<?xml version="1.0" encoding="UTF-8"?><!DOCTYPE article  PUBLIC "-//NLM//DTD Journal Publishing DTD v3.0 20080202//EN" "http://dtd.nlm.nih.gov/publishing/3.0/journalpublishing3.dtd"><article xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink" dtd-version="3.0" xml:lang="en" article-type="research article"><front><journal-meta><journal-id journal-id-type="publisher-id">OJNeph</journal-id><journal-title-group><journal-title>Open Journal of Nephrology</journal-title></journal-title-group><issn pub-type="epub">2164-2842</issn><publisher><publisher-name>Scientific Research Publishing</publisher-name></publisher></journal-meta><article-meta><article-id pub-id-type="doi">10.4236/ojneph.2020.102010</article-id><article-id pub-id-type="publisher-id">OJNeph-99628</article-id><article-categories><subj-group subj-group-type="heading"><subject>Articles</subject></subj-group><subj-group subj-group-type="Discipline-v2"><subject>Medicine&amp;Healthcare</subject></subj-group></article-categories><title-group><article-title>
 
 
  Prevalence and Determinants of Kidney Markers among Subjects with Hepatitis C Virus Infection
 
</article-title></title-group><contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Mathurin</surname><given-names>Pierre Kowo</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref><xref ref-type="corresp" rid="cor1"><sup>*</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Sylvain</surname><given-names>Raoul Simeni Njonnou</given-names></name><xref ref-type="aff" rid="aff2"><sup>2</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Murielle</surname><given-names>Sonia Mehly Ngninzeko</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Firmin</surname><given-names>Ankouane Andoulo</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Antonin</surname><given-names>Ndjitoyap Ndam</given-names></name><xref ref-type="aff" rid="aff1"><sup>1</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Michelle</surname><given-names>Tagny Sartre</given-names></name><xref ref-type="aff" rid="aff5"><sup>5</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Vicky</surname><given-names>Ama Moor</given-names></name><xref ref-type="aff" rid="aff6"><sup>6</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Jeanne</surname><given-names>Ngongang</given-names></name><xref ref-type="aff" rid="aff3"><sup>3</sup></xref></contrib><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>François</surname><given-names>Folefack Kaze</given-names></name><xref ref-type="aff" rid="aff4"><sup>4</sup></xref></contrib></contrib-group><aff id="aff3"><addr-line>Higher Institute of Health Sciences, Université des Montagnes, Bangangté, Cameroon</addr-line></aff><aff id="aff2"><addr-line>Department of Internal Medicine and Specialty, Faculty of Medicine and Pharmaceutical Sciences, University of Dschang, 
Dschang, Cameroon</addr-line></aff><aff id="aff5"><addr-line>Medical Centre “La Cathédrale”, Yaoundé, Cameroon</addr-line></aff><aff id="aff4"><addr-line>Yaounde University Teaching Hospital, Yaoundé, Cameroon</addr-line></aff><aff id="aff1"><addr-line>Department of Internal Medicine and Specialty, Faculty of Medicine and Biomedical Sciences, University of Yaoundé I, Yaoundé, Cameroon</addr-line></aff><aff id="aff6"><addr-line>Department of Physiological Sciences and Biochemistry, Faculty of Medicine and Biomedical Sciences, University of Yaoundé I, Yaoundé, Cameroon</addr-line></aff><pub-date pub-type="epub"><day>02</day><month>04</month><year>2020</year></pub-date><volume>10</volume><issue>02</issue><fpage>85</fpage><lpage>101</lpage><history><date date-type="received"><day>20,</day>	<month>March</month>	<year>2020</year></date><date date-type="rev-recd"><day>18,</day>	<month>April</month>	<year>2020</year>	</date><date date-type="accepted"><day>21,</day>	<month>April</month>	<year>2020</year></date></history><permissions><copyright-statement>&#169; Copyright  2014 by authors and Scientific Research Publishing Inc. </copyright-statement><copyright-year>2014</copyright-year><license><license-p>This work is licensed under the Creative Commons Attribution-NonCommercial International License (CC BY-NC).http://creativecommons.org/licenses/by-nc/4.0/</license-p></license></permissions><abstract><p>
 
 
  Introduction: Hepatitis C virus (HCV) infection is a worldwide public health problem with multisystemic involvements including kidneys. We assessed the prevalence and determinants of kidney markers among HCV infected subjects. 
  Methods: A cross-sectional study was conducted from March to July 2017 in two referral centers in Yaound&#233;. Sociodemographic, clinical and paraclinical data were collected from patient’s records. Renal involvement was evaluated using estimated glomerular filtration rate (eGFR) by Modification of Diet in Renal Disease’s (MDRD) equation, urine dipstick and albumin/creatinine ratio (ACR). An eGFR &lt; 60 and between 60 - 89 mL/min/1.73 m
  <sup>2</sup> was defined as low and reduced respectively. Albuminuria was defined by an ACR &gt; 30 mg/g and divided into A1 (&lt;30 mg/g), A2 (30 - 300 mg/g) and A3 (&gt;300 mg/g). 
  Results: We included 65 (41.5% males) HCV infected patients with a mean age of 56.8 &#177; 10.5 years. HCV infection was diagnosed for more than 5 years in 54 (83.1%) patients. HCV viral load and genotype were available in 40 (61.5%) patients; viral load was high (&gt;5.9 logs/mL) in 20 (50%) of them and genotypes 4 (40%), 1 (32.5%) and 2 (27.5%) were found in this population. The mean eGFR was 112.9 &#177; 31.9 mL/min/1.73 m
  <sup>2</sup> with 14 (21.5%) and 4 (6.2%) patients having reduced and low eGFR respectively. Albuminuria (80%), leukocyturia (24.6%) and hematuria (4.6%) were the observed dipstick abnormalities. Median albuminuria (IQR) was 542.4 (238.7 - 961.5) mg/g, with 7 (11%), 12 (18%) and 46 (71%) patients in A1, A2 and A3 respectively. Reduced/low eGFR and albuminuria were observed in 58 (89.2%) patients while low eGFR and albuminuria were found in 55 (84.6%) patients. Advanced age, female gender, HCV genotype 1 and 4, and albuminuria (all p &lt; 0.03) were associated with eGFR reduction. 
  Conclusion: Renal abnormalities are common in HCV infected patients leading by proteinuria and decreased eGFR. Known risk factors of kidney diseases, HCV genotype 1 and 4 and albuminuria were associated with eGFR reduction in our setting.
 
</p></abstract><kwd-group><kwd>Hepatitis C Virus</kwd><kwd> Chronic Kidney Disease</kwd><kwd> Prevalence</kwd><kwd> Sub-Saharan Africa</kwd></kwd-group></article-meta></front><body><sec id="s1"><title>1. Introduction</title><p>Chronic viral hepatitis C (CVHC) predisposes to liver fibrosis and is a major cause of liver-related mortality and morbidity [<xref ref-type="bibr" rid="scirp.99628-ref1">1</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref2">2</xref>]. With a global prevalence of 3% (71 million persons infected), CVHC infection is a major public health problem worldwide [<xref ref-type="bibr" rid="scirp.99628-ref1">1</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref3">3</xref>]. Its prevalence ranges from 0.4% in Western Europe to more than 9% in Central Africa [<xref ref-type="bibr" rid="scirp.99628-ref3">3</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref4">4</xref>]. Cameroon is one of the most affected countries, with a nation-wide prevalence of 6.5% [<xref ref-type="bibr" rid="scirp.99628-ref5">5</xref>]. This prevalence varies according to regional and temporal disparities ranging from 13% among Pygmies and Bantus in South Cameroon to 21.1% in the East region [<xref ref-type="bibr" rid="scirp.99628-ref5">5</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref6">6</xref>].</p><p>Morbi-mortality of hepatitis C virus (HCV) infection is mainly related to cirrhosis and hepatocellular carcinoma [<xref ref-type="bibr" rid="scirp.99628-ref7">7</xref>]. Despite the HCV hepatotrophicity, it can affect other organs, leading to manifestations such as autoimmune, metabolic, renal, cardiovascular, central nervous system, and lymphoproliferative disorders [<xref ref-type="bibr" rid="scirp.99628-ref8">8</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref9">9</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref10">10</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref11">11</xref>]. Those extrahepatic manifestations are rarely in the foreground but can reveal the disease, may be severe and require urgent management. Recent studies show a variation of extrahepatic manifestations ranging from 1.76% for ischemic stroke to 50% for neurocognitive changes, porphyria cutanea tarda and cutaneous vasculitis [<xref ref-type="bibr" rid="scirp.99628-ref9">9</xref>]. The renal manifestations of HCV infection are common and contribute to worsening prognosis as well as the burden of the disease; they are mainly glomerular including membranoproliferative glomerulonephritis, membranous nephropathy and cryoglobulinemia [<xref ref-type="bibr" rid="scirp.99628-ref10">10</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref12">12</xref>]. They lead to chronic kidney disease (CKD) which progresses to end-stage kidney disease [<xref ref-type="bibr" rid="scirp.99628-ref13">13</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref14">14</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref15">15</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref16">16</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref17">17</xref>].</p><p>If renal manifestations of HCV infection have been widely assessed in Western countries, these have been poorly investigated in Africa [<xref ref-type="bibr" rid="scirp.99628-ref18">18</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref19">19</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref20">20</xref>]. A recent study in Cameroon found an anti-HCV prevalence of 19.2% among patients on maintenance hemodialysis (MHD) [<xref ref-type="bibr" rid="scirp.99628-ref21">21</xref>]. With the availability of direct-acting antiviral agents (DAAA), it was therefore important for us to assess the prevalence of renal manifestations of HCV infection and identify associated risk factors. The early diagnosis will help to introduce nephroprotection measures within such a population.</p></sec><sec id="s2"><title>2. Methods</title><p>Study design and setting: This cross-sectional study was carried out in two therapeutic centers for hepatitis management in Yaounde (Yaounde University Teaching Hospital and Medical Centre “La Cath&#233;drale”). Yaounde University Teaching Hospital is a tertiary hospital while Medical Centre “La Cath&#233;drale” is a private medical institution with a high technology platform; all in Yaounde, the capital city of Cameroon.</p><p>Study population: Patients seen in outpatient consultation and hospitalization ward with the diagnosis of HCV infection were recruited. Patients followed up, but not seen at outpatient consultation were invited through phone calls to participate to the study. Detection of HCV antibodies was done using a rapid diagnostic test and those who tested positive had a confirmatory ELISA test.</p><p>Variables and Measurements: All consenting HCV-infected subjects above 18 years, na&#239;ve to treatment were included. Patients with conditions that may lead to confusion at the urine test such as hypertension, diabetes, hepatitis B virus infection, HIV infection, systemic lupus, renal lithiasis or urinary tract infection, were excluded. Sociodemographic characteristics (age, gender, profession, alcohol consumption, smoking), clinical data (weight, height, signs of hepatocellular failure and/or portal hypertension), biological (serum and urinary creatinine, urine dipstick, 24 hours albuminuria) and virological parameters (HCV-viral load and genotype) were collected. Height (in m) was measured using a wooden platform and a height rule. Body mass index (BMI) was calculated as weight (kg)/height (m) &#215; height (m).</p><p>Quantitative determination of HCV RNA and the genotyping were requested for each new patient. For followed up patients, these pieces of information were obtained from their files. Fibroscan&#174; (Echosens, Paris, France), a noninvasive marker of fibrosis, was used and converted to the METAVIR score to categorize fibrosis in chronic hepatitis C according to a 5-stages classification: F0 (no fibrosis), F1 (portal and periportal fibrosis without septa), F2 (portal and periportal fibrosis with rare septa), F3 (numerous septa without cirrhosis), and F4 (cirrhosis). The selection process is summarized in <xref ref-type="fig" rid="fig1">Figure 1</xref>.</p><p>Laboratory testing</p><p>For each patient, blood and urinary samples were collected. Urine dipstick tests were conducted with CombiScreen<sup>&#174;</sup> 7SL PLUS 7 test strips (Analyticon Biotechnologies AG, D-35,104 Lichentenfeis, Germany). Urinary pH, specific gravity and glucose were not taken into consideration for the purpose of the study.</p><p>Serum and urinary creatinine were conducted using a kinetic method called “Jaff&#233; reaction” (with CYPRESS<sup>&#174;</sup> reagents, CYPRESS Diagnostics, Hulshout,</p><p>Belgium). Albuminuria dosage was performed using a spectrophotometric method. Glomerular filtration rate (GFR) was estimated by The Modification of Diet in Renal Disease (MDRD) equation [<xref ref-type="bibr" rid="scirp.99628-ref15">15</xref>]. A urine dipstick test was conducted for evaluating albuminuria, hematuria and leukocyturia. 24 hours albuminuria was estimated using urine albumin/creatinine ratio (ACR) from the urine spot.</p><p>Definitions:</p><p>Obesity was defined as a body mass index (BMI) ≥ 30 kg/m<sup>2</sup>, and overweight was defined as a BMI between 25 and 29.9 kg/m<sup>2</sup>. Excessive alcohol consumption was considered for a consumption &gt; 30 g/day for women and 40 g/day for men or more than 10 (5 for women) local beers per week. The METAVIR score also categorized activity according to a 4-grade classification: A0 (no activity), A1 (minimal activity), A2 (moderate activity), and A3 (severe activity) [<xref ref-type="bibr" rid="scirp.99628-ref22">22</xref>]. GFR (in mL/min per 1.73 m<sup>2</sup>) was divided into G1 (&gt;90), G2 (60 - 89), G3 (30 - 59) G4 (15 - 29) and G5 (&lt;15). For this study, an eGFR &lt; 60 mL/min per 1.73 m<sup>2</sup> was considered as low while between 60 - 89 mL/min per 1.73 m<sup>2</sup> was defined as reduced. Raised creatinine was considered for levels &gt; 1.3 mg/dL. Albuminuria was defined by ACR ≥ 30 mg/g. It was divided into A1 (ACR &lt; 30 mg/g), A2 (ACR (30 - 300 mg/g) and A3 (ACR &gt; 300 mg/g). The diagnosis of urine dipstick abnormalities was based on at least 1+ confirmed by a second test two weeks later. An abnormal GPT level was defined as values greater than 35 IU/L. HCV viral load was considered as high if &gt;800,000 IU/mL (5.9 logs/mL) [<xref ref-type="bibr" rid="scirp.99628-ref23">23</xref>].</p><p>Sample size and Statistical analysis: A consecutive sample of all eligible cases was considered for this study. Data were analyzed using Statistical Package for Social Sciences (SSPS Inc, Chicago, Illinois, USA) V.20.0 and EPI-INFO V.3.5 software. Discrete variables were presented as counts and percentages, and continuous variables as mean (standard deviation) or median (IQR). The Chi-square test was used, Student t-test, and ANOVA where appropriate.</p></sec><sec id="s3"><title>3. Results</title><p>Characteristics of the study population</p><p>We included 65 (41.5% males) HCV-infected patients, na&#239;ve to treatment. Patients’ mean age was 56.8 &#177; 10.5 years with 30 (46.2%) above 60 years old. The mean BMI was 27.1 &#177; 4.2 Kg/m<sup>2</sup> with overweight and obesity found in 35 (53.8%) and 15 (23.1%) patients respectively. Regular consumption of nephrotoxics was found in 35 (53.8%) patients. At-risk alcohol consumption was observed in 4 (6.2%) patients. There were 54 (83.1%) patients diagnosed with HCV infection for more than 5 years.</p><p>HCV viral load was performed in 40 (61.5%) patients with a mean of was 6.3 &#177; 3.5 logs and 20 (50%) patients had a viral load greater than 5.9 logs. Genotype: 4 (40%), 1 (32.5%) and 2 (27.5%) were found in this population. Liver fibrosis was evaluated in 50 patients with the following stage F4 (32%), F3 (10%), F2 (18%), F1 (22%) and F0 (18%). The mean GPT was 37.9 &#177; 24 U/L and was increased in 24 (36.9%) patients. <xref ref-type="table" rid="table1">Table 1</xref> reports the clinicobiological characteristics of the study population.</p><p>Kidney function and urine profile</p><p>Median albuminuria (IQR) was 542.4 (238.7 - 961.5) mg/g, with 7 (11%), 12 (18%) and 46 (71%) patients classified in A1, A2 and A3 categories respectively. Association of reduced/low eGFR and albuminuria was observed in 58 (89.2%) patients while low eGFR associated with albuminuria was found in 55 (84.6%) patients (<xref ref-type="fig" rid="fig2">Figure 2</xref>).</p><p>The mean serum creatinine was 1.2 &#177; 0.3 mg/dL with 16 (24.6%) having raised serum creatinine. The mean eGFR was 112.9 &#177; 31.9 mL/min/1.73 m<sup>2</sup> with 14 (21.5%) and 4 (6.2%) patients having reduced and low eGFR respectively. Albuminuria (80%), leukocyturia (24.6%) and hematuria (4.6%) were dipstick abnormalities recorded for the purpose of the study. These abnormalities were also</p><table-wrap-group id="1"><label><xref ref-type="table" rid="table1">Table 1</xref></label><caption><title> Clinicobiological profile of the study population</title></caption><table-wrap id="1_1"><table><tbody><thead><tr><th align="center" valign="middle" >Variables</th><th align="center" valign="middle" >Frequency (n)</th><th align="center" valign="middle" >Percentage (%)</th></tr></thead><tr><td align="center" valign="middle" >Gender</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Male</td><td align="center" valign="middle" >27</td><td align="center" valign="middle" >41.5</td></tr><tr><td align="center" valign="middle" >Female</td><td align="center" valign="middle" >38</td><td align="center" valign="middle" >58.5</td></tr><tr><td align="center" valign="middle" >Age group</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >20 - 39</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >10.8</td></tr><tr><td align="center" valign="middle" >40 - 59</td><td align="center" valign="middle" >28</td><td align="center" valign="middle" >43.1</td></tr><tr><td align="center" valign="middle" >≥60</td><td align="center" valign="middle" >30</td><td align="center" valign="middle" >46.1</td></tr><tr><td align="center" valign="middle" >Duration of HCV infection (in years)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >1 - 5</td><td align="center" valign="middle" >54</td><td align="center" valign="middle" >83.1</td></tr><tr><td align="center" valign="middle" >6 - 10</td><td align="center" valign="middle" >8</td><td align="center" valign="middle" >12.3</td></tr><tr><td align="center" valign="middle" >11 - 20</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >4.6</td></tr><tr><td align="center" valign="middle" >Drug consumption</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Traditional medicine</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >6.1</td></tr><tr><td align="center" valign="middle" >Modern medicine</td><td align="center" valign="middle" >22</td><td align="center" valign="middle" >18.5</td></tr><tr><td align="center" valign="middle" >Modern and traditional medicine</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >33.8</td></tr><tr><td align="center" valign="middle" >None</td><td align="center" valign="middle" >27</td><td align="center" valign="middle" >41.6</td></tr><tr><td align="center" valign="middle" >Alcohol consumption</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >10.8</td></tr><tr><td align="center" valign="middle" >At-risk</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >6.1</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >58</td><td align="center" valign="middle" >89.2</td></tr><tr><td align="center" valign="middle" >Body mass index</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Normal</td><td align="center" valign="middle" >27</td><td align="center" valign="middle" >41.5</td></tr><tr><td align="center" valign="middle" >Overweight</td><td align="center" valign="middle" >23</td><td align="center" valign="middle" >35.4</td></tr><tr><td align="center" valign="middle" >Obesity</td><td align="center" valign="middle" >15</td><td align="center" valign="middle" >23.1</td></tr><tr><td align="center" valign="middle" >Genotype (n = 42)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >13</td><td align="center" valign="middle" >20.9</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >11</td><td align="center" valign="middle" >26.1</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >4.8</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >16</td><td align="center" valign="middle" >38.1</td></tr><tr><td align="center" valign="middle" >Fibrosis staging (n = 50)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >F0</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >18</td></tr><tr><td align="center" valign="middle" >F1</td><td align="center" valign="middle" >11</td><td align="center" valign="middle" >22</td></tr><tr><td align="center" valign="middle" >F2</td><td align="center" valign="middle" >9</td><td align="center" valign="middle" >18</td></tr><tr><td align="center" valign="middle" >F3</td><td align="center" valign="middle" >5</td><td align="center" valign="middle" >10</td></tr><tr><td align="center" valign="middle" >F4</td><td align="center" valign="middle" >16</td><td align="center" valign="middle" >32</td></tr></tbody></table></table-wrap><table-wrap id="1_2"><table><tbody><thead><tr><th align="center" valign="middle" >Dipstick profile</th><th align="center" valign="middle" ></th><th align="center" valign="middle" ></th></tr></thead><tr><td align="center" valign="middle" >Isolated albuminuria</td><td align="center" valign="middle" >35</td><td align="center" valign="middle" >53.8</td></tr><tr><td align="center" valign="middle" >Isolated leucocyturia</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td></tr><tr><td align="center" valign="middle" >Isolated hematuria</td><td align="center" valign="middle" >0</td><td align="center" valign="middle" >0</td></tr><tr><td align="center" valign="middle" >Albuminuria + Leukocyturia</td><td align="center" valign="middle" >16</td><td align="center" valign="middle" >24.6</td></tr><tr><td align="center" valign="middle" >Albuminuria + hematuria</td><td align="center" valign="middle" >3</td><td align="center" valign="middle" >4.6</td></tr><tr><td align="center" valign="middle" >Albuminuria + Leukocyturia + hematuria</td><td align="center" valign="middle" >2</td><td align="center" valign="middle" >3.1</td></tr><tr><td align="center" valign="middle" >Albuminuria categories</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >A1</td><td align="center" valign="middle" >7</td><td align="center" valign="middle" >10.7</td></tr><tr><td align="center" valign="middle" >A2</td><td align="center" valign="middle" >12</td><td align="center" valign="middle" >18.5</td></tr><tr><td align="center" valign="middle" >A3</td><td align="center" valign="middle" >46</td><td align="center" valign="middle" >70.8</td></tr><tr><td align="center" valign="middle" >Cytolysis</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Increased ALAT</td><td align="center" valign="middle" >24</td><td align="center" valign="middle" >36.9</td></tr><tr><td align="center" valign="middle" >Increased ASAT</td><td align="center" valign="middle" >38</td><td align="center" valign="middle" >58.5</td></tr><tr><td align="center" valign="middle" >Increased creatinine</td><td align="center" valign="middle" >16</td><td align="center" valign="middle" >24.6</td></tr><tr><td align="center" valign="middle" >Reduced eGFR</td><td align="center" valign="middle" >4</td><td align="center" valign="middle" >6.1</td></tr></tbody></table></table-wrap></table-wrap-group><p>associated to each other with albuminuria-leukocyturia in 16 (24.6%) patients, albuminuria-hematuria in 3 (4.6%) patients and albuminuria-hematuria-leukocyturia in 2 (3.1%) patients.</p><p>Determinants of renal markers</p><p>We observed that advanced age (p = 0.018), female gender (p &lt; 0.001), HCV genotype 1 and 4 (p = 0.003) and albuminuria (p = 0.03) were associated with low/reduce eGFR (<xref ref-type="table" rid="table2">Table 2</xref>). There was no factor associated with albuminuria (all p &gt; 0.05) (<xref ref-type="table" rid="table3">Table 3</xref>).</p></sec><sec id="s4"><title>4. Discussion</title><p>This cross-sectional study, assessing the prevalence and associated factors of renal markers among HCV-infected patients in a sub-Saharan African (SSA) setting, revealed that kidney abnormalities are common, leading by proteinuria (89.2%) and reduced/low eGFR (27.7%). Advanced age, female gender, HCV genotype 1 and 4, and albuminuria were associated with eGFR reduction. This study represents to our knowledge, the first published analysis of renal involvement of HCV infection in SSA.</p><p>The female predominance of HCV antibodies in this population (58.4%) was similar to reports done by other authors [<xref ref-type="bibr" rid="scirp.99628-ref24">24</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref25">25</xref>]. Patients’ mean age was high (56.8 &#177; 10.5 years), similar to that reported by Kowo et al. and Denniston et al. [<xref ref-type="bibr" rid="scirp.99628-ref6">6</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref26">26</xref>]. It might be related to the age at the contamination time probably during the mass vaccination campaign before virus discovery. However, the discovery of the infection was less than 5 years old in most (83.1%) of these patients.</p><table-wrap-group id="2"><label><xref ref-type="table" rid="table2">Table 2</xref></label><caption><title> Factors associated with glomerular filtration rate levels</title></caption><table-wrap id="2_1"><table><tbody><thead><tr><th align="center" valign="middle" >Variables</th><th align="center" valign="middle" >Mean eGFR (ml/min/1.73 m<sup>2</sup>)</th><th align="center" valign="middle" >p value</th></tr></thead><tr><td align="center" valign="middle" >Age group</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >20 - 39</td><td align="center" valign="middle" >141</td><td align="center" valign="middle"  rowspan="3"  >0.018</td></tr><tr><td align="center" valign="middle" >40 - 59</td><td align="center" valign="middle" >115.2</td></tr><tr><td align="center" valign="middle" >≥60</td><td align="center" valign="middle" >104.2</td></tr><tr><td align="center" valign="middle" >Gender</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Male</td><td align="center" valign="middle" >129.5</td><td align="center" valign="middle"  rowspan="2"  >&lt;0.001</td></tr><tr><td align="center" valign="middle" >Female</td><td align="center" valign="middle" >101.2</td></tr><tr><td align="center" valign="middle" >Duration of HCv infection (in years)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >1 - 5</td><td align="center" valign="middle" >114.6</td><td align="center" valign="middle"  rowspan="3"  >0.565</td></tr><tr><td align="center" valign="middle" >6 - 10</td><td align="center" valign="middle" >107.7</td></tr><tr><td align="center" valign="middle" >11 - 20</td><td align="center" valign="middle" >96</td></tr><tr><td align="center" valign="middle" >Traditional Medicine</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >118.5</td><td align="center" valign="middle"  rowspan="2"  >0.448</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >111.3</td></tr><tr><td align="center" valign="middle" >Modern Medicine</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >105.8</td><td align="center" valign="middle"  rowspan="2"  >0.168</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >117.1</td></tr><tr><td align="center" valign="middle" >Alcohol consumption</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >128.3</td><td align="center" valign="middle"  rowspan="2"  >0.094</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >111.1</td></tr><tr><td align="center" valign="middle" >Body mass index</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Normal</td><td align="center" valign="middle" >114</td><td align="center" valign="middle"  rowspan="2"  >0.815</td></tr><tr><td align="center" valign="middle" >Increased</td><td align="center" valign="middle" >112.1</td></tr><tr><td align="center" valign="middle" >HCV viral load</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Increased</td><td align="center" valign="middle" >120.3</td><td align="center" valign="middle"  rowspan="2"  >0.386</td></tr><tr><td align="center" valign="middle" >Low</td><td align="center" valign="middle" >112.8</td></tr><tr><td align="center" valign="middle" >Fibrosis staging</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >F0</td><td align="center" valign="middle" >119.6</td><td align="center" valign="middle"  rowspan="5"  >0.979</td></tr><tr><td align="center" valign="middle" >F1</td><td align="center" valign="middle" >120.4</td></tr><tr><td align="center" valign="middle" >F2</td><td align="center" valign="middle" >113.6</td></tr><tr><td align="center" valign="middle" >F3</td><td align="center" valign="middle" >115.6</td></tr><tr><td align="center" valign="middle" >F4</td><td align="center" valign="middle" >112.8</td></tr><tr><td align="center" valign="middle" >Genotype</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >110.1</td><td align="center" valign="middle"  rowspan="4"  >0.003</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >137.6</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >170</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >107.9</td></tr></tbody></table></table-wrap><table-wrap id="2_2"><table><tbody><thead><tr><th align="center" valign="middle" >ALAT</th><th align="center" valign="middle" ></th><th align="center" valign="middle" ></th></tr></thead><tr><td align="center" valign="middle" >Normal</td><td align="center" valign="middle" >111</td><td align="center" valign="middle"  rowspan="2"  >0.541</td></tr><tr><td align="center" valign="middle" >Increased</td><td align="center" valign="middle" >116.1</td></tr><tr><td align="center" valign="middle" >ASAT</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Normal</td><td align="center" valign="middle" >115.1</td><td align="center" valign="middle"  rowspan="2"  >0.640</td></tr><tr><td align="center" valign="middle" >Increased</td><td align="center" valign="middle" >111.3</td></tr><tr><td align="center" valign="middle" >Dipstick albuminuria</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >108.6</td><td align="center" valign="middle"  rowspan="2"  >0.030</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >130</td></tr><tr><td align="center" valign="middle" >Dipstick leukocyturia</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >117.8</td><td align="center" valign="middle"  rowspan="2"  >0.480</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >111.3</td></tr><tr><td align="center" valign="middle" >Dipstick hematuria</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >109.6</td><td align="center" valign="middle"  rowspan="2"  >0.858</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >113.1</td></tr><tr><td align="center" valign="middle" >Albuminuria categories</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >A1</td><td align="center" valign="middle" >129.1</td><td align="center" valign="middle"  rowspan="3"  >0.286</td></tr><tr><td align="center" valign="middle" >A2</td><td align="center" valign="middle" >116.8</td></tr><tr><td align="center" valign="middle" >A3</td><td align="center" valign="middle" >109.4</td></tr></tbody></table></table-wrap></table-wrap-group><table-wrap-group id="3"><label><xref ref-type="table" rid="table3">Table 3</xref></label><caption><title> Factors associated with albuminuria</title></caption><table-wrap id="3_1"><table><tbody><thead><tr><th align="center" valign="middle" >Variables</th><th align="center" valign="middle" >Albuminuria</th><th align="center" valign="middle" >p value</th></tr></thead><tr><td align="center" valign="middle" >Age group</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >20 - 39</td><td align="center" valign="middle" >841.3</td><td align="center" valign="middle"  rowspan="3"  >0.050</td></tr><tr><td align="center" valign="middle" >40 - 59</td><td align="center" valign="middle" >625.6</td></tr><tr><td align="center" valign="middle" >≥60</td><td align="center" valign="middle" >1112.2</td></tr><tr><td align="center" valign="middle" >Gender</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Male</td><td align="center" valign="middle" >817.8</td><td align="center" valign="middle"  rowspan="2"  >0.915</td></tr><tr><td align="center" valign="middle" >Female</td><td align="center" valign="middle" >912.9</td></tr><tr><td align="center" valign="middle" >Duration of HCV infection (in years)</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >1 - 5</td><td align="center" valign="middle" >709.9</td><td align="center" valign="middle"  rowspan="3"  >0.127</td></tr><tr><td align="center" valign="middle" >6 - 10</td><td align="center" valign="middle" >1510.7</td></tr><tr><td align="center" valign="middle" >11 - 20</td><td align="center" valign="middle" >2116.6</td></tr><tr><td align="center" valign="middle" >Traditional Medicine</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >851.1</td><td align="center" valign="middle"  rowspan="2"  >0.937</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >880.1</td></tr></tbody></table></table-wrap><table-wrap id="3_2"><table><tbody><thead><tr><th align="center" valign="middle" >Modern Medicine</th><th align="center" valign="middle" ></th><th align="center" valign="middle" ></th></tr></thead><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >1098.1</td><td align="center" valign="middle"  rowspan="2"  >0.376</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >741.8</td></tr><tr><td align="center" valign="middle" >Alcohol consumption</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >610.9</td><td align="center" valign="middle"  rowspan="2"  >0.557</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >905.1</td></tr><tr><td align="center" valign="middle" >Body mass index</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Normal</td><td align="center" valign="middle" >868.8</td><td align="center" valign="middle"  rowspan="2"  >0.980</td></tr><tr><td align="center" valign="middle" >Increased</td><td align="center" valign="middle" >876.6</td></tr><tr><td align="center" valign="middle" >HCV viral load</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Increased</td><td align="center" valign="middle" >805.5</td><td align="center" valign="middle"  rowspan="2"  ></td></tr><tr><td align="center" valign="middle" >Low</td><td align="center" valign="middle" >795.4</td></tr><tr><td align="center" valign="middle" >Fibrosis staging</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >F0</td><td align="center" valign="middle" >410.3</td><td align="center" valign="middle"  rowspan="5"  >0.180</td></tr><tr><td align="center" valign="middle" >F1</td><td align="center" valign="middle" >868.6</td></tr><tr><td align="center" valign="middle" >F2</td><td align="center" valign="middle" >468.2</td></tr><tr><td align="center" valign="middle" >F3</td><td align="center" valign="middle" >1750.7</td></tr><tr><td align="center" valign="middle" >F4</td><td align="center" valign="middle" >1072</td></tr><tr><td align="center" valign="middle" >Genotype</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >1</td><td align="center" valign="middle" >585.5</td><td align="center" valign="middle"  rowspan="4"  >0.769</td></tr><tr><td align="center" valign="middle" >2</td><td align="center" valign="middle" >895.8</td></tr><tr><td align="center" valign="middle" >3</td><td align="center" valign="middle" >628</td></tr><tr><td align="center" valign="middle" >4</td><td align="center" valign="middle" >666</td></tr><tr><td align="center" valign="middle" >ALAT</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Normal</td><td align="center" valign="middle" >683.3</td><td align="center" valign="middle"  rowspan="2"  >0.462</td></tr><tr><td align="center" valign="middle" >Increased</td><td align="center" valign="middle" >1198.2</td></tr><tr><td align="center" valign="middle" >ASAT</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Normal</td><td align="center" valign="middle" >639.4</td><td align="center" valign="middle"  rowspan="2"  >0.196</td></tr><tr><td align="center" valign="middle" >Increased</td><td align="center" valign="middle" >1039.6</td></tr><tr><td align="center" valign="middle" >Dipstick leukocyturia</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >1385.1</td><td align="center" valign="middle"  rowspan="2"  >0.345</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >706.3</td></tr><tr><td align="center" valign="middle" >Dipstick hematuria</td><td align="center" valign="middle" ></td><td align="center" valign="middle" ></td></tr><tr><td align="center" valign="middle" >Yes</td><td align="center" valign="middle" >2685.5</td><td align="center" valign="middle"  rowspan="2"  >0.999</td></tr><tr><td align="center" valign="middle" >No</td><td align="center" valign="middle" >785.7</td></tr></tbody></table></table-wrap></table-wrap-group><p>The recent introduction of information and screening campaigns could explain this result. Unlike Caucasians, our patients had low alcohol consumption and smoking [<xref ref-type="bibr" rid="scirp.99628-ref27">27</xref>]. The mean BMI of this population was similar to Naga et al. findings [<xref ref-type="bibr" rid="scirp.99628-ref28">28</xref>]. This increased BMI promotes liver fibrosis and carcinogenesis, hence the need for lifestyle modifications [<xref ref-type="bibr" rid="scirp.99628-ref29">29</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref30">30</xref>]. Pre-therapeutic workup shows moderate to severe fibrosis among the study population. This is probably due to long and slow evolution of the disease and late diagnosis, usually with complications, in Africa [<xref ref-type="bibr" rid="scirp.99628-ref31">31</xref>]. Only two over three patients performed HCV viral load, due to the high cost of this exam. Half of them had a high viral load, similar to Sonderup et al. reports [<xref ref-type="bibr" rid="scirp.99628-ref32">32</xref>]. Genotype testing revealed a type 4 predominance similar to Njouom et al. in south-Cameroon and Ndong-Atome et al. in Gabon [<xref ref-type="bibr" rid="scirp.99628-ref33">33</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref34">34</xref>]. Although genotypes 1 and 4 predominate in SSA, genotype 4 is most frequent in central Africa [<xref ref-type="bibr" rid="scirp.99628-ref31">31</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref32">32</xref>].</p><p>The mean eGFR was 112.9 &#177; 31.9 ml/min/1.73 m<sup>2</sup>. Our findings were close to those from Saddadi et al. and Tsui et al. respectively in Iran and the United States of America (USA) [<xref ref-type="bibr" rid="scirp.99628-ref27">27</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref35">35</xref>]. Reduced eGFR was found in 4 (6.2%) patients. This prevalence was higher than those from Saddadi et al. (0.6%) and Tsui et al. (2%) [<xref ref-type="bibr" rid="scirp.99628-ref27">27</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref35">35</xref>]. This discrepancy could be due to the difference in population and the late diagnosis of the disease. A high prevalence of albuminuria (89.2%) was found in this population contrasting with the 4% and 8.3% found by Saddadi et al. and Huang et al. respectively [<xref ref-type="bibr" rid="scirp.99628-ref35">35</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref36">36</xref>]. An explanation of this difference could be the elevated albuminuria threshold used by Saddadi et al. (500 mg/24 h) and the different methods for determining albuminuria. Otherwise, moderate albuminuria prevalence was similar to Liangpunsakul et al. findings [<xref ref-type="bibr" rid="scirp.99628-ref29">29</xref>]. However, severe albuminuria prevalence in our population was high. This discrepancy could be explained by the disease age (high in Africa’s population) and probably increased by the intake of nephrotoxic drugs. Proteinuria and hematuria found at urine dipstick could reinforce the hypothesis of HCV-related glomerular disease, mainly membranoproliferative glomerulonephritis and membranous nephropathy [<xref ref-type="bibr" rid="scirp.99628-ref35">35</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref37">37</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref38">38</xref>]. Leukocyturia, on the contrary, seems to correlate with the interstitial involvement of HCV infection [<xref ref-type="bibr" rid="scirp.99628-ref39">39</xref>].</p><p>Advanced age, female gender, HCV genotype and albuminuria (all p &lt; 0.03) were associated with eGFR reduction in univariate analysis. Patients with type 1 and 4 genotypes seemed to have a reduced eGFR as compared to others, but the small study population reduces our capacity to make significant associations. Tsui et al. found no association between age and renal manifestation, but Liangpunsakul et al. showed an association between albuminuria, advanced age and the black race in patients with HCV infection [<xref ref-type="bibr" rid="scirp.99628-ref27">27</xref>] [<xref ref-type="bibr" rid="scirp.99628-ref29">29</xref>]. A confounding factor could be the drug intake, responsible for renal toxicity, which was found in more than half of patients. Similarly to Iseki et al., albuminuria was associated with reduced eGFR, suggesting the role of proteinuria in the progression of CKD [<xref ref-type="bibr" rid="scirp.99628-ref40">40</xref>]. However, no association with albuminuria was observed.</p><p>This study should be interpreted in light of some limitations. Our study population was small compared to other studies on this subject. We excluded many patients with confounding factors for proteinuria to avoid bias. Another limitation was biological and anatomopathological exams. Urine sediment, which is more reliable for hematuria and leukocyturia, was not performed. Due to limited financial issues, just a urine dipstick was realized. No kidney biopsy was performed in this population.</p></sec><sec id="s5"><title>5. Conclusion</title><p>This study is the first of its type carried out in Cameroon. The prevalence of renal manifestations of HCV infection is high, led by proteinuria and reduced/low eGFR. Advanced age, female gender, HCV genotype 1 and 4, and albuminuria were associated with eGFR reduction. A regular follow-up of these patients with eGFR determination and urinalysis is necessary for the early diagnosis of renal manifestations and the implementation of nephroprotective measures.</p></sec><sec id="s6"><title>Acknowledgements</title><p>We thank all the staff of the Gastroenterology and laboratory units at of the Yaounde University Teaching Hospital and all the staff of the Medical Centre “La Cath&#233;drale”.</p></sec><sec id="s7"><title>Availability of Data and Materials</title><p>The dataset analyzed during this study is not publicly available due to individual privacy issues. It could be available from the corresponding author on a reasonable request.</p></sec><sec id="s8"><title>Authors’ Contribution</title><p>Conception and Design: JN, MSMN, MPK, FJKF. Data collection: MSMN, MPK, FJKF, MTS. Administrative support: MTS, MPK, FJKF, JN, FAA, MTS. Data analysis and Interpretation: MSMN, MPK, SRSN, ANN. Drafting of the manuscript: SRSN, MSMN, MPK. Reviewing Manuscript: MTS, FJKF, VAM. All the authors read and approved the final draft for publication.</p></sec><sec id="s9"><title>Funding</title><p>No funding was received for this study.</p></sec><sec id="s10"><title>Conflicts of Interest</title><p>The authors declare that they have no competing interests.</p></sec><sec id="s11"><title>Ethical Consideration</title><p>This work was approved by the institutional review board of the Higher Institute of Health Sciences, Universit&#233; des Montagnes, Bangangte, Cameroon (registration number 2014/82/UdM/PR/CAB/CIE). Administrative authorization from the Yaounde University Teaching Hospital, Medical Centre “La Cath&#233;drale” was obtained. This work was carried out in accordance with the declarations of Helsinki [<xref ref-type="bibr" rid="scirp.99628-ref41">41</xref>]. All ethical rules involving research on disadvantaged groups such as prisoners have been respected [<xref ref-type="bibr" rid="scirp.99628-ref42">42</xref>]. Patients were informed and a signed consent forms was collected from each participant who was equally free to attend the study without any outside constraint. This work is reported in compliance with the STROBE checklist.</p></sec><sec id="s12"><title>Cite this paper</title><p>Kowo, M.P., Njonnou, S.R.S., Ngninzeko, M.S.M., Andoulo, F.A., Ndam, A.N., Sartre, M.T., Moor, V.A., Ngongang, J. and Kaze, F.F. (2020) Prevalence and Determinants of Kidney Markers among Subjects with Hepatitis C Virus Infection. Open Journal of Nephrology, 10, 85-101. https://doi.org/10.4236/ojneph.2020.102010</p></sec><sec id="s13"><title>List of Abbreviations</title><p>ACR: Albuminuria/creatinuria ratio</p><p>BMI: Body mass index</p><p>CHVC: Chronic viral Hepatitis C</p><p>CKD: Chronic kidney disease</p><p>CKD-EPI: Chronic Kidney Disease Epidemiology Collaboration</p><p>eGFR: estimated glomerular filtration rate</p><p>HCV: Hepatitis C virus</p><p>MDRD: Modification of Diet in Renal Disease</p><p>MHD: Maintenance hemodialysis</p><p>MPGN: Membranoproliferative glomerulonephritis</p><p>SSA: sub-Saharan Africa</p><p>SPSS: Statistical Package for Social Sciences</p><p>USA: United States of America</p></sec></body><back><ref-list><title>References</title><ref id="scirp.99628-ref1"><label>1</label><mixed-citation publication-type="other" xlink:type="simple">World Health Organization (2017) Global Hepatitis Programme. 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