36% prevalence of proteinuria reported by FolefackKaze et al.¹⁸ in Cameroon. This disparity could have been because, instead of the gold standard 24-h urine protein as used in this study, the dipstick urinalysis was used in the FolefackKaze et al. study, which is less sensitive.

Risk factors for decreased renal function

In this study, we evaluated CD4 cell count, age, type of regimen, duration of treatment, and patients’ adherence to treatment as risk factors of CKD among patients on ART. We demonstrated that though there was a difference in the mean CD4 cell count between the study groups, CD4 cell count was not associated with decreased renal function. There was also no association with the type of regimen, duration on treatment, and patients’ adherence. Our results were in line with those of Kamga et al.¹⁹ who reported that the effect of ART on the renal function was not associated with the type of ART regimen used, the duration on treatment, or the CD4 cell count. Our results were not in agreement with those reported by Nsagha et al.¹⁶ who reported the ART regimen ‘tenofovir, lamivudine and efavirenz’ to be the most nephrotoxic. We also demonstrated a negative correlation between CD4 cell count and proteinuria. This was in line with FolefackKaze et al.¹⁸ who also reported an association between decreased CD4 cell count and increased proteinuria.

This study is limited in that microalbuminuria was not measured. However, a quantitative measurement of urinary protein gives a good picture of the renal function. Only the current and not past treatment regimens were considered for the participants on ART. Another limitation in this study was that we did not repeat the evaluation of proteinuria after three months to differentiate acute from CKD.

Conclusions

This study demonstrated a high prevalence of reduced renal function among PLWH in Cameroon before treatment and even higher on ART. We demonstrated that age is a risk factor associated with decreased CrCl but found no association between decreased CrCl and CD4 cell count, type of regimen, duration of treatment, or patients’ adherence to treatment. However, we demonstrated that decreased CD4 cell count increases the patients’ risk of developing proteinuria.

Footnotes

Acknowledgements

This was part of an MSc thesis by Achu Che Awah Nforbugwe under the supervision of Prof. Assob and co-supervision of Prof. Asongalem in the Department of Medical laboratory Sciences of the University of Buea. The authors are grateful for the participation of the entire staff of the Day Clinic and laboratory of the Bamenda Regional Hospital to the realization of this study. We as well appreciate all our participants for their patience and dedication.

Authors’ contribution

ACAN conceived, designed, conducted the study, collected and analyzed the data, conducted the literature search and review, and wrote the manuscript. BRN assisted in study design and review of manuscript. EAT and FSW assisted in data analysis and critically reviewed the manuscript. AEA and NJCA coordinated the entire study and reviewed the manuscript. All authors read and approved the final paper.

Availability of data and material

All data generated or analyzed during this study are included in this published article.

Consent for publication

Not applicable.

Declaration of conflicting interests

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

Ethics approval and consent to participate

Ethical clearance was obtained from the Bamenda Regional Hospital Institutional Review Board (BRHIRB 2016/023). Authorization was obtained from the North West Regional Delegation of Public Health and from the administration of Bamenda Regional Hospital. A written consent form was provided to the participants wherein the procedure of the study was explained, its risks and benefits to the participant, confidentiality and the participant’s right of withdrawal from the study at any time. Only participants who gave their consent by signing this form were recruited into the study.

Funding

The authors disclosed receipt of the following financial support for the research, authorship and/or publication of this article: We acknowledge the financial assistance from the Adolphe Monkiedje Fellowship board to carry out this study.

ORCID iD

Achu Che Awah Nforbugwe

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