Prevalence of Chronic Kidney Disease (CKD) among Patients Co-infected with  COVID-19 and HIV at the University of Ilorin Teaching Hospital, Ilorin, Nigeria

Prevalence of Chronic Kidney Disease (CKD) among Patients Co-infected with COVID-19 and HIV at the University of Ilorin Teaching Hospital, Ilorin, Nigeria | Research Square window.SnipcartSettings = { analytics: { enabled: false } }; (function() { var accessVector = localStorage.getItem('access_vector') || ''; window.dataLayer = window.dataLayer || []; if (accessVector) { window.dataLayer.push({ user: { profile: { profileInfo: { snid: accessVector } } } }); } })(); (function(w,d,s,l,i){w[l]=w[l]||[];w[l].push({'gtm.start':new Date().getTime(),event:'gtm.js'});var f=d.getElementsByTagName(s)[0],j=d.createElement(s),dl=l!='dataLayer'?'&l='+l:'';j.async=true;j.src='https://www.googletagmanager.com/gtm.js?id='+i+dl;f.parentNode.insertBefore(j,f);})(window,document,'script','dataLayer','GTM-K279D39R'); Browse Preprints In Review Journals COVID-19 Preprints AJE Video Bytes Research Tools Research Promotion AJE Professional Editing AJE Rubriq About Preprint Platform In Review Editorial Policies Our Team Advisory Board Help Center Sign In Submit a Preprint Cite Share Download PDF Research Article Prevalence of Chronic Kidney Disease (CKD) among Patients Co-infected with COVID-19 and HIV at the University of Ilorin Teaching Hospital, Ilorin, Nigeria Blessing Iveren Olusanjo, Mariam K. Sulaiman, Timothy Olusegun Olarenwaju, and 5 more This is a preprint; it has not been peer reviewed by a journal. https://doi.org/ 10.21203/rs.3.rs-8902316/v1 This work is licensed under a CC BY 4.0 License Status: Under Revision Version 1 posted 17 You are reading this latest preprint version Abstract Background Coronavirus disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), remains a significant global health challenge. People living with human immunodeficiency virus (HIV) may face an elevated risk of severe complications, particularly those with low CD4 counts, high viral loads, advanced clinical disease, or antiretroviral therapy (ART) non-adherence. Lockdown-related ART disruptions further compounded these risks. This study aimed to evaluate the prevalence of Chronic Kidney Disease (CKD) among HIV patients co-infected with COVID-19. Methods A hospital-based cross-sectional study was conducted with 423 participants. SARS-CoV-2 status was determined via real-time polymerase chain reaction (PCR). CKD was defined as an estimated glomerular filtration rate (eGFR) < 60 mL/min/1.73 m² (using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) without race coefficient) calculated using serum creatinine values obtained via Jaffe’s method and/or proteinuria ≥ + 1 identified through dipstick urinalysis persistent over three months. Data were analyzed using SPSS version 21, Student’s t-tests for continuous variables and chi-square tests for categorical associations. Results The prevalence of COVID-19 infection was 13.5%. Notably, 56.6% of infected individuals had received two or more vaccine doses, and 73.5% were asymptomatic. The overall prevalence of CKD was 8.4%, with a higher proportion observed in females. Among HIV/COVID-19 co-infected patients, CKD prevalence was 1.5%. HIV viral suppression (p = 0.003) and proteinuria ≥ + 1 (p < 0.001) were significantly associated with CKD status. Conclusions The study indicates that COVID-19 co-infection does not result in a higher CKD among HIV patients compared to those without the virus. However, prolonged ART duration, gender, education level, and socio-occupational status were identified as significant risk factors. Additionally, the high infection rate of COVID-19 among the vaccinated participants suggests a need for further research into vaccine efficacy and the impact of various COVID-19 vaccines within this cohort. COVID-19 Chronic Kidney Disease Renal dysfunction Co-infection HIV Africa Nigeria Figures Figure 1 Background Since the emergence of Coronavirus disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there have been over 760 million cases and 6 million deaths globally. Nigeria has recorded approximately 267,000 cases, with Kwara State accounting for over 4,600 cases and 64 deaths [ 1 ]. While 80% of COVID-19 patients experience mild or asymptomatic courses, severity is significantly influenced by age, sex, and underlying co-morbidities, including human immunodeficiency virus (HIV) infection [ 2 , 3 ]. The pathophysiology of SARS-CoV-2 involves a spike protein with a receptor-binding domain (RBD) that targets angiotensin-converting enzyme 2 (ACE2) receptors. Because ACE2 is ubiquitous, the virus can directly replicate within huan renal tissue [ 4 ]. Consequently, kidney damage occurs in approximately 30% of COVID-19 cases [ 5 ]. In people living with HIV (PLWH), the risk of renal dysfunction is already elevated due to their abnormal humoral and T-cell mediated immune response that can lead to opportunistic infections especially among patients with low cluster of differentiation 4 (CD4) cell counts, high viral load, advanced disease, and those not on antiretroviral therapy (ART) [ 6 ]. 48% of HIV patients at the University of Ilorin Teaching Hospital (UITH) were previously found to have chronic kidney disease (CKD) [ 7 ]. PLWH are particularly vulnerable to severe COVID-19 outcomes due to potential immune system impairment, characterized by delayed antibody responses and prolonged disease courses. Factors such as low CD4 cell counts, high viral loads, and advanced disease stages increase the probability of infection two- to three-fold [ 2 ]. Furthermore, the COVID-19 pandemic caused significant disruptions to ART for over 11.5 million people worldwide, potentially exacerbating HIV-associated nephropathy and other complications [ 2 , 6 ]. Renal dysfunction in these patients may stem from various pathways: direct viral cell injury, immune-mediated damage, systemic inflammation, or antiviral drug-induced nephrotoxicity. These pathways can lead to Acute Kidney Injury (AKI), progression of CKD, or end-stage renal disease [ 5 ]. Despite the availability of vaccinations, immunocompromised individuals may not achieve full protection, and breakthrough infections of COVID-19 remain a concern for those with co-morbidities [ 3 ]. Current data on the clinical outcomes of HIV and COVID-19 co-infection remain conflicting. While both viruses are established independent causes of renal disease, the impact of their co-existence on renal prevalence is not fully understood [ 8 ]. Given the high burden of HIV in Sub-Saharan Africa and the potential for increased mortality from synergistic renal injury in which CKD accounted for 1.2 million deaths globally, with 48% of HIV patients found to have CKD at University of Ilorin Teaching Hospital (UITH) [ 5 , 7 ], there is an urgent need for local data. Therefore, this study aims to determine the prevalence of CKD among HIV patients co-infected with COVID-19 at UITH, Ilorin, Nigeria. Methodology Study design and setting This hospital-based cross-sectional study was conducted at the ART clinic of UITH, Ilorin, Nigeria. UITH is a 600-bed tertiary healthcare facility in Kwara State, North-central Nigeria, which records approximately 12,000 annual admissions. The ART clinic operates from Monday to Thursday, attending to an average of 40 patients living with HIV daily, totaling approximately 1,120 patient visits per month [9]. Sample size, sampling technique and participant recruitment A systematic random sampling technique was employed to recruit participants from the ART clinic. The sampling frame was established based on the monthly clinic volume (N = 1,120) and the calculated sample size (n = 423) by Fischer’s formula using the 48% prevalence of CKD observed among HIV patients in UITH [7,10]. The sampling interval (k) was determined as follows: K=N/n =1120/423=2.6, approx. 3 Consequently, every third patient from the clinic register was invited to participate until the required sample size was achieved. Study population Inclusion criteria Participants included for the study were those who had confirmed diagnosis of HIV infection, age above 18 years at the time of recruitment, registered and receiving antiretroviral therapy at the UITH ART clinic for a minimum of six months with written informed consent. Exclusion criteria Patients with known pre-existing CKD or those undergoing renal replacement therapy (RRT) during the course of the study, patients with sickle cell anaemia and those unable or unwilling to return for the follow-up assessment at three months Measurement of variables The participants of the study filled questionnaires about demographic characteristics and medical history, laboratory tests were also conducted. Collection of specimen was done on two occasion (three months apart). Oropharyngeal and nasopharyngeal swabs, veinular blood and midstream urine samples were collected for the diagnosis of COVID-19 and determination of renal dysfunction during the first visit. On the second visit (after three months), veinular blood samples and midstream urine samples only were collected and analyzed for the confirmation of CKD. Before the start of the study, all data and sample collectors were trained. Swabs collected were transported in viral transport mediums (VTMs) placed in cold packs as soon as possible to the laboratory for the detection of SARS-COv-2 genes [11]. Nucleic acid was extracted from the swabs using a kit-based column method. The DaAnGene RNA Purification Kit (DaAn Gene Co., Ltd., Guangzhou, China) was used for the purification of SARS-CoV-2 RNA according to the manufacturer’s instructions [12]. Samples were analyzed using probe-based multiplex RT-qPCR to determine the presence of SARS-CoV-2. The GeneFinder™ COVID-19 Plus Real Amp Kit (OSANG Healthcare, Gyeonggi-do, South Korea) was utilized for the identification of SARS-CoV-2 RNA. This kit targets the RdRp, E, and N genes [13]. Venous blood was collected for serum creatinine analysis. The estimated glomerular filtration rate (eGFR) was calculated using the 2021 CKD-EPI creatinine equation without the race coefficient, as recommended by the National Kidney Foundation. CKD was defined as an eGFR < 60 mL/min/1.73m 2 when persistent after three months for the purpose of this study [14]. Fresh mid-stream urine samples were analyzed by dipstick urinalysis using URS-10A by Abbonn health care(UK) test kit according to manufacturer’s instruction) to determine pH, specific gravity, proteinuria, and the presence of leukocytes, nitrites, and ketones [15]. Virological Profile (HIV viral load (copies/mL) results were obtained from the patients’ medical record during their routine laboratory testing at the ART clinic, UITH at the time of the study. Variables of interest Detection of SARS-CoV-2 The probe-based multiplex RT-qPCR (using GeneFinder TM COVID-19 plus real amp kit) assay targets the presence of one or more of the following genes: the RNA-dependent RNA polymerase- (RdRp), envelope- (E), nucleotidecapsid- (N), spike- (S) or membrane protein (M) it contains an Internal Control which targets the human endogenous RNase P gene. According to manufacturer’s instructions, a sample was considered positive for SARS-CoV-2 when all the three genes were detected or the combinations of: RdRP with E or RdRP and N. in a situation where a single gene was detected (only RdRP-gene or only N-gene) or a combination of E and N, the result was considered not reliable and tests repeated to confirm the sample was positive for SARS-CoV-2. The presence of only the E gene was interpreted as SARS-CoV-2 positive. Results with high cycle threshold or curves showed that the sample was positive while results with lower cycle threshold or curves indicate a negative result [15,16]. Determination of CKD Serum creatinine in the blood samples collected was measured by Jaffe’s reaction and used to determine estimated glomerular filtration rate (eGFR) using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation without race. According to the National Kidney Foundation(NKF), Normal eGFR = ≥ 60 mL/min/1.73m 2 . Chronic Kidney Disease was defined as eGFR < 60 mL/min/1.73 m 2 when persistent after three months for the purpose of this study [14,16]. Proteiunuria ≥+1 was considered significant Data extraction and statistical analysis Data such as HIV-related characteristics e.g viral load (copies/mL), and antiretroviral therapy before COVID-19 diagnosis was obtained from the ART clinic of UITH. Also, COVID-19-related clinical symptoms and other underlying conditions were extracted from the questionnaires and analyzed using SPSS® version 21 (SPSS Inc, Chicago Il.) computer software package. Frequency tables were used to describe both categorical and quantitative variables, continuous variables was analyzed by median and interquartile ranges, for variables such as Creatinine, eGFR, pH, Viral Load), the Independent Student’s t-test was used to compare means between groups. For categorical variable; frequency, proportions and percentages was used, chi-square was used to assess association between the variables (gender, education, proteinuria) and compare differences between groups. Ethical approval Ethical approval was obtained from the Ethical Review Committee (ERC) of UITH, Ilorin, before the commencement of the study. Archival materials retrieved for this study was handled with care and personal data of participants were handled with confidentiality Operational definitions The following definitions were used for the variables in this study A sample was considered positive for SARS-CoV-2 if all three genes, if specific combinations (RdRP with E, or RdRP with N) or E gene alone were detected and a High cycle threshold (Ct) values or characteristic amplification curves [15]. Dipstick proteinuria of 1+ or greater was taken as significant. HIV Viral load above 100,000 copies per milliliter of blood is considered to be high, viral load below 10,000 copies per milliliter of blood is considered low. Viral suppression or undetectable HIV viral load is less than 20 copies per milliliter of blood [17]. Chronic Kidney Disease(CKD) was defined as eGFR < 60 mL/min/1.73 m 2 and/or for the purpose of this study which was persistent when measured after three month [14]. Results Out of the total enrollment of 423 patients in this study, 393 patients (92.89%) return rate) provided complete and analyzable data. Socio-demographic and clinical characteristics of the study population The study population had a mean age of 46.1 ± 11.5 years, with a range of 18 to 80 years. The most represented age cohort was the 45–54 year group, accounting for 32.3% (n=127) of the total sample. A significant female preponderance was observed, comprising of 72.3% (n=284) of the participants compared to 27.7% (n=109) for males. Regarding marital status, the majority of the respondents (69%, n=271) were married. Furthermore, a high proportion of the cohort had limited formal education, with 18.3% (n=72) having attained only primary education or no formal schooling. All participants were receiving ART at the time of the study. Analysis of treatment duration revealed that the majority (70.5%, n=277) had been on ART for more than 5 years, while 21.9% (n=86) had been on treatment for 1–5 years, and 7.6% (n=30) for less than one year. Co-morbidities observed include ulcers (6.1%), hypertension (4.6%), diabetes mellitus (1.5%), and asthma (0.5%). A family history of renal disease was reported by only 1.3% (n=5) of the subjects. While awareness of COVID-19 was universal among participants, only 9.7% (n=38) had undergone previous testing, all of whom reported negative results. Vaccination coverage of COVID-19 was 53.2% (n=209); of these, 72.7% (n=152) had received more than one dose, while 27.3% (n=57) had received a single dose. Majority of participants (83.3%, n=327) remained asymptomatic. Frequently reported symptoms were body weakness (7.6%), catarrh and cough (3.8%), high fever (1.5%), and malaria-like symptoms (0.8%). Table 1 shows that males had significantly higher levels of education, with 67.9% attaining secondary education or higher compared to 23.9% of females (p<0.001). Occupation and ART duration also showed significant gender-based differences (p<0.001). Regarding laboratory parameters, males exhibited significantly higher mean serum creatinine (101.97 vs 81.86 μmol/L,p80 mL/min/1.73m 2 ). In urinalysis, females showed a significantly higher prevalence of hematuria (11.3% vs 5.5%, p<0.001), whereas males had a higher prevalence of proteinuria (p<0.001). No significant differences were observed in age, vaccination status, or underlying health conditions. Table 1: Comparison of sociodemographic, clinical, and laboratory parameters by gender (N=393) Characteristics Male (n=109) Female (n=284) P-Value Age (years), Mean ± SD 48.28 ±12.36 45.29 ± 11.11 0.105 Education, n (%) <0.001 - Illiterate 13 (11.9) 162 (57.0) - Primary 22 (20.2) 52 (18.3) - Secondary 30 (27.5) 6 (2.1) - Graduate 44 (40.4) 62 (21.8) Marital Status, n (%) 0.094 - Married 84 (77.1) 183 (64.4) - Single 14 (12.8) 20 (7.0) - Separated/Widowed 11 (10.1) 81 (28.6) Occupation, n (%) <0.001 - Trader 51 (46.8) 198 (69.7) - Civil Servant 39 (35.8) 64 (22.5) - Farmer 10 (9.2) 8 (2.8) - Student / None 9 (8.3) 14 (4.9) COVID-19 Vaccination Status, n (%) 0.110 - Vaccinated 48 (44.0) 160 (56.4) - Not Vaccinated 61 (56.0) 124 (43.6) ART Duration, n (%) <0.001 - 5 years 79 (72.5) 193 (68.1) Underlying Health Condition, n (%) 10 (9.2) 52 (18.3) 0.989 Laboratory Parameters Creatinine (μmol/L), Mean 101.97 81.86 <0.001 eGFR (mL/min/1.73m 2 ), Mean 84.73 80.88 <0.001 HIV Viral Load, Mean 20,528.15 7,543.22 0.038 Urinary pH, Mean 6.35 6.34 <0.001 Specific Gravity, Mean 1.013 1.015 0.270 Proteinuria (Trace or Positive) 26 (23.9) 59 (20.9) <0.001 Hematuria (Presence of Blood) 6 (5.5) 32 (11.3) <0.001 Leucocytes (Positive) 30 (27.5) 116 (40.8) 0.935 Significant P-values (<0.005) are highlighted for easy observation Prevalence of COVID-19 A prevalence of 13.5% of COVID-19 infection was found among the participants. The mean ages and standard deviation of the HIV patients co-infected with COVID-19 were 47.11 ± 9.978 years ranging between 28 years to 68 years. The highest age group in the study was 45 to 54 (32.1%) of the total sample indicates that patients within this age group were mostly co-infected with COVID-19. COVID-19 co-infection was observed in more female (69.8%) compared to the male (30.2%). 73.5% asymptomatic cases was observed and 56.6% of the COVID-19 infection was observed among the vaccinated participants. The study found significant differences in COVID-19 vaccination status between groups (p<0.001), although the absolute percentage of vaccinated individuals was similar (56.6% in the co-infected group vs. 52.4% in the control). Among those vaccinated, the co-infected group had a higher proportion of individuals who had received two or more doses (73.3% vs. 37.1%), though this trend toward higher dosage did not reach independent statistical significance (p=0.065). Significant associations with COVID-19 infection were also found for gender (p=0.001), occupation (p<0.001), and underlying health conditions (p<0.001), particularly hypertension. Table 2 shows that patients co-infected with COVID-19 exhibited significantly higher viral loads (p=0.001) and higher urinary pH levels (p<0.001) compared to those without COVID-19. Significant associations with COVID-19 status were observed regarding gender (p=0.001), educational background (p=0.020), occupation (p<0.001) and duration of ART usage (p<0.001). Furthermore, underlying health conditions; specifically hypertension and ulcers were more prevalent in the co-infected group (p<0.001). While vaccination status differed significantly (p0.05). Table 2: Sociodemographic, clinical, and laboratory characteristics of HIV Patients by COVID-19 status (N=393) Characteristics HIV with COVID-19 (n=53) HIV without COVID-19 (n=340) P-Value Age (years), Mean ± SD 47.11 ± 9.98 45.96 ±11.97 0.602 Gender, n (%) 0.001 - Male 16 (30.2) 93 (27.4) - Female 37 (69.8) 247 (72.6) Marital Status, n (%) 0.591 - Married 39 (73.5) 228 (67.1) - Single 3 (5.7) 31 (9.1) - Widow(er) 10 (18.9) 57 (16.6) Education, n (%) 0.020 - Illiterate 8 (15.1) 50 (14.7) - Primary 10 (18.9) 63 (18.5) - Secondary/Above 13 (24.5) 111 (32.2) - Graduate 22 (41.5) 115 (33.8) Occupation, n (%) <0.001 - Trader 29 (54.7) 208 (61.2) - Civil Servant 14 (26.4) 71 (19.3) - Farmer 3 (5.7) 16 (4.7) - Others 7 (13.2) 45 (14.8) COVID-19 Vaccination Status, n (%) <0.001 - Vaccinated 30 (56.6) 178 (52.4) - Not Vaccinated 23 (43.4) 159 (46.7) COVID-19 Vaccine Doses, n (%) 0.065 - One dose 7 (23.3) 51 (15.0) - Two or more 22 (73.3) 126 (37.1) ART Duration, n (%) <0.001 - 5 years 36 (67.9) 235 (69.3) Underlying Condition, n (%) <0.001 - Hypertension 7 (13.2) 13 (3.8) - Diabetes 1 (1.9) 4 (1.2) - None 39 (73.6) 292 (90.4) Laboratory Parameters Viral Load, Mean SD 11924.63 76,939.2 6223.58 0.001 Creatinine (μmol/L), Mean SD 86.79 91.60 0.781 eGFR (mL/min/1.73m^2), Mean SD 82.61 20.41 77.74 15.87 0.267 Urinary pH, Mean SD 6.35 6.30 <0.001 Proteinuria (trace or positive) 8(15.0) 77(22.7) 1.000 Significant P-values (<0.005) are highlighted for easy observation Prevalence of CKD among all participants The prevalence of CKD among all participants observed in this study is 8.4% with the mean ages and standard deviation of 54.33±9.78 years ranging between 36 years to 70years. The highest age group in the study was 45 to 54years. More female (66.7%) of the total sample had CKD compared to the male (30.2%). Table 3 shows the comparison between HIV patients with CKD (n=33) and without CKD (n=360) shows that the CKD group was significantly older on average and had a higher proportion of males (p=0.024). From a clinical perspective, the CKD group demonstrated significantly higher creatinine and lower eGFR (p<0.001), as well as a higher prevalence of proteinuria (p<0.001) and more acidic urinary pH (p<0.001). Notably, viral load was significantly lower in the CKD group (p=0.003). No significant differences were found in vaccination status, ART duration, or underlying health conditions between the two groups (p>0.05 Table 3: Sociodemographic, clinical, and laboratory characteristics of HIV Patients by CKD Status (N=393) Characteristics HIV with CKD (n=33) HIV without CKD (n=360) P-Value Age (years), Mean ± SD 54.33 ± 9.78 45.37 ± 11.40 0.137 Gender, n (%) 0.024 - Male 11 (33.3) 98 (27.2) - Female 22 (66.7) 265 (72.8) Marital Status, n (%) 0.992 - Married 22 (66.7) 245 (68.1) - Single 1 (3.0) 33 (9.2) - Separated 2 (6.1) 15 (4.2) - Widow(er) 8 (24.2) 67 (18.6) Education, n (%) 0.211 - Illiterate 6 (18.2) 52 (14.4) - Primary 8 (24.2) 65 (18.1) - Secondary 11 (33.3) 114 (31.7) - Graduate 8 (24.2) 129 (35.8) Occupation, n (%) 0.689 - Trader 20 (60.6) 229 (63.6) - Civil Servant 10 (30.3) 93 (25.8) - Farmer 2 (6.1) 16 (4.4) - Others 1 (3.0) 22 (6.1) COVID-19 Vaccination Status, n (%) 0.299 - Vaccinated 24 (72.7) 184 (51.1) - Not Vaccinated 9 (27.3) 176 (48.9) COVID-19 Vaccine Doses, n (%) 0.148 - One dose 6 (25.0) 52 (28.3) - Two or more 18 (75.0) 130 (70.7) ART Duration, n (%) 1.000 - 5 years 21 (63.6) 251 (69.7) Underlying Condition, n (%) 0.999 - Hypertension 2 (6.0) 17 (4.7) - Diabetes 1 (3.0) 4 (1.1) - None 27 (81.8) 302 (84.2) Viral Load, Mean± SD 1,037.96±4077.83 12,083.70±79009.32 0.003 Creatinine (μmol/L),Mean± SD 142.39±68.15 82.40±14.61 <0.001 eGFR(mL/min/1.73m2),Mean± SD 47.15±11.32 85.14±17.33 <0.001 Urinary pH, Mean ± SD 6.23 ± 0.34 6.35 ± 0.56 <0.001 Proteinuria(trace or positive), n (%) 15 (45.4) 70 (19.4) <0.001 Significant P-values (<0.005) are highlighted for easy observation Prevalence of CKD among patients co-infected with COVID-19 and HIV The prevalence of CKD among HIV patients co-infected with COVID-19 was found to be 1.5% with mean ages and standard deviation of 49.33 ±7.992 ranging from 39 years to 62 years of age. Both male and female were affected equally. Table 4 shows that among HIV patients co-infected with COVID-19, those with CKD (n=6) exhibited significantly impaired renal markers compared to those without CKD (n=47). Mean serum creatinine was significantly higher (145.67 vs.84.70μmol/L, p=0.002), while eGFR was significantly lower (49.17 vs.81.38mL/min/1.73m 2 , p<0.001). Furthermore, the CKD group presented with significantly more acidic urinary pH levels (6.08 vs. 6.33, p<0.001) and lower specific gravity (1.008 vs. 1.017, p<0.001). Interestingly, despite the physiological differences in kidney function, there were no statistically significant variations in sociodemographic factors, ART duration, or vaccination status between the two co-infected subgroups (p>0.05). Viral load levels were lower in the CKD group, though this difference did not reach statistical significance (p=0.316). A visual comparison of these key demographic and clinical parameters across all study cohorts including the general participant, HIV/COVID-19 co-infected groups, and those with CKD is presented in Figure 1. Table 4: Sociodemographic, clinical, and laboratory characteristics of COVID-19 co-infected HIV Patients by CKD Status (n=53) Characteristics Co-Infected with CKD (n=6) Co-Infected without CKD (n=47) P-Value Age (years), Mean ± SD 49.33 ±7.99 46.83 ± 10.24 0.247 Gender, n (%) 0.622 - Male 3 (50.0) 13 (27.6) - Female 3 (50.0) 34 (72.3) Marital Status, n (%) 0.999 - Married 4 (66.7) 35 (74.5) - Single/Separated 1 (16.7) 3 (6.4) - Widow(er) 1 (16.7) 8 (17.0) Education, n (%) 0.669 - Illiterate 1 (16.7) 7 (14.9) - Primary 3 (50.0) 7 (14.9) - Secondary/Graduate 2 (33.3) 33 (70.3) COVID-19 Vaccination Status, n (%) 0.949 - Vaccinated 6 (100.0) 24 (51.1) - Not Vaccinated 0 (0.0) 23 (48.9) COVID vaccine Doses, n (%) 0.787 - One dose 1 (16.7) 6 (12.8) - Two or more 5 (83.3) 17 (36.2) ART Duration, n (%) 0.766 - 1–5 years 4 (66.7) 10 (21.2) - > 5 years 2 (33.3) 34 (73.3) Underlying Condition (Hypertension), n (%) 1 (16.7) 6 (12.8) 0.733 Creatinine (μmol/L), Mean ± SD 145.67 ± 61.89 84.70 ± 12.88 0.002 eGFR (mL/min/1.73m 2 ), Mean ± SD 49.17 ± 12.47 81.38 ± 12.16 <0.001 Viral Load, Mean± SD 196.67±432.74 6,992.98±38997.56 0.316 Urinary pH, Mean ± SD 6.08 ± 0.20 6.33 ± 0.51 <0.001 Specific Gravity, Mean 1.008 1.017 <0.001 Proteinuria (trace or positive), n (%) 1 (16.7) 7 (14.8) 0.997 Discussions Chronic kidney disease among HIV patients may lead to severe complications if not early diagnosed and properly managed [7]. The outbreak of COVID-19 is a major concern among co-infected patients for effective management in other to prevent more complications and higher mortality rate among the population. Our findings corroborate several regional reports indicating that females are disproportionately affected by HIV, with a male-to-female ratio of 0.4:1. This trend aligns with studies by Dada et al. [7], Wools-Kaloustian et al.[18], and Han et al.[19], who reported ratios of 0.8:1, 0.5:1, and 0.3:1, respectively. This gender disparity may be attributed to deep-seated socio-cultural factors, gender inequalities that limit preventive agency, and biological vulnerabilities. Conversely, our findings contrast with Agaba et al., who reported a male predominance (60.5%) in Jos [20]. These regional variations may stem from distinct behavioral attitudes, such as the use of unsterilized instruments especially the use of manual hair shavers and nail cutters or the prevalence of polygamous practices in specific Northern regions, which traditionally increase the number of sexual partners among males. The cohort’s mean age of 46.1 ± 11.5 years is remarkably consistent with data from Uganda reported by Mwemezi et al. [21]. However, this reflects an aging trend compared to earlier Nigerian cohorts where mean ages ranged from 34.6 to 42.3 years [20, 22, 23,]. The shift toward the 45–54 age group (32.3%) suggests that middle-aged adults, who are most active socio-economically and sexually, now represent the primary demographic at risk. This demographic shift is further complicated by marital status; 69% of our participants were married, a finding supported by Orire et al. [24] and Nabukenya et al. [25], emphasizing the risk of intra-marital transmission if virological control is not strictly maintained. Furthermore, the high prevalence of infection among participants with limited formal education (49.6%) suggests that health literacy is a critical barrier to disease control. The observed intersection between female gender and lower educational attainment likely compounds HIV risk, as limited access to health information often results in poor management of sexual health and higher transmission rates due to lack of awareness. A significant proportion of participants (70.5%) had been on ART for over five years, which likely accounts for the high rate of viral suppression (66.4%). Our suppression rates are comparable to findings from Togo (69.2%) and Kenya (62%) [26,27], though they remain lower than the 74–86% reported in other Nigerian, Cameroonians and Congolese cohorts [28,29,30]. Importantly, our results exceeded the UNAIDS global average of 47% reported in 2018 [31], indicating high treatment efficacy within this center. However, the prolonged use of ART necessitates routine monitoring of renal biomarkers to prevent drug-induced nephrotoxicity over time. The observed COVID-19 prevalence of 13.5% is higher than the pooled global prevalence (2–3.8%) [32] but lower than the 26.9% reported in recent meta-analyses [33]. The high level of COVID-19 awareness among participants likely contributed to the relatively low transmission rate. Notably, 73.5% of co-infected participants were asymptomatic, supporting the findings of Tian et al. [3] regarding the high frequency of asymptomatic presentations. In contrast to global reports by Massarwa [34], which indicated a male predominance in co-infections, our study found that 69.8% of co-infected patients were female. We also observed that 56.6% of co-infected individuals were vaccinated. This shows the potential for breakthrough infections in immunocompromised populations, where traditional vaccine-induced protection may be attenuated, particularly among those who received multiple doses supporting findings by Tian et al [3]. A critical finding was that co-infected patients exhibited higher HIV viral loads, lower eGFR, and higher proteinuria levels (>+1) compared to those without COVID-19. This biochemical signature suggests that SARS-CoV-2 may exacerbate renal strain in PLWH, potentially through direct viral entry into renal tubules or the systemic inflammatory response. Additionally, males exhibited higher baseline creatinine and lower pH/eGFR levels. This gender-based biochemical difference may reflect late-presentation tendencies among males, who often seek medical intervention only during severe illness. These findings emphasize that COVID-19 in HIV patients is not merely a respiratory concern but a multi-system challenge that may accelerate renal decline if not managed through rigorous monitoring of laboratory parameters. A proper understanding and early diagnosis of CKD among HIV patients may help to reduce mortality. Although, the prevalence of 8.4% observed in this study agrees with the global prevalence range of between 2-38% prevalence reported by Bertoldi et al. [35], the result obtained in this finding is lower than results obtained in Nigeria; 47.6% in Ilorin, 38% in Ile-ife, 51.8% in Jos, 15.3% in Calabar, 22.9% in the South-East, and 23.5% in the South-West [7,23,36,37,38,39,40]. This may be as a result of variations in methodology of the various studies, a single measurement of serum creatinine and albumin creatinine ratio which may not be a true representation of the obtained CKD prevalence rate was used. The overall CKD prevalence of 8.4% observed among HIV patients in this study aligns with contemporary findings across West Africa, reinforcing the high burden of renal disease in this demographic. Our results are closely comparable to a 2021 study in Ivory Coast, which reported a 10.4% prevalence among patients on highly active antiretroviral therapy (HAART) [41]. Interestingly, our prevalence is slightly lower than the 10.0%–17.6% range reported in a recent 2024 study of ART-naïve patients in Lagos, Nigeria [42]. This disparity may suggest that the established ART clinic at UITH provides a degree of renal protection through better virological control and clinical management compared to ART-naïve cohorts in other regions of Nigeria. The mean ages and standard deviation of the patients with CKD were 54.33±9.778years ranging between 36 years to 70years supporting the study conducted by Beagelehole et al.[43]. The overall 8.4% CKD prevalence in our study falls within the lower spectrum of reported rates in Sub-Saharan Africa. For instance, while we observed similarities with South Africa (8.1%) [44], our prevalence is markedly lower than studies from Ethiopia (18.2%) and Zambia (33.5%) [45,46]. Globally, our findings contrast with the D:A:D Study (Europe and Australia), which reported a much lower CKD prevalence of roughly 3.3% [47]. This discrepancy highlights the persistent biological and socio-economic vulnerability of African populations to renal injury, potentially due to a higher prevalence of the Apolipoprotein L1 (APOL1) genetic risk variants, which are less common in European cohorts [48]. The highest age group in the study was 45 to 54, accounting for 33.3% of the total sample indicates that adults are more affected by CKD either due to prolonged use of ARTs, underlying health conditions and/or other factors. Majority, comprising of 66.7% females of patients with CKD is similar to a research by Agbaji et al.[49] who reported a higher prevalence of CKD among females and contrary to Anyabolu et al.[50] who reported that there is no significant association between gender and CKD. The High serum creatinine and consequently a lower eGFR which is a measure of renal dysfunction was found to be associated with CKD in HIV subjects is in line with other earlier studies.[23,50]; This indicates impaired kidney function in the CKD group. The viral load, a measure of HIV replication in the body, was found to be significantly lower in HIV patients with CKD compared to those without CKD which is contrary to Manaye et al. [45], who reported that having viral load≥1000 copies/mm 3 was associated with CKD. 261(66.4%) of the patients had viral load count < 20copies/milliliter (Viral suppression) this may be due to efficiency in the treatment and control of the disease as 277(70.5%) of the participant have been on ARTs for more than 5 years. This is also an indication that CKD could be as a result of prolonged antiretroviral drugs. While data specifically detailing the prevalence of Chronic Kidney Disease (CKD) among people living with HIV (PLWH) co-infected with COVID-19 has been scarce, this study identifies a co-infection CKD prevalence of 1.5%. The mean age of these co-infected patients was 49.33 ± 7.99 years (range: 39–62 years), with an equal distribution across genders. These findings align with emerging global observations from the ISARIC-4C and Spanish multicenter cohorts, which suggested that PLWH with mild COVID-19 often experience clinical outcomes comparable to the general population [34,51]. However, the low prevalence in our study contrasts with reports from New York and Wuhan, where renal involvement in hospitalized co-infected patients was significantly higher [52,53]. Our results indicate that individuals co-infected with COVID-19 and CKD display a distinct laboratory profile specifically characterized by higher creatinine levels alongside lower pH and eGFR values. Despite these markers of renal strain, no significant differences were observed in other physiological parameters between the groups. This biochemical signature supports the hypothesis of a "renal hit" even in non-hospitalized COVID-19 cases, which may persist as part of the "long-tail" of COVID-19 [54]. Beyond the viral co-infection, this study identifies a complex interplay of non-viral factors that exacerbate CKD risk. We found that prolonged use of ART, gender, level of education, occupational status, and marital status were significant contributors to renal vulnerability. These findings are consistent with the Global Burden of Disease perspectives, which view HIV and COVID-19 as part of a "syndemic" where social determinants and biological factors (long-term ART toxicity) converge to worsen chronic outcomes [54]. Limitation of the study We acknowledge that although the aim of the study was achieved, insufficient fund did not allow us to dive deeper into other areas that could equally aid the better understanding of the study. These areas include; determining the COVID-19 strain(s) involved in the breakthrough infections among others. Conclusions The high level of awareness of COVID-19 prevention and control mechanisms may be responsible for the low prevalence of co-infection of HIV and COVID-19 among the participants of the study. The study also reported breakthrough infections among vaccinated participants as most participants infected with COVID-19 from the study were patients who were vaccinated with two or more doses of the COVID-19 vaccine. This suggests the need for further research to examine the effect of vaccination on the study population and the general population. A higher prevalence of CKD observed among participants who are on ART for more than five years and viral suppression is an indication that the usage of ART is a risk factor for CKD. Although HIV and COVID-19 have been reported to be responsible for CKD individually, results obtained from this study reviews that HIV Patients co-infected with COVID-19 does not have a higher prevalence of CKD. This study also reviews that other factors such as prolonged use of ART, gender, level of education, viral load, occupational and marital status can also increase the risk of having CKD. Recommendations Since a higher prevalence of CKD was observed in subjects on ART for more than five years, we recommend that a routine check should be added to effectively help manage the health of the patients. Proper education and follow up should be conducted among HIV patients. With 100% COVID-19 vaccination in the co-infected CKD subgroup, continued prioritization of booster doses for renal patients is recommended to maintain the low severity observed. Abbreviations ACE2 Angiotensin-converting enzyme 2 AKI Acute Kidney Injury ART Antiretroviral therapy CD4 Cluster of differentiation 4 CKD Chronic Kidney Disease CKD-EPI Chronic Kidney Disease Epidemiology Collaboration COVID-19 Coronavirus disease 2019 Ct Cycle threshold eGFR Estimated glomerular filtration rate ERC Ethical Review Committee HIV Human immunodeficiency virus NKF National Kidney Foundation PCR Polymerase chain reaction PLWH People living with HIV RBD Receptor-binding domain RNA Ribonucleic acid RRT Renal replacement therapy RT-qPCR Real-time quantitative polymerase chain reaction SARS-CoV-2 Severe Acute Respiratory Syndrome Coronavirus 2 UITH University of Ilorin Teaching Hospital VTMs Viral transport mediums Declarations Guidelines : We ensure that all methods carried out in this study were carried out according to standards and regulations. Ethical Approval: Obtained from the University of Ilorin Teaching Hospital(UITH) Ethical Review Committee with reference number UITH/CAT/189/19 B /278. The study was conducted in accordance with the Declaration of Helsinki. Archival materials retrieved for this study were handled with care and personal data of participants were handled with confidentiality. Availability of Data : Data from this study is available upon request from the corresponding author. Funding : No specific funding was received for this study Consent for publication : Not applicable Conflicting Interest : there is no conflicting interest among all authors. Authors' contributions BIO conceived and designed the study, participated in sample and data collection, performed the laboratory and statistical analyses, and drafted the manuscript. MKS supervised the study, assisted in the study design, oversaw the molecular analysis for SARS-CoV-2, and contributed to the writing of the manuscript. TOO co-supervised the study, assisted in the study design, and provided oversight for the CKD-specific aspects of the research. OAS participated in sample and data collection and performed laboratory analyses. STS facilitated the collection of clinical data at the ART clinic and performed the creatinine testing. CCB, SDB, and MKA performed laboratory experiments and were responsible for data acquisition. All authors read and approved the final manuscript. Acknowledgements: The authors wish to thank the staff of the ART clinic and the Molecular Diagnostic and Research Laboratory at the University of Ilorin Teaching Hospital for their technical support. References World Health Organization. WHO Coronavirus (COVID-19) Dashboard with Vaccination Data. Geneva: World Health Organization. 2024. https://covid19.who.int/ . Accessed 15 Jan 2024. World Health Organization. HIV & COVID-19. 2020. https://www.who.int/teams/global-hiv-hepatitis-and-stis-programmes/covid-19 . Accessed 10 May 2021. 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A Comparison of the HIV-Infected and Uninfected Populations in Western Kenya. J Int Assoc Provid AIDS Care. 2012;11(4):237–42. Han M, Zhou J, Zhang J, et al. Clinical characteristics and outcomes of HIV-infected patients with COVID-19: a systematic review and meta-analysis. J Med Virol. 2022;94(5):1852–65. Agaba EI, Agaba PA, Sirisena ND, et al. Renal disease in the acquired immunodeficiency syndrome in north central Nigeria. Niger J Med. 2003;12:120–5. Mwemezi O, Ruggajo P, Mngumi J, et al. Renal Dysfunction among HIV-Infected Patients on Antiretroviral Therapy in Dar es Salaam, Tanzania: A Cross-Sectional Study. Int J Nephrol. 2020;2020:8378947. Bah A, Kaba ML, Diallo AD, et al. Kidney disease in HIV-infected patients in Conakry, Guinea. Nephrol Ther. 2007;3(7):448–51. Emem-Chioma P, Arogunbade FA, Sanusi AA, et al. Renal disease in HIV sero-positive patients in Nigeria: an assessment of prevalence, clinical features and risk factors. Nephrol Dial Transpl. 2008;23:741–6. 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Muwonga J, Edidi S, Butel C, et al. Resistance to Antiretroviral Drugs in Treated and Drug-Naive Patients in the Democratic Republic of Congo. J Acquir Immune Defic Syndr. 2011;57(Suppl 1):S27–33. UNAIDS. 90-90-90 - An ambitious treatment target to help end the AIDS epidemic. 2014. https://www.unaids.org/sites/default/files/media_asset/90-90-90_en_0.pdf . Accessed 15 June 2019. Abdullahi TA, Olotu MT, Oyetunde OB, et al. COVID-19 outcomes in HIV patients: A review: Systematic Review / Meta-analysis. Ann Med Surg. 2022;78:103768. Danwang C, Noubiap JJ, Robert A, et al. Outcomes of patients with HIV and COVID-19 co-infection: a systematic review and meta-analysis. AIDS Res Ther. 2022;19:3. Massarvva T. Clinical outcomes of COVID-19 amongst HIV patients: a systematic literature review. Epidemiol Health. 2021;43:e2021036. Bertoldi A, De Crignis E, Miserocchi A, et al. HIV and kidney: a dangerous liaison. New Microbiol. 2017;40:1–10. Naicker S, Fabian J. Risk factors for the development of chronic kidney disease with HIV/AIDS. Clin Nephrol. 2010;74(Suppl 1):S51–6. Anyabolu EN, Chukwuonye II, Arodiwe E, et al. Prevalence and predictors of chronic kidney disease in newly diagnosed human immunodeficiency virus patients in Owerri, Nigeria. Indian J Nephrol. 2016;26(1):10–5. Okpa HO, Elvis MB, Ofem E, et al. Predictors of chronic kidney disease among HIV–infected patients on highly active antiretroviral therapy at the University of Calabar Teaching Hospital, Calabar, South-South Nigeria. HIV AIDS (Auckl). 2019;11:61–7. Meredith G. Coronavirus cause: Origin and how it spreads. Newsletter; 2020. Louis N, Robert K, Pauline B. Prevalence of renal dysfunction among HIV infected patients receiving Tenofovir at Mulago: a cross-sectional study. BMC Nephrol. 2020;21:232. Coulibaly A, et al. Prevalence of CKD among HIV patients on HAART in Ivory Coast. Afr J Nephrol. 2021;24(1):12–8. Amira CO, et al. Prevalence and associations of chronic kidney disease among ART-naïve persons living with HIV in Lagos, Nigeria. West Afr J Med. 2024;41(2):145–52. Beaglehole R, Yach D. Globalisation and the prevention and control of non-communicable disease: the role of the World Health Organization. BMC Public Health. 2003;3:23. Maggiolo F, et al. Renal dysfunction in HIV-infected patients: a South African perspective. J Antimicrob Chemother. 2021;76(2):440–47. Manaye B, Tesfaye T, Molla G, et al. Chronic kidney disease and associated factors among HIV/AIDS patients on antiretroviral therapy in Southern Ethiopia. BMC Nephrol. 2020;21:188. Mulenga LB, Musonda P, Mayondi GK, et al. Prevalence of renal dysfunction and associated risk factors among HIV-infected adults in Lusaka, Zambia. BMC Nephrol. 2015;16:75. Mocroft A, Kirk O, Reiss P, et al. Estimated glomerular filtration rate, chronic kidney disease and antiretroviral drug exposure: the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study. AIDS. 2010;24(9):1357–65. Kopp JB, Nelson GW, Sampath K, et al. APOL1 genetic variants in the African diaspora and kidney disease. Nat Rev Nephrol. 2020;16(11):631–40. Agbaji OO, Onu A, Agaba PE, et al. Predictors of impaired renal function among HIV infected patients commencing highly active antiretroviral therapy in Jos, Nigeria. Niger Med J. 2022;52:182–5. Anyabolu EN, Chukwuanukwu RC. Gender and chronic kidney disease in HIV-subjects in South-East Nigeria. J Trop Dis. 2016;4:218. Sigel K, et al. COVID-19 Outcomes Among People Living With HIV in New York City: A Matched Cohort Study. Clin Infect Dis. 2020;71(15):1933–9. Mellor AC, et al. Outcomes of HIV-infected patients hospitalized with COVID-19. J Am Soc Nephrol. 2021;32:201–11. Zhang H, et al. Estimated glomerular filtration rate in post-COVID-19 patients at 12–18 months: a longitudinal cohort study. BMC Med. 2025;23(1):44. Shiau S, et al. HIV and SARS-CoV-2 Co-infection: Epidemiological, Clinical Features, and Future Implications. Curr HIV/AIDS Rep. 2022;19(1):1–11. Additional Declarations No competing interests reported. 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Also discoverable on Platform About Our Team In Review Editorial Policies Advisory Board Help Center Resources Author Services Accessibility API Access RSS feed Manage Cookie Preferences © Research Square 2026 | ISSN 2693-5015 (online) Privacy Policy Terms of Service Do Not Sell My Personal Information {"props":{"pageProps":{"initialData":{"identity":"rs-8902316","acceptedTermsAndConditions":true,"allowDirectSubmit":false,"archivedVersions":[],"articleType":"Research Article","associatedPublications":[],"authors":[{"id":607590373,"identity":"a6af028d-a4df-4511-8bfb-35cd35e9cfda","order_by":0,"name":"Blessing Iveren Olusanjo","email":"data:image/png;base64,iVBORw0KGgoAAAANSUhEUgAAAZAAAAAyAQMAAABI0h/eAAAABlBMVEX///8AAABVwtN+AAAACXBIWXMAAA7EAAAOxAGVKw4bAAAA50lEQVRIiWNgGAWjYBACA3YYi7354AMgxcNHUAszjMVzLNkARLERr0Uix0wCRBPUYs7MfPjjzxwbOXOJBLPKrzl2MmwMzA8f3cCjxbKZLU2ad1uasWXPg7TbstuSgQ5jMzbOweewwzxmzIzbDiduOJ5w7LbkNmagFh42afxa+D9//Lntf+KGA4ltxZLb6onRwsMgwbvtQOKGE8lsjB+3HSasBegXM6Bfko0NzhxjlmbcdpyHjZmAX8zZmx8DHWYnZ3C8/yOQUW3Pz9788DE+LSiAmQdMEqscBBh/kKJ6FIyCUTAKRgwAAChURfLB/pwIAAAAAElFTkSuQmCC","orcid":"","institution":"University of Ilorin","correspondingAuthor":true,"prefix":"","firstName":"Blessing","middleName":"Iveren","lastName":"Olusanjo","suffix":""},{"id":607590374,"identity":"430288dc-abf1-4a2c-9475-80a2f11760cf","order_by":1,"name":"Mariam K. Sulaiman","email":"","orcid":"","institution":"University of Ilorin","correspondingAuthor":false,"prefix":"","firstName":"Mariam","middleName":"K.","lastName":"Sulaiman","suffix":""},{"id":607590375,"identity":"808e157b-327f-403b-9bb6-d723049e6856","order_by":2,"name":"Timothy Olusegun Olarenwaju","email":"","orcid":"","institution":"University of Ilorin Teaching Hospital","correspondingAuthor":false,"prefix":"","firstName":"Timothy","middleName":"Olusegun","lastName":"Olarenwaju","suffix":""},{"id":607590376,"identity":"1f357754-359c-4296-a1e8-29f1b343ed39","order_by":3,"name":"Omobola Ajoke Salami","email":"","orcid":"","institution":"University of Ilorin","correspondingAuthor":false,"prefix":"","firstName":"Omobola","middleName":"Ajoke","lastName":"Salami","suffix":""},{"id":607590377,"identity":"e84120e7-8dcf-4a77-abd6-dd2019ab1eb2","order_by":4,"name":"Sherifat Tinuke Suleiman","email":"","orcid":"","institution":"University of Ilorin","correspondingAuthor":false,"prefix":"","firstName":"Sherifat","middleName":"Tinuke","lastName":"Suleiman","suffix":""},{"id":607590378,"identity":"0e3f80c4-6818-4790-a9ef-8f343dff9b8e","order_by":5,"name":"Charles Callistus Benedict","email":"","orcid":"","institution":"University of Ilorin","correspondingAuthor":false,"prefix":"","firstName":"Charles","middleName":"Callistus","lastName":"Benedict","suffix":""},{"id":607590379,"identity":"a2aaa732-148d-4b12-a5fa-4295d58b16fc","order_by":6,"name":"Kola Abubakar Muhammad","email":"","orcid":"","institution":"University of Ilorin","correspondingAuthor":false,"prefix":"","firstName":"Kola","middleName":"Abubakar","lastName":"Muhammad","suffix":""},{"id":607590380,"identity":"53ec8bda-548a-40b0-b391-a573d2fe6a42","order_by":7,"name":"Bamidele Samson Oyedele","email":"","orcid":"","institution":"University of Ilorin","correspondingAuthor":false,"prefix":"","firstName":"Bamidele","middleName":"Samson","lastName":"Oyedele","suffix":""}],"badges":[],"createdAt":"2026-02-17 15:08:06","currentVersionCode":1,"declarations":"","doi":"10.21203/rs.3.rs-8902316/v1","doiUrl":"https://doi.org/10.21203/rs.3.rs-8902316/v1","draftVersion":[],"editorialEvents":[],"editorialNote":"","failedWorkflow":false,"files":[{"id":104888157,"identity":"fdc5e43f-9f63-493b-a6ac-779da91ab6c9","added_by":"auto","created_at":"2026-03-18 10:13:30","extension":"png","order_by":1,"title":"Figure 1","display":"","copyAsset":false,"role":"figure","size":35882,"visible":true,"origin":"","legend":"\u003cp\u003eComparison of important parameters among the different groups with their corresponding color indications;\u003c/p\u003e\n\u003cp\u003eParameters included: age, gender, marital status (M.S), duration of ART usage (D.A). COVID-19 vaccination status (V.S), COVID-19 vaccination dose (V.D), proteinuria (P.U) and eGFR.\u003c/p\u003e","description":"","filename":"1.png","url":"https://assets-eu.researchsquare.com/files/rs-8902316/v1/9408ab67fa195d76898e724a.png"},{"id":105034481,"identity":"1b71e78a-978d-4f2f-af27-57049913209e","added_by":"auto","created_at":"2026-03-20 07:23:24","extension":"pdf","order_by":0,"title":"","display":"","copyAsset":false,"role":"manuscript-pdf","size":1293536,"visible":true,"origin":"","legend":"","description":"","filename":"manuscript.pdf","url":"https://assets-eu.researchsquare.com/files/rs-8902316/v1/c3965d54-786a-42f1-a1e9-503cd9bfc3f4.pdf"}],"financialInterests":"No competing interests reported.","formattedTitle":"Prevalence of Chronic Kidney Disease (CKD) among Patients Co-infected with COVID-19 and HIV at the University of Ilorin Teaching Hospital, Ilorin, Nigeria","fulltext":[{"header":"Background","content":"\u003cp\u003eSince the emergence of Coronavirus disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), there have been over 760\u0026nbsp;million cases and 6\u0026nbsp;million deaths globally. Nigeria has recorded approximately 267,000 cases, with Kwara State accounting for over 4,600 cases and 64 deaths [\u003cspan citationid=\"CR1\" class=\"CitationRef\"\u003e1\u003c/span\u003e]. While 80% of COVID-19 patients experience mild or asymptomatic courses, severity is significantly influenced by age, sex, and underlying co-morbidities, including human immunodeficiency virus (HIV) infection [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eThe pathophysiology of SARS-CoV-2 involves a spike protein with a receptor-binding domain (RBD) that targets angiotensin-converting enzyme 2 (ACE2) receptors. Because ACE2 is ubiquitous, the virus can directly replicate within huan renal tissue [\u003cspan citationid=\"CR4\" class=\"CitationRef\"\u003e4\u003c/span\u003e]. Consequently, kidney damage occurs in approximately 30% of COVID-19 cases [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. In people living with HIV (PLWH), the risk of renal dysfunction is already elevated due to their abnormal humoral and T-cell mediated immune response that can lead to opportunistic infections especially among patients with low cluster of differentiation 4 (CD4) cell counts, high viral load, advanced disease, and those not on antiretroviral therapy (ART) [\u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e]. 48% of HIV patients at the University of Ilorin Teaching Hospital (UITH) were previously found to have chronic kidney disease (CKD) [\u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e].\u003c/p\u003e \u003cp\u003ePLWH are particularly vulnerable to severe COVID-19 outcomes due to potential immune system impairment, characterized by delayed antibody responses and prolonged disease courses. Factors such as low CD4 cell counts, high viral loads, and advanced disease stages increase the probability of infection two- to three-fold [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e]. Furthermore, the COVID-19 pandemic caused significant disruptions to ART for over 11.5\u0026nbsp;million people worldwide, potentially exacerbating HIV-associated nephropathy and other complications [\u003cspan citationid=\"CR2\" class=\"CitationRef\"\u003e2\u003c/span\u003e, \u003cspan citationid=\"CR6\" class=\"CitationRef\"\u003e6\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eRenal dysfunction in these patients may stem from various pathways: direct viral cell injury, immune-mediated damage, systemic inflammation, or antiviral drug-induced nephrotoxicity. These pathways can lead to Acute Kidney Injury (AKI), progression of CKD, or end-stage renal disease [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e]. Despite the availability of vaccinations, immunocompromised individuals may not achieve full protection, and breakthrough infections of COVID-19 remain a concern for those with co-morbidities [\u003cspan citationid=\"CR3\" class=\"CitationRef\"\u003e3\u003c/span\u003e].\u003c/p\u003e \u003cp\u003eCurrent data on the clinical outcomes of HIV and COVID-19 co-infection remain conflicting. While both viruses are established independent causes of renal disease, the impact of their co-existence on renal prevalence is not fully understood [\u003cspan citationid=\"CR8\" class=\"CitationRef\"\u003e8\u003c/span\u003e]. Given the high burden of HIV in Sub-Saharan Africa and the potential for increased mortality from synergistic renal injury in which CKD accounted for 1.2\u0026nbsp;million deaths globally, with 48% of HIV patients found to have CKD at University of Ilorin Teaching Hospital (UITH) [\u003cspan citationid=\"CR5\" class=\"CitationRef\"\u003e5\u003c/span\u003e, \u003cspan citationid=\"CR7\" class=\"CitationRef\"\u003e7\u003c/span\u003e], there is an urgent need for local data. Therefore, this study aims to determine the prevalence of CKD among HIV patients co-infected with COVID-19 at UITH, Ilorin, Nigeria.\u003c/p\u003e"},{"header":"Methodology","content":"\u003cp\u003e\u003cstrong\u003eStudy design and setting\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThis hospital-based cross-sectional study was conducted at the ART clinic of UITH, Ilorin, Nigeria. UITH is a 600-bed tertiary healthcare facility in Kwara State, North-central Nigeria, which records approximately 12,000 annual admissions. The ART clinic operates from Monday to Thursday, attending to an average of 40 patients living with HIV daily, totaling approximately 1,120 patient visits per month [9].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eSample size, sampling technique and participant recruitment\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eA systematic random sampling technique was employed to recruit participants from the ART clinic. The sampling frame was established based on the monthly clinic volume (N = 1,120) and the calculated sample size (n = 423) by Fischer\u0026rsquo;s formula using the 48% prevalence of CKD observed among HIV patients in UITH [7,10]. The sampling interval (k) was determined as follows: K=N/n =1120/423=2.6, approx. 3\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eConsequently, every third patient from the clinic register was invited to participate until the required sample size was achieved.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eStudy population\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eInclusion criteria\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eParticipants included for the study were those who had confirmed diagnosis of HIV infection, age above 18 years at the time of recruitment, registered and receiving antiretroviral therapy at the UITH ART clinic for a minimum of six months with written informed consent.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003e\u003cem\u003eExclusion criteria\u003c/em\u003e\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003ePatients with known pre-existing CKD or those undergoing renal replacement therapy (RRT) during the course of the study, patients with sickle cell anaemia and those unable or unwilling to return for the follow-up assessment at three months\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eMeasurement of variables\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe participants of the study filled questionnaires about demographic characteristics and medical history, laboratory tests were also conducted. Collection of specimen was done on two occasion (three months apart). Oropharyngeal and nasopharyngeal swabs, veinular blood and midstream urine samples were collected for the diagnosis of COVID-19 and determination of renal dysfunction during the first visit. On the second visit (after three months), veinular blood samples and midstream urine samples only were collected and analyzed for the confirmation of CKD. Before the start of the study, all data and sample collectors were trained. Swabs collected were transported in viral transport mediums (VTMs) placed in cold packs as soon as possible to the laboratory for the detection of SARS-COv-2 genes [11].\u0026nbsp;Nucleic acid was extracted from the swabs using a kit-based column method. The DaAnGene RNA Purification Kit (DaAn Gene Co., Ltd., Guangzhou, China) was used for the purification of SARS-CoV-2 RNA according to the manufacturer\u0026rsquo;s instructions [12]. Samples were analyzed using probe-based multiplex RT-qPCR to determine the presence of SARS-CoV-2. The GeneFinder\u0026trade; COVID-19 Plus Real Amp Kit (OSANG Healthcare, Gyeonggi-do, South Korea) was utilized for the identification of SARS-CoV-2 RNA. This kit targets the RdRp, E, and N genes [13].\u003c/p\u003e\n\u003cp\u003eVenous blood was collected for serum creatinine analysis. The estimated glomerular filtration rate (eGFR) was calculated using the 2021 CKD-EPI creatinine equation without the race coefficient, as recommended by the National Kidney Foundation. CKD was defined as an eGFR \u0026lt; 60 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e when persistent after three months for the purpose of this study [14].\u003c/p\u003e\n\u003cp\u003eFresh mid-stream urine samples were analyzed by dipstick urinalysis using URS-10A by Abbonn health care(UK) test kit according to manufacturer\u0026rsquo;s instruction)\u0026nbsp;to determine pH, specific gravity, proteinuria, and the presence of leukocytes, nitrites, and ketones [15].\u003c/p\u003e\n\u003cp\u003eVirological Profile (HIV viral load (copies/mL) results were obtained from the patients\u0026rsquo; medical record during their routine laboratory testing at the ART clinic, UITH at the time of the study.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eVariables of interest\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eDetection of SARS-CoV-2\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eThe probe-based multiplex RT-qPCR (using GeneFinder\u003csup\u003eTM\u003c/sup\u003e COVID-19 plus real amp kit) \u0026nbsp;assay targets the presence of one or more of the following genes: the RNA-dependent RNA polymerase- (RdRp), envelope- (E), nucleotidecapsid- (N), spike- (S) or membrane protein (M) it contains an Internal Control which targets the human endogenous \u003cstrong\u003eRNase\u003c/strong\u003e P gene. According to manufacturer\u0026rsquo;s instructions, a sample was considered positive for SARS-CoV-2 when all the three genes were detected or the combinations of: RdRP with E or RdRP and N. in a situation where a single gene was detected (only RdRP-gene or only N-gene) or a combination of E and N, the result was considered not reliable and tests repeated to confirm the sample was positive for SARS-CoV-2. The presence of only the E gene was interpreted as SARS-CoV-2 positive. Results with high cycle threshold or curves showed that the sample was positive while results with lower cycle threshold or curves indicate a negative result [15,16].\u003c/p\u003e\n\u003cp\u003e\u003cem\u003e\u003cstrong\u003eDetermination of CKD\u003c/strong\u003e\u003c/em\u003e\u003c/p\u003e\n\u003cp\u003eSerum creatinine in the blood samples collected was measured by Jaffe\u0026rsquo;s reaction and used to determine estimated glomerular filtration rate (eGFR) using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) equation without race. According to the National Kidney Foundation(NKF),\u0026nbsp;Normal eGFR\u0026nbsp;= \u0026ge; 60 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e. Chronic Kidney Disease was defined as eGFR \u0026lt; 60 mL/min/1.73 m\u003csup\u003e2\u0026nbsp;\u003c/sup\u003ewhen persistent after three months for the purpose of this study [14,16]. Proteiunuria \u0026ge;+1 was considered significant\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eData extraction and statistical analysis\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eData such as HIV-related characteristics e.g viral load (copies/mL), and antiretroviral therapy before COVID-19 diagnosis was obtained from the ART clinic of UITH. Also, COVID-19-related clinical symptoms and other underlying conditions were extracted from the questionnaires and analyzed using SPSS\u0026reg; version 21 (SPSS Inc, Chicago Il.) computer software package. Frequency tables were used to describe both categorical and quantitative variables, continuous variables was analyzed by median and interquartile ranges, for variables such as Creatinine, eGFR, pH, Viral Load), the Independent Student\u0026rsquo;s t-test was used to compare means between groups.\u003c/p\u003e\n\u003cp\u003eFor categorical variable; frequency, proportions and percentages was used, chi-square was used to assess association between the variables (gender, education, proteinuria) and compare differences between groups.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical approval\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eEthical approval was obtained from the Ethical Review Committee (ERC) of UITH, Ilorin, before the commencement of the study. Archival materials retrieved for this study was handled with care and personal data of participants were handled with confidentiality\u003c/p\u003e\n\u003cp\u003eOperational definitions\u003c/p\u003e\n\u003cp\u003eThe following definitions were used for the variables in this study\u003c/p\u003e\n\u003cul\u003e\n \u003cli\u003eA sample was considered positive for SARS-CoV-2 if all three genes, if specific combinations (RdRP with E, or RdRP with N) or E gene alone were detected and a High cycle threshold (Ct) values or characteristic amplification curves [15].\u003cbr\u003eDipstick proteinuria of 1+ or greater was taken as significant.\u003c/li\u003e\n \u003cli\u003eHIV Viral load above 100,000 copies per milliliter of blood is considered to be high, viral load below 10,000 copies per milliliter of blood is considered low. Viral suppression or undetectable HIV viral load is less than 20 copies per milliliter of blood [17].\u003c/li\u003e\n \u003cli\u003eChronic Kidney Disease(CKD) was defined as eGFR \u0026lt; 60 mL/min/1.73 m\u003csup\u003e2\u0026nbsp;\u003c/sup\u003eand/or for the purpose of this study which was persistent when measured after three month [14].\u003c/li\u003e\n\u003c/ul\u003e"},{"header":"Results","content":"\u003cp\u003eOut of the total enrollment of 423 patients in this study, 393 patients (92.89%) return rate) provided complete and analyzable data.\u003c/p\u003e\n\u003ch2\u003eSocio-demographic and clinical characteristics of the study population\u003c/h2\u003e\n\u003cp\u003eThe study population had a mean age of 46.1 \u0026plusmn; 11.5 years, with a range of 18 to 80 years. The most represented age cohort was the 45\u0026ndash;54 year group, accounting for 32.3% (n=127) of the total sample. A significant female preponderance was observed, comprising of 72.3% (n=284) of the participants compared to 27.7% (n=109) for males. Regarding marital status, the majority of the respondents (69%, n=271) were married. Furthermore, a high proportion of the cohort had limited formal education, with 18.3% (n=72) having attained only primary education or no formal schooling.\u003c/p\u003e\n\u003cp\u003eAll participants were receiving ART at the time of the study. Analysis of treatment duration revealed that the majority (70.5%, n=277) had been on ART for more than 5 years, while 21.9% (n=86) had been on treatment for 1\u0026ndash;5 years, and 7.6% (n=30) for less than one year. Co-morbidities observed include ulcers (6.1%), hypertension (4.6%), diabetes mellitus (1.5%), and asthma (0.5%). A family history of renal disease was reported by only 1.3% (n=5) of the subjects.\u003c/p\u003e\n\u003cp\u003eWhile awareness of COVID-19 was universal among participants, only 9.7% (n=38) had undergone previous testing, all of whom reported negative results. Vaccination coverage of COVID-19 was 53.2% (n=209); of these, 72.7% (n=152) had received more than one dose, while 27.3% (n=57) had received a single dose. Majority of participants (83.3%, n=327) remained asymptomatic. Frequently reported symptoms were body weakness (7.6%), catarrh and cough (3.8%), high fever (1.5%), and malaria-like symptoms (0.8%).\u003c/p\u003e\n\u003cp\u003eTable 1 shows that males had significantly higher levels of education, with 67.9% attaining secondary education or higher compared to 23.9% of females (p\u0026lt;0.001). Occupation and ART duration also showed significant gender-based differences (p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eRegarding laboratory parameters, males exhibited significantly higher mean serum creatinine (101.97 vs 81.86 \u0026mu;mol/L,p\u0026lt;0.001) and HIV viral load (20,528 vs 7,543 copies/mL, p=0.038). While eGFR was statistically different between the groups, both means remained within the normal range (\u0026gt;80 mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e). In urinalysis, females showed a significantly higher prevalence of hematuria (11.3% vs 5.5%, p\u0026lt;0.001), whereas males had a higher prevalence of proteinuria (p\u0026lt;0.001). No significant differences were observed in age, vaccination status, or underlying health conditions.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 1: Comparison of sociodemographic, clinical, and laboratory parameters by gender (N=393)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eMale (n=109)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eFemale (n=284)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge (years), Mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e48.28 \u0026plusmn;12.36\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45.29 \u0026plusmn; 11.11\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.105\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEducation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Illiterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13 (11.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e162 (57.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Primary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (20.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30 (27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (2.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e44 (40.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e62 (21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarital Status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.094\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e84 (77.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e183 (64.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Single\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20 (7.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Separated/Widowed\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11 (10.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e81 (28.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOccupation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Trader\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51 (46.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e198 (69.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Civil Servant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39 (35.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e64 (22.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Farmer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 (2.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Student / None\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9 (8.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14 (4.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCOVID-19 Vaccination Status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.110\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Vaccinated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e48 (44.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e160 (56.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Not Vaccinated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e61 (56.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e124 (43.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eART Duration, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- \u0026lt; 1 year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- 1\u0026ndash;5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23 (21.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65 (22.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- \u0026gt; 5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e79 (72.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e193 (68.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUnderlying Health Condition, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52 (18.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.989\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLaboratory Parameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCreatinine (\u0026mu;mol/L), Mean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e101.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e81.86\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eeGFR (mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e), Mean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e84.73\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e80.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHIV Viral Load, Mean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20,528.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7,543.22\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.038\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUrinary pH, Mean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.35\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSpecific Gravity, Mean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.013\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.015\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.270\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProteinuria\u0026nbsp;(Trace or Positive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e26 (23.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e59 (20.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHematuria\u0026nbsp;(Presence of Blood)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (5.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e32 (11.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLeucocytes\u0026nbsp;(Positive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30 (27.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e116 (40.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.935\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSignificant P-values (\u0026lt;0.005) are highlighted for easy observation\u003c/p\u003e\n\u003cp\u003ePrevalence of COVID-19\u003c/p\u003e\n\u003cp\u003eA prevalence of 13.5% of COVID-19 infection was found among the participants.\u0026nbsp;The mean ages and standard deviation of the HIV patients co-infected with COVID-19 were 47.11 \u0026plusmn; 9.978 years ranging between 28 years to 68 years. The highest\u0026nbsp;age group in the study was 45 to 54 (32.1%) of the total sample indicates that patients within this age group were mostly co-infected with COVID-19. COVID-19 co-infection was observed in more female (69.8%) compared to the male (30.2%). 73.5% asymptomatic cases was observed and 56.6% of the COVID-19 infection was observed among the vaccinated participants.\u003c/p\u003e\n\u003cp\u003eThe study found significant differences in COVID-19 vaccination status between groups (p\u0026lt;0.001), although the absolute percentage of vaccinated individuals was similar (56.6% in the co-infected group vs. 52.4% in the control). Among those vaccinated, the co-infected group had a higher proportion of individuals who had received two or more doses (73.3% vs. 37.1%), though this trend toward higher dosage did not reach independent statistical significance (p=0.065). Significant associations with COVID-19 infection were also found for gender (p=0.001), occupation (p\u0026lt;0.001), and underlying health conditions (p\u0026lt;0.001), particularly hypertension.\u003c/p\u003e\n\u003cp\u003eTable 2 shows that patients co-infected with COVID-19 exhibited significantly higher viral loads (p=0.001) and higher urinary pH levels (p\u0026lt;0.001) compared to those without COVID-19.\u003c/p\u003e\n\u003cp\u003eSignificant associations with COVID-19 status were observed regarding gender (p=0.001), educational background (p=0.020), occupation (p\u0026lt;0.001) and duration of ART usage (p\u0026lt;0.001). Furthermore, underlying health conditions; specifically hypertension and ulcers were more prevalent in the co-infected group (p\u0026lt;0.001). While vaccination status differed significantly (p\u0026lt;0.001), renal function markers, including mean creatinine (86.79 vs 91.60 \u0026mu;mol/L) and eGFR, did not show statistically significant differences between the two cohorts (p\u0026gt;0.05).\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 2: Sociodemographic, clinical, and laboratory characteristics of HIV Patients by COVID-19 status (N=393)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHIV with COVID-19 (n=53)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eHIV without COVID-19 (n=340)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge (years), Mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47.11 \u0026plusmn; 9.98\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45.96 \u0026plusmn;11.97\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.602\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGender, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16 (30.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e93 (27.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e37 (69.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e247 (72.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarital Status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.591\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39 (73.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e228 (67.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Single\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e31 (9.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Widow(er)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10 (18.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e57 (16.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEducation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.020\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Illiterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 (15.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e50 (14.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Primary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10 (18.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e63 (18.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Secondary/Above\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13 (24.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e111 (32.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (41.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e115 (33.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOccupation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Trader\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e29 (54.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e208 (61.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Civil Servant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14 (26.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e71 (19.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Farmer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Others\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCOVID-19 Vaccination \u0026nbsp;Status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Vaccinated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30 (56.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e178 (52.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Not Vaccinated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23 (43.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e159 (46.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCOVID-19 Vaccine Doses, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.065\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- One dose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (23.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e51 (15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Two or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (73.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e126 (37.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eART Duration, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- \u0026lt; 1 year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (5.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e30 (8.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- 1\u0026ndash;5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e14 (26.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e74 (21.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- \u0026gt; 5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e36 (67.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e235 (69.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUnderlying Condition, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (13.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13 (3.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (1.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 (1.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- None\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e39 (73.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e292 (90.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eLaboratory Parameters\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eViral Load, Mean\u0026nbsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11924.63\u0026nbsp;76,939.2\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6223.58\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCreatinine (\u0026mu;mol/L), Mean\u0026nbsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e86.79\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e91.60\u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.781\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eeGFR (mL/min/1.73m^2), Mean\u0026nbsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82.61\u0026nbsp;20.41\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e77.74\u0026nbsp;15.87\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.267\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUrinary pH, Mean\u0026nbsp;SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.35 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.30 \u0026nbsp;\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProteinuria (trace or positive)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8(15.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e77(22.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSignificant P-values (\u0026lt;0.005) are highlighted for easy observation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevalence of CKD among all participants\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe prevalence of CKD among all participants observed in this study is 8.4% with the mean ages and standard deviation of 54.33\u0026plusmn;9.78 years ranging between 36 years to 70years. The highest\u0026nbsp;age group in the study was 45 to 54years. More female (66.7%) of the total sample had CKD compared to the male (30.2%).\u003c/p\u003e\n\u003cp\u003eTable 3 shows the comparison between HIV patients with CKD (n=33) and without CKD (n=360) shows that the CKD group was significantly older on average and had a higher proportion of males (p=0.024). From a clinical perspective, the CKD group demonstrated significantly higher creatinine and lower eGFR (p\u0026lt;0.001), as well as a higher prevalence of proteinuria (p\u0026lt;0.001) and more acidic urinary pH (p\u0026lt;0.001). Notably, viral load was significantly lower in the CKD group (p=0.003). No significant differences were found in vaccination status, ART duration, or underlying health conditions between the two groups (p\u0026gt;0.05\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 3: Sociodemographic, clinical, and laboratory characteristics of HIV Patients by CKD Status (N=393)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCharacteristics\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHIV with CKD (n=33)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eHIV without CKD (n=360)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eP-Value\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge (years), Mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e54.33 \u0026plusmn; 9.78\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e45.37 \u0026plusmn; 11.40\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.137\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGender, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.024\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e98 (27.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e265 (72.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarital Status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.992\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e245 (68.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Single\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33 (9.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Separated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15 (4.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Widow(er)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 (24.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e67 (18.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEducation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.211\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Illiterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (18.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52 (14.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Primary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 (24.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e65 (18.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Secondary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e11 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e114 (31.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 (24.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e129 (35.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eOccupation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.689\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Trader\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e20 (60.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e229 (63.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Civil Servant\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10 (30.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e93 (25.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Farmer\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e16 (4.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Others\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e22 (6.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCOVID-19 Vaccination Status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.299\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Vaccinated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24 (72.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e184 (51.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Not Vaccinated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e9 (27.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e176 (48.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCOVID-19 Vaccine Doses, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.148\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- One dose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (25.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e52 (28.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Two or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e18 (75.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e130 (70.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eART Duration, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.000\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- \u0026lt; 1 year\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (15.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e28 (7.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- 1\u0026ndash;5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e81 (22.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- \u0026gt; 5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e21 (63.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e251 (69.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUnderlying Condition, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Hypertension\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (6.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17 (4.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Diabetes\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (3.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 (1.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- None\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e27 (81.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e302 (84.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eViral Load, Mean\u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1,037.96\u0026plusmn;4077.83\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e12,083.70\u0026plusmn;79009.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.003\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCreatinine (\u0026mu;mol/L),Mean\u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e142.39\u0026plusmn;68.15\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e82.40\u0026plusmn;14.61\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eeGFR(mL/min/1.73m2),Mean\u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e47.15\u0026plusmn;11.32\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e85.14\u0026plusmn;17.33\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUrinary pH, Mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.23 \u0026plusmn; 0.34\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.35 \u0026plusmn; 0.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProteinuria(trace or positive), n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e15 (45.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e70 (19.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e\n\u003cp\u003eSignificant P-values (\u0026lt;0.005) are highlighted for easy observation\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003ePrevalence of CKD among patients co-infected with COVID-19 and HIV\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe prevalence of CKD among HIV patients co-infected with COVID-19 was found to be 1.5% with mean ages and standard deviation of 49.33\u0026nbsp;\u0026plusmn;7.992 ranging from 39 years to 62 years of age. Both male and female were affected equally.\u003c/p\u003e\n\u003cp\u003eTable 4 shows that among HIV patients co-infected with COVID-19, those with CKD (n=6) exhibited significantly impaired renal markers compared to those without CKD (n=47). Mean serum creatinine was significantly higher (145.67 vs.84.70\u0026mu;mol/L, p=0.002), while eGFR was significantly lower (49.17 vs.81.38mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e, p\u0026lt;0.001). Furthermore, the CKD group presented with significantly more acidic urinary pH levels (6.08 vs. 6.33, p\u0026lt;0.001) and lower specific gravity (1.008 vs. 1.017, p\u0026lt;0.001).\u003c/p\u003e\n\u003cp\u003eInterestingly, despite the physiological differences in kidney function, there were no statistically significant variations in sociodemographic factors, ART duration, or vaccination status between the two co-infected subgroups (p\u0026gt;0.05). Viral load levels were lower in the CKD group, though this difference did not reach statistical significance (p=0.316).\u003c/p\u003e\n\u003cp\u003eA visual comparison of these key demographic and clinical parameters across all study cohorts including the general participant, HIV/COVID-19 co-infected groups, and those with CKD is presented in Figure 1.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eTable 4: Sociodemographic, clinical, and laboratory characteristics of COVID-19 co-infected HIV Patients by CKD Status (n=53)\u003c/strong\u003e\u003c/p\u003e\n\u003ctable border=\"1\" cellspacing=\"0\" cellpadding=\"0\" class=\"fr-table-selection-hover\"\u003e\n \u003ctbody\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCharacteristics\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCo-Infected with CKD (n=6)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eCo-Infected without CKD (n=47)\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u003cstrong\u003eP-Value\u003c/strong\u003e\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eAge (years), Mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49.33 \u0026plusmn;7.99\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e46.83 \u0026plusmn; 10.24\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.247\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eGender, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.622\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Male\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e13 (27.6)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Female\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34 (72.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eMarital Status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.999\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Married\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e35 (74.5)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Single/Separated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (6.4)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Widow(er)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e8 (17.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eEducation, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.669\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Illiterate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Primary\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e3 (50.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (14.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Secondary/Graduate\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e33 (70.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCOVID-19 Vaccination Status, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.949\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Vaccinated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (100.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e24 (51.1)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Not Vaccinated\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0 (0.0)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e23 (48.9)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003eCOVID vaccine Doses, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026nbsp;\u003c/p\u003e\n \u003cp\u003e0.787\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- One dose\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- Two or more\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e5 (83.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e17 (36.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eART Duration, n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.766\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- 1\u0026ndash;5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e4 (66.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e10 (21.2)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e- \u0026gt; 5 years\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e2 (33.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e34 (73.3)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\u003cbr\u003e\u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUnderlying Condition (Hypertension), n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6 (12.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.733\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eCreatinine (\u0026mu;mol/L), Mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e145.67 \u0026plusmn; 61.89\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e84.70 \u0026plusmn; 12.88\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.002\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eeGFR (mL/min/1.73m\u003csup\u003e2\u003c/sup\u003e), Mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e49.17 \u0026plusmn; 12.47\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e81.38 \u0026plusmn; 12.16\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eViral Load, Mean\u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e196.67\u0026plusmn;432.74\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6,992.98\u0026plusmn;38997.56\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.316\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eUrinary pH, Mean \u0026plusmn; SD\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.08 \u0026plusmn; 0.20\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e6.33 \u0026plusmn; 0.51\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eSpecific Gravity, Mean\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.008\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1.017\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e\u0026lt;0.001\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003ctr\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003eProteinuria\u0026nbsp;(trace or positive), n (%)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e1 (16.7)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e7 (14.8)\u003c/p\u003e\n \u003c/td\u003e\n \u003ctd valign=\"top\"\u003e\n \u003cp\u003e0.997\u003c/p\u003e\n \u003c/td\u003e\n \u003c/tr\u003e\n \u003c/tbody\u003e\n\u003c/table\u003e"},{"header":"Discussions","content":"\u003cp\u003eChronic kidney disease among HIV patients may lead to severe complications if not early diagnosed and properly managed [7]. The outbreak of COVID-19 is a major concern among co-infected patients for effective management in other to prevent more complications and higher mortality rate among the population.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eOur findings corroborate several regional reports indicating that females are disproportionately affected by HIV, with a male-to-female ratio of 0.4:1. This trend aligns with studies by Dada et al. [7], Wools-Kaloustian et al.[18], and Han et al.[19], who reported ratios of 0.8:1, 0.5:1, and 0.3:1, respectively. This gender disparity may be attributed to deep-seated socio-cultural factors, gender inequalities that limit preventive agency, and biological vulnerabilities. Conversely, our findings contrast with Agaba et al., who reported a male predominance (60.5%) in Jos [20]. These regional variations may stem from distinct behavioral attitudes, such as the use of unsterilized instruments especially the use of manual hair shavers and nail cutters or the prevalence of polygamous practices in specific Northern regions, which traditionally increase the number of sexual partners among males.\u003c/p\u003e\n\u003cp\u003eThe cohort\u0026rsquo;s mean age of 46.1 \u0026plusmn; 11.5 years is remarkably consistent with data from Uganda reported by Mwemezi et al. [21]. However, this reflects an aging trend compared to earlier Nigerian cohorts where mean ages ranged from 34.6 to 42.3 years [20, 22, 23,]. The shift toward the 45\u0026ndash;54 age group (32.3%) suggests that middle-aged adults, who are most active socio-economically and sexually, now represent the primary demographic at risk. This demographic shift is further complicated by marital status; 69% of our participants were married, a finding supported by Orire et al. [24] and Nabukenya et al. [25], emphasizing the risk of intra-marital transmission if virological control is not strictly maintained.\u003c/p\u003e\n\u003cp\u003eFurthermore, the high prevalence of infection among participants with limited formal education (49.6%) suggests that health literacy is a critical barrier to disease control. The observed intersection between female gender and lower educational attainment likely compounds HIV risk, as limited access to health information often results in poor management of sexual health and higher transmission rates due to lack of awareness.\u003c/p\u003e\n\u003cp\u003eA significant proportion of participants (70.5%) had been on ART for over five years, which likely accounts for the high rate of viral suppression (66.4%). Our suppression rates are comparable to findings from Togo (69.2%) and Kenya (62%) [26,27], though they remain lower than the 74\u0026ndash;86% reported in other Nigerian, Cameroonians and Congolese cohorts [28,29,30]. Importantly, our results exceeded the UNAIDS global average of 47% reported in 2018 [31], indicating high treatment efficacy within this center. However, the prolonged use of ART necessitates routine monitoring of renal biomarkers to prevent drug-induced nephrotoxicity over time.\u003c/p\u003e\n\u003cp\u003eThe observed COVID-19 prevalence of 13.5% is higher than the pooled global prevalence (2\u0026ndash;3.8%) [32] but lower than the 26.9% reported in recent meta-analyses [33]. The high level of COVID-19 awareness among participants likely contributed to the relatively low transmission rate. Notably, 73.5% of co-infected participants were asymptomatic, supporting the findings of Tian et al. [3] regarding the high frequency of asymptomatic presentations.\u003c/p\u003e\n\u003cp\u003eIn contrast to global reports by Massarwa [34], which indicated a male predominance in co-infections, our study found that 69.8% of co-infected patients were female. We also observed that 56.6% of co-infected individuals were vaccinated. This shows the potential for breakthrough infections in immunocompromised populations, where traditional vaccine-induced protection may be attenuated, particularly among those who received multiple doses supporting findings by Tian et al [3].\u003c/p\u003e\n\u003cp\u003eA critical finding was that co-infected patients exhibited higher HIV viral loads, lower eGFR, and higher proteinuria levels (\u0026gt;+1) compared to those without COVID-19. This biochemical signature suggests that SARS-CoV-2 may exacerbate renal strain in PLWH, potentially through direct viral entry into renal tubules or the systemic inflammatory response.\u003c/p\u003e\n\u003cp\u003eAdditionally, males exhibited higher baseline creatinine and lower pH/eGFR levels. This gender-based biochemical difference may reflect late-presentation tendencies among males, who often seek medical intervention only during severe illness. These findings emphasize that COVID-19 in HIV patients is not merely a respiratory concern but a multi-system challenge that may accelerate renal decline if not managed through rigorous monitoring of laboratory parameters.\u003c/p\u003e\n\u003cp\u003eA proper understanding and early diagnosis of CKD among HIV patients may help to reduce mortality. Although, the prevalence of 8.4% observed in this study agrees with the global prevalence range of between 2-38% prevalence reported by Bertoldi et al. [35], the result obtained in this finding is lower than results obtained in Nigeria; 47.6% in Ilorin, 38% in Ile-ife, 51.8% in Jos, 15.3% in Calabar, 22.9% in the South-East, and 23.5% in the South-West [7,23,36,37,38,39,40]. This may be as a result of variations in methodology of the various studies, a single measurement of serum creatinine and albumin creatinine ratio which may not be a true representation of the obtained CKD prevalence rate was used. The overall CKD prevalence of 8.4% observed among HIV patients in this study aligns with contemporary findings across West Africa, reinforcing the high burden of renal disease in this demographic. Our results are closely comparable to a 2021 study in Ivory Coast, which reported a 10.4% prevalence among patients on highly active antiretroviral therapy (HAART) [41]. Interestingly, our prevalence is slightly lower than the 10.0%\u0026ndash;17.6% range reported in a recent 2024 study of ART-na\u0026iuml;ve patients in Lagos, Nigeria [42]. This disparity may suggest that the established ART clinic at UITH provides a degree of renal protection through better virological control and clinical management compared to ART-na\u0026iuml;ve cohorts in other regions of Nigeria.\u0026nbsp;The mean ages and standard deviation of the patients with CKD were\u0026nbsp;54.33\u0026plusmn;9.778years ranging between 36 years to 70years supporting the study conducted by Beagelehole et al.[43]. The overall\u0026nbsp;8.4% CKD prevalence\u0026nbsp;in our study falls within the lower spectrum of reported rates in Sub-Saharan Africa. For instance, while we observed similarities with\u0026nbsp;South Africa (8.1%)\u0026nbsp;[44], our prevalence is markedly lower than studies from\u0026nbsp;Ethiopia (18.2%)\u0026nbsp;and\u0026nbsp;Zambia (33.5%)\u0026nbsp;[45,46]. Globally, our findings contrast with the\u0026nbsp;D:A:D Study (Europe and Australia), which reported a much lower CKD prevalence of roughly\u0026nbsp;3.3%\u0026nbsp;[47]. This discrepancy highlights the persistent biological and socio-economic vulnerability of African populations to renal injury, potentially due to a higher prevalence of the\u0026nbsp;Apolipoprotein L1 (APOL1) genetic risk variants, which are less common in European cohorts [48]. The highest\u0026nbsp;age group in the study was 45 to 54, accounting for 33.3% of the total sample indicates that adults are more affected by CKD either due to prolonged use of ARTs, underlying health conditions and/or other factors. Majority, comprising of 66.7% females of patients with CKD is similar to a research by Agbaji et al.[49] who reported a higher prevalence of CKD among females and contrary to\u0026nbsp;Anyabolu et al.[50] who reported that there is no significant association between gender and CKD.\u003c/p\u003e\n\u003cp\u003eThe High serum creatinine and consequently a lower eGFR which is a measure of renal dysfunction was found to be associated with CKD in HIV subjects is in line with other earlier studies.[23,50];\u0026nbsp;This indicates impaired kidney function in the CKD group.\u003c/p\u003e\n\u003cp\u003eThe viral load, a measure of HIV replication in the body, was found to be significantly lower in HIV patients with CKD compared to those without CKD which is contrary to Manaye et al. [45], who reported that\u0026nbsp;having viral load\u0026ge;1000 copies/mm\u003csup\u003e3\u003c/sup\u003e was associated with CKD.\u0026nbsp;261(66.4%) of the patients had viral load count \u0026lt; 20copies/milliliter (Viral suppression) this may be due to efficiency in the treatment and control of the disease as 277(70.5%) of the participant have been on ARTs for more than 5 years. This is also an indication that CKD could be as a result of prolonged antiretroviral drugs.\u003c/p\u003e\n\u003cp\u003eWhile data specifically detailing the prevalence of Chronic Kidney Disease (CKD) among people living with HIV (PLWH) co-infected with COVID-19 has been scarce, this study identifies a co-infection CKD prevalence of 1.5%. The mean age of these co-infected patients was 49.33\u0026nbsp;\u0026plusmn;\u0026nbsp;7.99 years (range: 39\u0026ndash;62 years), with an equal distribution across genders.\u003c/p\u003e\n\u003cp\u003eThese findings align with emerging global observations from the ISARIC-4C and Spanish multicenter cohorts, which suggested that PLWH with mild COVID-19 often experience clinical outcomes comparable to the general population [34,51]. However, the low prevalence in our study contrasts with reports from New York and Wuhan, where renal involvement in hospitalized co-infected patients was significantly higher [52,53].\u003c/p\u003e\n\u003cp\u003eOur results indicate that individuals co-infected with COVID-19 and CKD display a distinct laboratory profile specifically characterized by higher creatinine levels alongside lower pH and eGFR values. Despite these markers of renal strain, no significant differences were observed in other physiological parameters between the groups. This biochemical signature supports the hypothesis of a \u0026quot;renal hit\u0026quot; even in non-hospitalized COVID-19 cases, which may persist as part of the \u0026quot;long-tail\u0026quot; of COVID-19 [54].\u003c/p\u003e\n\u003cp\u003eBeyond the viral co-infection, this study identifies a complex interplay of non-viral factors that exacerbate CKD risk. We found that prolonged use of ART, gender, level of education, occupational status, and marital status were significant contributors to renal vulnerability. These findings are consistent with the Global Burden of Disease perspectives, which view HIV and COVID-19 as part of a \u0026quot;syndemic\u0026quot; where social determinants and biological factors (long-term ART toxicity) converge to worsen chronic outcomes [54].\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eLimitation of the study\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eWe acknowledge that although the aim of the study was achieved, insufficient fund did not allow us to dive deeper into other areas that could equally aid the better understanding of the study.\u0026nbsp;\u003c/p\u003e\n\u003cp\u003eThese areas include; determining the COVID-19 strain(s) involved in the breakthrough infections among others.\u0026nbsp;\u003c/p\u003e"},{"header":"Conclusions","content":"\u003cp\u003eThe high level of awareness of COVID-19 prevention and control mechanisms may be responsible for the low prevalence of co-infection of HIV and COVID-19 among the participants of the study. The study also reported breakthrough infections among vaccinated participants as most participants infected with COVID-19 from the study were patients who were vaccinated with two or more doses of the COVID-19 vaccine. This suggests the need for further research to examine the effect of vaccination on the study population and the general population.\u003c/p\u003e\n\u003cp\u003eA higher prevalence of CKD observed among participants who are on ART for more than five years and viral suppression is an indication that the usage of ART is a risk factor for CKD.\u003c/p\u003e\n\u003cp\u003eAlthough HIV and COVID-19 have been reported to be responsible for CKD individually, results obtained from this study reviews that HIV Patients co-infected with COVID-19 does not have a higher prevalence of CKD. This study also reviews that other factors such as prolonged use of ART, gender, level of education, viral load, occupational and marital status can also increase the risk of having CKD.\u003c/p\u003e\n\u003ch2\u003eRecommendations\u0026nbsp;\u003c/h2\u003e\n\u003cp\u003eSince a higher prevalence of CKD was observed in subjects on ART for more than five years, we recommend that a routine check should be added to effectively help manage the health of the patients. Proper education and follow up should be conducted among HIV patients.\u003c/p\u003e\n\u003cp\u003eWith 100% COVID-19 vaccination in the co-infected CKD subgroup, continued prioritization of booster doses for renal patients is recommended to maintain the low severity observed.\u003c/p\u003e"},{"header":"Abbreviations","content":"\u003cdiv class=\"DefinitionList\"\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eACE2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAngiotensin-converting enzyme 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eAKI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAcute Kidney Injury\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eART\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eAntiretroviral therapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCD4\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCluster of differentiation 4\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCKD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic Kidney Disease\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCKD-EPI\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eChronic Kidney Disease Epidemiology Collaboration\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCOVID-19\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCoronavirus disease 2019\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eCt\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eCycle threshold\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eeGFR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEstimated glomerular filtration rate\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eERC\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eEthical Review Committee\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eHIV\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eHuman immunodeficiency virus\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eNKF\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eNational Kidney Foundation\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePolymerase chain reaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003ePLWH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003ePeople living with HIV\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRBD\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReceptor-binding domain\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRNA\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRibonucleic acid\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRRT\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eRenal replacement therapy\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eRT-qPCR\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eReal-time quantitative polymerase chain reaction\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eSARS-CoV-2\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eSevere Acute Respiratory Syndrome Coronavirus 2\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eUITH\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eUniversity of Ilorin Teaching Hospital\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003cdiv class=\"DefinitionListEntry\"\u003e \u003cdiv class=\"Term\"\u003eVTMs\u003c/div\u003e \u003cdiv class=\"Description\"\u003e \u003cp\u003eViral transport mediums\u003c/p\u003e \u003c/div\u003e \u003c/div\u003e \u003c/div\u003e"},{"header":"Declarations","content":"\u003cp\u003e\u003cstrong\u003eGuidelines\u003c/strong\u003e: We ensure that all methods carried out in this study were carried out according to standards and regulations.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eEthical Approval:\u003c/strong\u003e Obtained from the University of Ilorin Teaching Hospital(UITH) Ethical Review Committee with reference number UITH/CAT/189/19\u003csup\u003eB\u003c/sup\u003e/278.\u0026nbsp;The study was conducted in accordance with the Declaration of Helsinki. Archival materials retrieved for this study were handled with care and personal data of participants were handled with confidentiality.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAvailability of Data\u003c/strong\u003e: Data from this study is available upon request from the corresponding author.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eFunding\u003c/strong\u003e: No specific funding was received for this study\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConsent for publication\u003c/strong\u003e: Not applicable\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eConflicting Interest\u003c/strong\u003e: there is no conflicting interest among all authors.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAuthors\u0026apos; contributions\u0026nbsp;\u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eBIO conceived and designed the study, participated in sample and data collection, performed the laboratory and statistical analyses, and drafted the manuscript. MKS supervised the study, assisted in the study design, oversaw the molecular analysis for SARS-CoV-2, and contributed to the writing of the manuscript. TOO co-supervised the study, assisted in the study design, and provided oversight for the CKD-specific aspects of the research. OAS participated in sample and data collection and performed laboratory analyses. STS facilitated the collection of clinical data at the ART clinic and performed the creatinine testing. CCB, SDB, and MKA performed laboratory experiments and were responsible for data acquisition. All authors read and approved the final manuscript.\u003c/p\u003e\n\u003cp\u003e\u003cstrong\u003eAcknowledgements: \u003c/strong\u003e\u003c/p\u003e\n\u003cp\u003eThe authors wish to thank the staff of the ART clinic and the Molecular Diagnostic and Research Laboratory at the University of Ilorin Teaching Hospital for their technical support.\u003c/p\u003e"},{"header":"References","content":"\u003col\u003e\u003cli\u003e\u003cspan\u003eWorld Health Organization. WHO Coronavirus (COVID-19) Dashboard with Vaccination Data. Geneva: World Health Organization. 2024. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://covid19.who.int/\u003c/span\u003e\u003cspan address=\"https://covid19.who.int/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 15 Jan 2024.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWorld Health Organization. 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Kidney Int. 2024;105(4S):S117\u0026ndash;271.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbbonn Healthcare. URS-10A Reagent Strips Technical Specifications. London; 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eVaidya SR, Aeddula NR. Chronic Renal Failure. In: StatPearls [Internet]. Treasure Island (FL): StatPearls Publishing; 2023. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.ncbi.nlm.nih.gov/books/NBK535404/\u003c/span\u003e\u003cspan address=\"https://www.ncbi.nlm.nih.gov/books/NBK535404/\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIAPAC. 2021 IAPAC Guidelines for Optimizing the HIV Care Continuum. J Int Assoc Provid AIDS Care. 2021;20:1\u0026ndash;15.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eWools-Kaloustian K, Sidle JE, Selke HM, et al. A Comparison of the HIV-Infected and Uninfected Populations in Western Kenya. J Int Assoc Provid AIDS Care. 2012;11(4):237\u0026ndash;42.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHan M, Zhou J, Zhang J, et al. Clinical characteristics and outcomes of HIV-infected patients with COVID-19: a systematic review and meta-analysis. J Med Virol. 2022;94(5):1852\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgaba EI, Agaba PA, Sirisena ND, et al. Renal disease in the acquired immunodeficiency syndrome in north central Nigeria. Niger J Med. 2003;12:120\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMwemezi O, Ruggajo P, Mngumi J, et al. Renal Dysfunction among HIV-Infected Patients on Antiretroviral Therapy in Dar es Salaam, Tanzania: A Cross-Sectional Study. Int J Nephrol. 2020;2020:8378947.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBah A, Kaba ML, Diallo AD, et al. Kidney disease in HIV-infected patients in Conakry, Guinea. Nephrol Ther. 2007;3(7):448\u0026ndash;51.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eEmem-Chioma P, Arogunbade FA, Sanusi AA, et al. Renal disease in HIV sero-positive patients in Nigeria: an assessment of prevalence, clinical features and risk factors. Nephrol Dial Transpl. 2008;23:741\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOrire IO, Alab K. Spatio-temporal distribution of HIV/AIDS infections in Ilorin metropolis, Kwara State, Nigeria. FUDMA J Sci. 2020;4(1):623\u0026ndash;31.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNabukenya AM, Nambuusi A, Matovu JK. Risk factors for HIV infection among married couples in Rakai, Uganda: a cross-sectional study. BMC Infect Dis. 2020;20:25.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDagnra AY, Vidal N, Mensah A, et al. High Prevalence of HIV-1 Drug Resistance among Patients on First-Line Antiretroviral Treatment in Lom\u0026eacute;, Togo. J Int AIDS Soc. 2011;14:30.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eHumphrey JM, Genberg BL, Keter A, et al. Viral Suppression among Children and Their Caregivers Living with HIV in Western Kenya. J Int AIDS Soc. 2019;22:e2527.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eIsaac E, Ajani A, Difa A, et al. Viral Suppression in Adult Nigerians in a Regional Antiretroviral Therapy Programme: A Cross Sectional Descriptive Study. World J AIDS. 2021;11:1\u0026ndash;14.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eFokam J, Sosso SM, Yagai B, et al. Viral Suppression in Adults, Adolescents and Children Receiving Antiretroviral Therapy in Cameroon. AIDS Res Ther. 2019;16:36.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMuwonga J, Edidi S, Butel C, et al. Resistance to Antiretroviral Drugs in Treated and Drug-Naive Patients in the Democratic Republic of Congo. J Acquir Immune Defic Syndr. 2011;57(Suppl 1):S27\u0026ndash;33.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eUNAIDS. 90-90-90 - An ambitious treatment target to help end the AIDS epidemic. 2014. \u003cspan class=\"ExternalRef\"\u003e\u003cspan class=\"RefSource\"\u003ehttps://www.unaids.org/sites/default/files/media_asset/90-90-90_en_0.pdf\u003c/span\u003e\u003cspan address=\"https://www.unaids.org/sites/default/files/media_asset/90-90-90_en_0.pdf\" targettype=\"URL\" class=\"RefTarget\"\u003e\u003c/span\u003e\u003c/span\u003e. Accessed 15 June 2019.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAbdullahi TA, Olotu MT, Oyetunde OB, et al. COVID-19 outcomes in HIV patients: A review: Systematic Review / Meta-analysis. Ann Med Surg. 2022;78:103768.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eDanwang C, Noubiap JJ, Robert A, et al. Outcomes of patients with HIV and COVID-19 co-infection: a systematic review and meta-analysis. AIDS Res Ther. 2022;19:3.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMassarvva T. Clinical outcomes of COVID-19 amongst HIV patients: a systematic literature review. Epidemiol Health. 2021;43:e2021036.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBertoldi A, De Crignis E, Miserocchi A, et al. HIV and kidney: a dangerous liaison. New Microbiol. 2017;40:1\u0026ndash;10.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eNaicker S, Fabian J. Risk factors for the development of chronic kidney disease with HIV/AIDS. Clin Nephrol. 2010;74(Suppl 1):S51\u0026ndash;6.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnyabolu EN, Chukwuonye II, Arodiwe E, et al. Prevalence and predictors of chronic kidney disease in newly diagnosed human immunodeficiency virus patients in Owerri, Nigeria. Indian J Nephrol. 2016;26(1):10\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eOkpa HO, Elvis MB, Ofem E, et al. Predictors of chronic kidney disease among HIV\u0026ndash;infected patients on highly active antiretroviral therapy at the University of Calabar Teaching Hospital, Calabar, South-South Nigeria. HIV AIDS (Auckl). 2019;11:61\u0026ndash;7.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMeredith G. Coronavirus cause: Origin and how it spreads. Newsletter; 2020.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eLouis N, Robert K, Pauline B. Prevalence of renal dysfunction among HIV infected patients receiving Tenofovir at Mulago: a cross-sectional study. BMC Nephrol. 2020;21:232.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eCoulibaly A, et al. Prevalence of CKD among HIV patients on HAART in Ivory Coast. Afr J Nephrol. 2021;24(1):12\u0026ndash;8.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAmira CO, et al. Prevalence and associations of chronic kidney disease among ART-na\u0026iuml;ve persons living with HIV in Lagos, Nigeria. West Afr J Med. 2024;41(2):145\u0026ndash;52.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eBeaglehole R, Yach D. Globalisation and the prevention and control of non-communicable disease: the role of the World Health Organization. BMC Public Health. 2003;3:23.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMaggiolo F, et al. Renal dysfunction in HIV-infected patients: a South African perspective. J Antimicrob Chemother. 2021;76(2):440\u0026ndash;47.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eManaye B, Tesfaye T, Molla G, et al. Chronic kidney disease and associated factors among HIV/AIDS patients on antiretroviral therapy in Southern Ethiopia. BMC Nephrol. 2020;21:188.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMulenga LB, Musonda P, Mayondi GK, et al. Prevalence of renal dysfunction and associated risk factors among HIV-infected adults in Lusaka, Zambia. BMC Nephrol. 2015;16:75.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMocroft A, Kirk O, Reiss P, et al. Estimated glomerular filtration rate, chronic kidney disease and antiretroviral drug exposure: the Data Collection on Adverse Events of Anti-HIV Drugs (D:A:D) study. AIDS. 2010;24(9):1357\u0026ndash;65.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eKopp JB, Nelson GW, Sampath K, et al. APOL1 genetic variants in the African diaspora and kidney disease. Nat Rev Nephrol. 2020;16(11):631\u0026ndash;40.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAgbaji OO, Onu A, Agaba PE, et al. Predictors of impaired renal function among HIV infected patients commencing highly active antiretroviral therapy in Jos, Nigeria. Niger Med J. 2022;52:182\u0026ndash;5.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eAnyabolu EN, Chukwuanukwu RC. Gender and chronic kidney disease in HIV-subjects in South-East Nigeria. J Trop Dis. 2016;4:218.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eSigel K, et al. COVID-19 Outcomes Among People Living With HIV in New York City: A Matched Cohort Study. Clin Infect Dis. 2020;71(15):1933\u0026ndash;9.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eMellor AC, et al. Outcomes of HIV-infected patients hospitalized with COVID-19. J Am Soc Nephrol. 2021;32:201\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eZhang H, et al. Estimated glomerular filtration rate in post-COVID-19 patients at 12\u0026ndash;18 months: a longitudinal cohort study. BMC Med. 2025;23(1):44.\u003c/span\u003e\u003c/li\u003e \u003cli\u003e\u003cspan\u003eShiau S, et al. HIV and SARS-CoV-2 Co-infection: Epidemiological, Clinical Features, and Future Implications. Curr HIV/AIDS Rep. 2022;19(1):1\u0026ndash;11.\u003c/span\u003e\u003c/li\u003e\u003c/ol\u003e"}],"fulltextSource":"","fullText":"","funders":[],"hasAdminPriorityOnWorkflow":false,"hasManuscriptDocX":true,"hasOptedInToPreprint":true,"hasPassedJournalQc":"","hasAnyPriority":false,"hideJournal":false,"highlight":"","institution":"","isAcceptedByJournal":false,"isAuthorSuppliedPdf":false,"isDeskRejected":"","isHiddenFromSearch":false,"isInQc":false,"isInWorkflow":false,"isPdf":false,"isPdfUpToDate":true,"isWithdrawnOrRetracted":false,"journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true},"keywords":"COVID-19, Chronic Kidney Disease, Renal dysfunction, Co-infection, HIV, Africa, Nigeria","lastPublishedDoi":"10.21203/rs.3.rs-8902316/v1","lastPublishedDoiUrl":"https://doi.org/10.21203/rs.3.rs-8902316/v1","license":{"name":"CC BY 4.0","url":"https://creativecommons.org/licenses/by/4.0/"},"manuscriptAbstract":"\u003ch2\u003eBackground\u003c/h2\u003e \u003cp\u003eCoronavirus disease 2019 (COVID-19), caused by Severe Acute Respiratory Syndrome Coronavirus 2 (SARS-CoV-2), remains a significant global health challenge. People living with human immunodeficiency virus (HIV) may face an elevated risk of severe complications, particularly those with low CD4 counts, high viral loads, advanced clinical disease, or antiretroviral therapy (ART) non-adherence. Lockdown-related ART disruptions further compounded these risks. This study aimed to evaluate the prevalence of Chronic Kidney Disease (CKD) among HIV patients co-infected with COVID-19.\u003c/p\u003e\u003ch2\u003eMethods\u003c/h2\u003e \u003cp\u003eA hospital-based cross-sectional study was conducted with 423 participants. SARS-CoV-2 status was determined via real-time polymerase chain reaction (PCR). CKD was defined as an estimated glomerular filtration rate (eGFR)\u0026thinsp;\u0026lt;\u0026thinsp;60 mL/min/1.73 m\u0026sup2; (using the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) without race coefficient) calculated using serum creatinine values obtained via Jaffe\u0026rsquo;s method and/or proteinuria\u0026thinsp;\u0026ge;\u0026thinsp;+\u0026thinsp;1 identified through dipstick urinalysis persistent over three months. Data were analyzed using SPSS version 21, Student\u0026rsquo;s t-tests for continuous variables and chi-square tests for categorical associations.\u003c/p\u003e\u003ch2\u003eResults\u003c/h2\u003e \u003cp\u003eThe prevalence of COVID-19 infection was 13.5%. Notably, 56.6% of infected individuals had received two or more vaccine doses, and 73.5% were asymptomatic. The overall prevalence of CKD was 8.4%, with a higher proportion observed in females. Among HIV/COVID-19 co-infected patients, CKD prevalence was 1.5%. HIV viral suppression (p\u0026thinsp;=\u0026thinsp;0.003) and proteinuria\u0026thinsp;\u0026ge;\u0026thinsp;+\u0026thinsp;1 (p\u0026thinsp;\u0026lt;\u0026thinsp;0.001) were significantly associated with CKD status.\u003c/p\u003e\u003ch2\u003eConclusions\u003c/h2\u003e \u003cp\u003eThe study indicates that COVID-19 co-infection does not result in a higher CKD among HIV patients compared to those without the virus. However, prolonged ART duration, gender, education level, and socio-occupational status were identified as significant risk factors. Additionally, the high infection rate of COVID-19 among the vaccinated participants suggests a need for further research into vaccine efficacy and the impact of various COVID-19 vaccines within this cohort.\u003c/p\u003e","manuscriptTitle":"Prevalence of Chronic Kidney Disease (CKD) among Patients Co-infected with COVID-19 and HIV at the University of Ilorin Teaching Hospital, Ilorin, Nigeria","msid":"","msnumber":"","nonDraftVersions":[{"code":1,"date":"2026-03-18 10:13:25","doi":"10.21203/rs.3.rs-8902316/v1","editorialEvents":[{"type":"communityComments","content":0},{"type":"decision","content":"Revision requested","date":"2026-04-16T17:45:57+00:00","index":"","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-12T19:06:29+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-06T15:44:54+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-04-02T17:23:18+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"13150366923005484165847355227086977884","date":"2026-04-01T15:05:37+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-29T14:44:45+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"246451172457002850795898854505114502061","date":"2026-03-29T14:13:29+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"321450265275599141423374703897302034180","date":"2026-03-28T10:08:09+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"209302880878832783874105636477845539713","date":"2026-03-27T10:28:33+00:00","index":"hide","fulltext":""},{"type":"editorInvitedReview","content":"","date":"2026-03-26T12:27:19+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"23325831474122965621556182127658926396","date":"2026-03-25T12:01:25+00:00","index":"hide","fulltext":""},{"type":"reviewerAgreed","content":"143405743537331064569268995391750611521","date":"2026-03-24T01:37:58+00:00","index":"hide","fulltext":""},{"type":"reviewersInvited","content":"","date":"2026-03-17T07:39:55+00:00","index":"","fulltext":""},{"type":"editorInvited","content":"","date":"2026-02-23T05:28:53+00:00","index":"","fulltext":""},{"type":"editorAssigned","content":"","date":"2026-02-21T10:18:24+00:00","index":"","fulltext":""},{"type":"checksComplete","content":"","date":"2026-02-21T10:17:36+00:00","index":"","fulltext":""},{"type":"submitted","content":"BMC Nephrology","date":"2026-02-17T14:56:08+00:00","index":"","fulltext":""}],"status":"published","journal":{"display":true,"email":"[email protected]","identity":"bmc-nephrology","isNatureJournal":false,"hasQc":true,"allowDirectSubmit":false,"externalIdentity":"bnep","sideBox":"Learn more about [BMC Nephrology](http://bmcnephrol.biomedcentral.com/)","snPcode":"","submissionUrl":"https://www.editorialmanager.com/bnep/default.aspx","title":"BMC Nephrology","twitterHandle":"BMC_series","acdcEnabled":true,"dfaEnabled":false,"editorialSystem":"em","reportingPortfolio":"BMC Series","inReviewEnabled":true,"inReviewRevisionsEnabled":true}}],"origin":"","ownerIdentity":"fabfbd1f-2935-47ba-ba87-ac7dae986a29","owner":[],"postedDate":"March 18th, 2026","published":true,"recentEditorialEvents":[],"rejectedJournal":[],"revision":"","amendment":"","status":"in-revision","subjectAreas":[],"tags":[],"updatedAt":"2026-04-16T17:54:37+00:00","versionOfRecord":[],"versionCreatedAt":"2026-03-18 10:13:25","video":"","vorDoi":"","vorDoiUrl":"","workflowStages":[]},"version":"v1","identity":"rs-8902316","journalConfig":"researchsquare"},"__N_SSP":true},"page":"/article/[identity]/[[...version]]","query":{"redirect":"/article/rs-8902316","identity":"rs-8902316","version":["v1"]},"buildId":"XKTyCvWXoU3ODBz1xrDgd","isFallback":false,"isExperimentalCompile":false,"dynamicIds":[84888],"gssp":true,"scriptLoader":[]}