Comparison of the prevalence and associated factors of chronic kidney disease diagnosed by serum creatinine or cystatin C among young people living with HIV in Uganda

33 34

35 Young people living with HIV (YPLHIV) are at increased risk of developing chronic kidney disease 36 (CKD) which is associated with high mortality and morbidity. Early diagnosis is important to halt 37 progression. We aimed to estimate the prevalence and factors associated with CKD among YPLHIV in 38 Kampala, Uganda, and to compare serum creatinine and cystatin C for early diagnosis of CKD in this 39 population. 40

41 A cross-sectional study with YPLHIV aged 10 to 24 years was conducted in seven HIV clinics. 42 Participants provided a urine and blood sample to measure urinary albumin, proteinuria, serum creatinine 43 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 3 and cystatin C levels at baseline and after three months. The estimated glomerular filtration rate (eGFR) 44 was calculated using CKDEPI 2021, Cockroft-Gault and bedside Schwartz equations using creatinine or 45 cystatin C. The albumin creatinine ratio (ACR) and proteinuria were measured. CKD was defined as 46 either eGFR <60ml/min/1.73m2 or <90ml/min/1.73m2 or ACR above 30mg/g on two separate occasions. 47 Univariable and multivariable logistic regression were used to estimate adjusted odds ratios (aOR) and 48 95% confidence intervals (CI) for factors associated with CKD. 49

50 A total of 500 participants were enrolled. Most were female (56%; n=280) and aged 10 to 17 years 51 (66.9%; n=335). CKD prevalence ranged from 0-23% depending on the criteria, equation and biomarker 52 used. Cystatin C-based equations estimated higher prevalence of CKD compared to creatinine-based ones. 53 Prevalence of ACR above 30mg/g was 10.1% and of proteinuria 29%. Factors independently associated 54 with CKD were age (aOR=1.42; 95% CI:1.30-1.51) and male sex (aOR=3.02; 95% CI:1.68-5.43). 55

56 CKD prevalence among YPLHIV varied substantially depending on definitions used and the current 57 definition would likely lead to missed cases of CKD among YPLHIV. Estimating equations should be 58 validated against measured GFR in YPLHIV and the optimal definition of CKD in this vulnerable 59 population should be revised to optimise detection and opportunities for reducing disease progression. 60 61 Key words: prevalence, chronic kidney disease, young people, HIV, Africa, HIV comorbidities 62 63 64

65 Prevalence of chronic kidney disease (CKD) is increasing globally (1). CKD is defined as abnormalities 66 in kidney structure or function present for three or more months (2). The Global Burden of Disease study 67 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 4 estimates CKD prevalence at 9.1% (95% CI 8.5%-9.8%) with geographic variation (3). Studies in Sub-68 Saharan Africa (SSA) find prevalence ranging from 6%-48% depending on the population, the definitions 69 used, and the measurements taken (4-6). 70 Young people living with HIV (YPLHIV) are at higher risk of CKD than young people not living with 71 HIV (7). CKD risk is associated with high HIV viremia (>4000 copies per ml), severe 72 immunosuppression (CD4 cell count <200 cells/ml), infection with hepatitis C virus, diabetes, 73 hypertension, use of drugs that treat opportunistic infections, and toxicity due to anti-retroviral therapy 74 (ART) from tenofovir disoproxil fumarate (TDF) and indinavir (6, 8-11). Further, YPLHIV in SSA are 75 particularly vulnerable to developing CKD compared to adults living with HIV due to late HIV diagnosis 76 and initiation on ART, poorer adherence to ART complicated by high viremia and low CD4 cell counts 77 (12-14). 78 CKD is associated with high morbidity and mortality as diagnosis is usually delayed, often occurring after 79 kidney failure due to its insidious onset (15). Kidney failure can only be treated with expensive kidney 80 replacement therapies that are not readily available in low and middle-income countries (16). Early 81 diagnosis is important to minimise risk of progression to kidney failure and cardiovascular events (17). 82 Diagnosis of CKD is based on the level of glomerular filtration rate (GFR) and markers of kidney damage 83 such as protein excretion into the urine shown by proteinuria or albuminuria (18). GFR can either be 84 measured directly (mGFR) or estimated (eGFR) with a specific biomarker and one of the estimating 85 equations (19). Most commonly, serum creatinine and cystatin C estimating equations are used to 86 estimate GFR (18, 20). Serum creatinine is widely available and relatively cheap (21) but has limitations 87 as it is influenced by muscle mass, physical activity and general health status (22) as well as high analytic 88 variability (21). Cystatin C is not affected by these conditions as it is produced by most nucleated cells 89 and has uniform generation despite individual differences in people and situations (22-24). However, it is 90 affected by conditions of high inflammation, corticosteroid use and thyroid disease (25). Cystatin C more 91 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 5 accurately estimated measured GFR compared to creatinine (26) in a large cohort study done across 92 Uganda, Malawi and South Africa that recommended the use of Cystatin C in African populations (4). 93 Although YPLHIV are at high risk of CKD, little is known about CKD prevalence, the best biomarker to 94 diagnose CKD and factors associated with CKD in this vulnerable group. Therefore, we sought to study 95 this among YPLHIV in Kampala, Uganda. 96

97 Study design and setting: This cross-sectional study was conducted in the HIV clinics of seven urban 98 public health facilities from the 12th of April 2023 to 31st January 2024 in Kampala, Uganda. These offer 99 comprehensive HIV care to children (aged below 18 years) and adults (aged 18 years and above). 100 Study population and sampling: The study included YPLHIV aged 10-24 years with presumed perinatal 101 HIV infection (defined as being diagnosed with HIV before 10 years of age with self-report of no sexual 102 debut or blood transfusion prior to diagnosis). Pregnant YPLHIV were excluded. Systematic random 103 sampling was used to identify potential participants from all YPLHIV enrolled in the seven HIV clinics 104 from electronic medical records. They were ordered by age at diagnosis and every third person invited to 105 join the study. A sample size of 500 was powered to detect a prevalence of CKD between 16% and 24%. 106 Study procedures: Eligible participants were invited to the HIV clinic through a phone call where they 107 were screened, consented, and enrolled. A trained study team member conducted an interview with the 108 participant and completed a questionnaire to record demographic information, symptoms, risk factors and 109 the relevant medical history. Anthropometric measurements (mid-upper arm circumference (MUAC), 110 weight and height) were taken. Weight was assessed using a digital weighing scale, height using a 111 stadiometer and blood pressure (BP) using a digital BP machine with a paediatric cuff for younger 112 participants. Body composition monitoring was conducted using bioimpedance impedance spectroscopy 113 (BIS) to measure body fat, muscle mass and visceral fat. Participants provided a spot urine sample (20 114 mls) as well as 8 ml of venous blood. Urine dipstick was done at the facility to determine proteinuria and 115 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 6 other urinary abnormalities. The samples were stored in a cooler box before transfer to the study 116 laboratory on the same day. 117 Laboratory methods and testing: In the laboratory, serum creatinine, urinary albumin and cystatin C 118 levels were determined. Those with an albumin creatinine ratio (ACR) >30mg/g or eGFR 119 <60ml/min/1.73m2 at baseline were followed-up after three months to confirm the KDIGO guideline-120 recommended clinical diagnosis of CKD. Cystatin C was measured by particle-enhanced 121 immunoturbidimetric assay on Roche Cobas C311 platform with Tina-quant Cystatin C Gen.2. Creatinine 122 was measured using the enzymatic calorimetric method using an isotope dilution mass spectroscopy 123 (IDMS) traceable standard reference material on the Cobas Integra 400 plus machine with Creatinine Plus 124 Version 2 (CREP2), Roche Diagnostics. The urine albumin was quantified using the 125 immunoturbidimetric assay on the Roche Cobas C311 platform using Tina/i1quant Albumin Gen2, (Roche 126 Diagnostics). Prior to testing, the machines were calibrated according to manufacturer instructions. 127 Urinalysis by dipstick was done with AYDMED urinalysis Reagent Test Strips (Sungo Europe B.V 128 Amsterdam) to determine presence of urobilinogen, bilirubin, ketones, blood, proteins, nitrites, 129 leucocytes, glucose, specific gravity, pH, and ascorbic acid (27). 130 Diagnosis of CKD was based on the kidney disease improving global outcomes (KDIGO) guidelines 131 (28), i.e. 1) markers of kidney damage such as an albumin: creatinine ratio >30mg/g, or 2) eGFR 132 <60ml/min/1.73m2 , with these abnormalities confirmed with a repeat test after three months (29). To 133 explore CKD definition in this cohort that included children and where chronic disease had affected 134 pubertal development and mean body and muscle mass, we primarily used a range of GFR estimating 135 equations and eGFR cut offs that reflected contemporary practice for adults and children and/or sought to 136 adjust for body size. eGFRscr was estimated using the following creatinine-based equations: CKD 137 Epidemiology collaboration (CKDEPI) 2021 (30), the Bedside Schwartz (31), and Cockroft-Gault. 138 eGFRcystc was estimated using the following cystatin C-based equations: Schwartz cystatin C (32) and 139 CKDEPI 2012 (33). For completeness prevalence was also estimated using other relevant equations (Full 140 Age Spectrum, CKDEPI40 and Pierce U25), and in combination with ACR and proteinuria. Since a 141 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 7 normal GFR is between 90-120 ml/min/1.73m2, we also considered a eGFR cut off below 142 90ml/min/1.73m2 which is considered stage 2 CKD as abnormal in such a young population (34). 143 Data management and statistical analysis: Data were collected in REDCap and analysed with STATA 144 statistical software version 18 (STATA Corp USA). Viral suppression was considered as an HIV viral 145 load below 1000 copies/ml. Hypertension was classified according to the AAP guidelines as being above 146 the 95th percentile for age and sex below 13 years and above 130/80 in those above 13 years (35). Muscle 147 mass was abnormal if below 33.3 for males and 24.3 for females. Social economic status was divided into 148 three using principal component analysis. Demographic data were summarised in percentages or means 149 (standard deviation) and median (interquartile range). The distribution of eGFRs estimated with different 150 equations was shown in a Kernel density plot. CKD prevalence diagnosed by either creatinine or cystatin 151 C was calculated. Univariable logistic regression was used to estimate odds ratios (OR) of factors 152 associated with CKD for each of the five equations used, respectively. All variables with p<0.2 in the 153 univariable model, and a-priori identified variables known to be associated with CKD (age, sex, HIV viral 154 suppression, blood pressure) were then included in a multivariable logistic regression model for each of 155 the five equations. 156 Ethical considerations 157 Ethical approval was received from the Uganda Virus Research Institute (UVRI) Research Ethics 158 Committee (reference number GC/127/946), the Uganda National Council of Science and Technology 159 (HS2578ES) and the London School of Hygiene and Tropical Medicine institutional review board 160 (28797). Information about the study appropriate for adults, semi-literate adults and children was 161 provided in an information booklet that was read to the participants and caregivers. All the participants 162 more than 18 years of age provided a written informed consent. Those below 18 years of age provided 163 assent and their caregivers provided written informed consent. If a child refused to provide assent even 164 after their caregiver had provided consent, that child was not enrolled into the study. All participants had 165 the option to withdraw at any point during the research. All participants with suspected CKD were 166 referred to a nephrologist for management. 167 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 8

168 Of 532 YPLHIV invited to participate, 500 were enrolled as the 32 declined to participate (Table 1). The 169 majority were female (56.0%; n=280), children aged 10-17 years (66.9%; n=335) and living in Kampala 170 (58.9%; n=295). Females had better nutritional indicators than males - they were less likely to be 171 underweight (26.4% vs 48.9%; p<0.001), not stunted (85.6% vs 76.9%; p=0.03), and to have normal mid 172 upper circumference (92.9% vs 87.7%; p=0.05). 173 Table 1: Demographic characteristics of the study participants by sex. 174 Male Female Total N=220 (44%) N=280 (56%) N=500 Age (mean, SD) 16.5 (3.8) 16.3 (3.5) 16.4 (3.6) Age category Children 143 (65.0) 191 (68.2) 334 (66.8) Adults 77 (35.0) 89 (31.8) 166 (33.2) Address Kampala 123 (55.9) 171 (61.1) 294 (58.8) Wakiso 80 (36.4) 99 (35.4) 179 (35.8) Othe r distric ts 17 (7.7) 10 (3.6) 27 (5.4) Religion Christian 158 (71.8) 204 (72.9) 362 (72.4) Moslem 62 (28.2) 73 (26.1) 135 (27.0) Othe r 0 (0.0) 3 (1.1) 3 (0.6) Social Eco nomi c Status Lowest 78 (35.5) 100 (35.7) 178 (35.6) Middle 61 (27.7) 94 (33.6) 155 (31.00 Highest 81 (36.8) 86 (30.7) 167 (33.4) School goi ng No 58 (26.4) 67 (23.9) 125 (25.0) Yes 162 (73.6) 213 (76.1) 375 (75.0) Marital Status Marri ed 3 (1.4) 16 (5.7) 19 (3.80) Never mar ried 217 (98.6) 264 (94.3) 481 (96.2) Tribe Ganda 149 (67.7) 174 (62.1) 323 (64.6) Othe r trib es 65 (29.5) 86 (30.7) 151 (30.2) Non-Ugandan 6 (2.7) 20 (7.1) 26 (5.2) Weight mean (SD) 48.0 (12.4) 49.4 (12.4) 48.8 (12.4) Body Mass Index 1 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 9 Normal 173 (79.0) 214 (76.4) 387 (77.6) Underweigh t (25kg/m 2 ) 8 (3.7) 42 (15.0) 50 (10.0) Stunting** Not stu nted 123 (76.9) 184 (85.6) 307 (81.9) Stunt ed 37 (23.1) 31 (14.4) 68 (18.3) Mid Upper Ar m Circumfere nce 2 Normal 192 (87.7) 260 (92.9) 452 (90.6) Malnourish ed 27 (12.3) 20 (7.1) 47 (9.4) On TDF regimen No 61 (27.7) 66 (23.6) 127 (25.4) Yes 159 (72.3) 214 (76.4) 373 (74.6) Virally suppressed Yes 195 (89.5) 247 (88.5) 442 (88.9) No 23 (10.5) 32 (11.5) 55 (11.1) Muscle mass 2 Normal muscle mass 164 (82.0) 235 (87.7) 399 (85.3) Abnormal muscle mass 36 (18.0) 33 (12.3) 69 (14.7) * Living outside Kampala/Wakiso region. # included those with no religion and those of African traditional religion. 175 **Only those aged less than 19 years. 1 one missing, 2. 32 missing as their measurements were below threshold of 176 the BIS machine. 177 Comparison of serum creatinine and cystatin C 178 The mean serum creatinine (scr) was 0.63 mg/dl (SD 0.15) with a range of 0.29 to 1.2mg/dl. The mean scr 179 was significantly different according to sex, age, presence of stunting or viral suppression. The mean 180 cystatin C was 0.81 mg/dl (SD 0.13) with a range of 0.51 to 1.39 mg/dl. The mean cystatin C was higher 181 in males at 0.86 mg/dl versus 0.78 mg/dl in females but with no other differences (Supplemental table 182 1). Serum creatinine but not cystatin C was correlated with age and sex (Figure 1). 183 Figure 1: Relationship between serum creatinine and cystatin C and age for males and females 184 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 10 185 Distribution of the eGFR 186 CKDEPI consistently gave higher eGFR readings for both creatinine and cystatin C, and the Schwartz 187 cystatin C equation gave the lowest eGFR values (Figure 2). 188 Figure 2. Kernel density plot showing the distribution of the eGFR according to different estimating 189 equations and biomarkers. 190 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 11 191 Scr serum creatinine, CG cockroft Gault, cys Cystatin C 192 Prevalence of CKD using eGFR 193 CKD prevalence varied according to the eGFR cut-off, and the biomarker used. Using an 194 eGFR<60ml/min/1.73m2 cut-off, the highest prevalence was with the Schwartz cystatin C equation 195 (1.4%; 95% CI: 0.5-2.9% at baseline; 0.8%; 95% CI: 0.2-2.1% at 3-month follow-up) and the lowest with 196 the CKDEPI 2021 equation (0%; 95% CI 0-0.07%). Similarly, using eGFR< 90ml/min/1.73m2 cut-off, 197 the highest prevalence was with the Schwartz cystatin C equation (58.9%; 95% CI: 54.4-63.3%) and the 198 lowest with CKDEPI (0.6%; 95% CI: 0.01-1.7%) (Figure 3). Prevalence using other eGFR equations 199 ranged from 0% to 27.5% (Supplementary Table 2). 200 Figure 3 Prevalence of CKD according to the different estimating equations and biomarkers. 201 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 12 202 Prevalence of CKD according to eGFR and ACR 203 All participants were staged according to combined baseline eGFR using cystatin C and ACR to assess 204 risk of progression (28). Overall, 438 (88.5%) participants had low risk of progression (green), 53 205 (10.7%) had intermediate risk of progression (yellow) and 4 (0.8%) were at high risk of progression 206 (orange) (Table 2). 207 Table 2. All participants’ CKD status staged according to estimated GFR from cystatin C and 208 albumin creatinine ratio at baseline. 209 eGFR and ACR categories ACR categories in mg/g 300 Severely increased Total numbers eGFR Stage A1 A2 A3 >90 Normal and high G1 178 (36.0%) 24 (4.9%) 1 (0.2%) 203 (41.1%) 60-89 Mild reduction G2 258 (52.2%) 24 (4.9%) 2 (0.2%) 284 (57.5%) 45-59 Mild to moderate reduction G3a 5 (1.0%) 2 (0.4%) 0 (0%) 7 (1.4%) 441 (89.3%) 50 (10.1%) 3 (0.6%) 494* (100%) . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 13 eGFR estimated glomerular filtration rate, ACR Albumin creatinine ratio, *6 participants were missing 210 serum creatinine and cystatin C results. 211 Prevalence of CKD according to markers of kidney damage 212 Urinalysis showed that 143 (29%) participants had proteinuria on dipstick. Prevalence of proteinuria was 213 similar for those with eGFR>90ml/min/1.73m2 and 30mg/g. 215 Factors associated with CKD. 216 Factors associated with CKD varied with the equation and biomarker used for those with an eGFR 217 <90ml/min/1.73m2 (Table 3) but was largely associated with male sex (with the exception of 218 CKDEPI2021), viral non-suppression (by the cystatin C based equations), increasing age (by the CKDEPI 219 and Bedside Schwartz equations), and being overweight (with the exception of the Cockroft-Gault 220 equation). CKD was also associated with proteinuria (by the CKDEPI 2012 equation) and being on a 221 TDF-based regimen (by the Bedside Schwartz equation). There was no evidence that CKD was associated 222 with high blood pressure, muscle mass, and ACR. 223

were similar when using CKD defined by eGFR<60ml/min/1.73m2 (Supplementary Table 3). 224 Table 3. Factors associated with having CKD (eGFR <90 ml/min/1.73m2) among st udy participants 225 accordi ng to the different estimating eq uations and biomarkers. 226 OR Odds ratio ART Anti-retroviral therapy. N Number, eGFR estimated glomerular filtration rate* 227 Adjusted for age, sex, blood pressure, viral suppression proteinuria, baseline CD4 T cell count. 228

229 This is the first study to compare the prevalence and factors associated with CKD diagnosed by creatinine 230 and cystatin C among YPLHIV in Uganda according to standard guidelines. We found highly variable 231 prevalence depending on the definition, the estimating equation and the biomarker used. This was 232 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 14 compounded by the commonly used GFR estimating equations being recommended for adults or children 233 only, despite the highly variable physical and sexual maturity within this important age group where long-234 term disease management is critical. Using cystatin C eGFR measures consistently gave substantially 235 higher prevalence of CKD: using the Schwartz cystatin equation approximately 60% of YPLHIV had 236 eGFR <90mls/min/1.73m2. While dipstick proteinuria is anticipated in this population largely treated with 237 anti-retroviral drugs, 10% of participants had substantially elevated levels of albuminuria. However, when 238 participants with baseline abnormalities were remeasured at 3 months according to the gold-standard 239 definition, overall prevalence of CKD was much lower. 240 The highest prevalence (59%) using an eGFR cutoff <90ml/min/1.73m2 at baseline which fell to 23% at 241 three months follow-up, was very high. This is similar to a study done in 96 Nigerian YPLHIV aged 15 to 242 29 years which found 53.3% prevalence (36) and a Tanzanian study among 240 YPLHIV aged less than 243 14 years that showed a prevalence of 28% (37). When kidney function was determined by eGFR below 244 60ml/min/1.73m2 on two separate occasions at least three months apart, the prevalence of CKD was 245 0.8%. This is lower than in a study done in Zambia among children living with HIV aged 1 to 18 years 246 that found a prevalence of 3.8% after 3 months (38). However, the children in this study were younger 247 than in this study. 248 Using a eGFR cut off of less than 60ml/min/1.73m2 excludes a large proportion of YPLHIV who are 249 already showing signs of impaired kidney function such as an ACR above 30mg/g, proteinuria and 250 hypertension, and who would benefit from early intervention to halt progression of their kidney disease 251 (39). Pottel et al. have shown that clinical manifestations of decreased kidney function in young people 252 start at GFR less than 75ml/min/1.73m2; they recommend that the CKD definition should be revised to 253 reflect this (40). 254 KDIGO recommends that screening and surveillance for CKD be tailored to the specific high risk group 255 (41). Our study suggests that using sequential estimation of eGFR over three months excludes YPLHIV at 256 risk of CKD, and might be misleading to the public health response whose goal is to halt progression and 257 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 15 to predict those who are in danger of kidney failure or development of cardiovascular complications (41). 258 KDIGO further recommends that screening frequency should be based on the risk profile of the individual 259 and potential to progress (42). YPLHIV have the potential to progress due to the continued insult to the 260 kidney, one abnormal eGFR measurement that shows reduced kidney function should be sufficient for 261 them to be followed up regularly and managed. 262 Estimating GFR in this population was challenging as the different estimating equations and biomarkers 263 gave very different results. This was worse as one transitioned from equations meant for those below 18 264 years to those equations meant for adults above 18 years. The difference in the eGFR was wide even in 265 the same individual. It is difficult to determine the true estimate for CKD among YPLHIV using these 266 estimating equations yet knowing the true estimate is important to plan the public health response for 267 CKD (15). Clinicians who seek to diagnose CKD and plan management may get confused about the true 268 CKD status of an individual. Misdiagnosis and classification of YPLHIV removes the opportunity to 269 intervene early to halt progression to kidney failure (43). However, it is not surprising that each of the 270 estimating equations gave a different prevalence since each estimating equation reflects the characteristics 271 of the population/dataset that was used to develop it (44). There is an urgent need to develop estimating 272 equations for Africans living in Africa. 273 The use of GFR alone doesn’t predict progression or mortality risk and other markers of kidney damage 274 such as albuminuria or proteinuria are used (13, 45). When ACR was used, the prevalence was 10.1%. 275 This is lower than that reported among a Tanzanian cohort of YPLHIV aged 1 to 14 years which found a 276 prevalence of 20.1% (37). However, the ACR was determined at a single time point and included younger 277 children. Proteinuria prevalence was 29% which was high in such a young population. Proteinuria is an 278 early marker of HIV associated nephropathy (46) and if persistent, is predictive of CKD status in children 279 (47). However, we measured proteinuria only at baseline and yet two positive out of three readings are 280 used to diagnose persistent proteinuria (41). 281 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 16 Cystatin C emerged as a better biomarker than serum creatinine as eGFR calculated from Cystatin C was 282 above CKD stage 1 more consistently for all those that had an increased ACR, proteinuria or hypertension 283 which are markers of abnormal kidney function (18). Cystatin C was recommended by a recent study in 284 three countries (Uganda, Malawi, and South Africa) as the better biomarker in Africans (4). Cystatin C 285 should be recommended for the diagnosis of CKD in YPLHIV as well. 286 We found that age, sex, and HIV viral non-suppression were associated with CKD and that proteinuria, 287 CD4 cell count, blood pressure, and being on a TDF regimen were not associated. A study among 288 perinatally infected YPLHIV in South Africa with a mean age of 12.0 years found sex, but not age or 289 blood pressure were associated with CKD (48). Males were also found to have more CKD than females in 290 a study in Zimbabwe (49). TDF use was also not associated with CKD status in a cohort of American 291 children with CKD (50). 292 293 One of the strengths of this study is that we estimated the eGFR at two different time points more than 294 three months apart as recommended by KDIGO and were able to ascertain those that actually had CKD 295 according to the standard definition of CKD. However, most of the GFR estimating equations and normal 296 serum creatinine have not been validated in YPLHIV in resource-limited settings especially in Africa and 297 this makes it that much harder to determine the abnormal values in YPLHIV (4, 51). This could explain 298 the low correlation between eGFR and the markers of kidney damage found in this study. We determined 299 both markers of kidney damage (albuminuria and proteinuria) and function and could tell YPLHIV that 300 were at risk of CKD progression. The biggest limitation is that we did not measure the GFR using either 301 ioxehol or the nuclear tracers 99mTc-diethylenetriaminepentaacetic acid (DTPA) or 51Cr-EDTA (10) and 302 so we are unable to tell how accurate the eGFR was. 303

304 CKD prevalence among YPLHIV in Uganda varies widely depending on the biomarker and definition 305 used. However, there is a substantial prevalence of albuminuria and reduced eGFR suggesting HIV 306 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 17 programs should prioritize screening for CKD among YPLHIV. The definition of CKD and best 307 biomarker to use in YPLHIV should be further investigated to optimise detection of those with early 308 abnormalities of kidney function. Estimating equations should be validated against measured GFR in 309 young people to define how best to estimate GFR across older children and young adults in Africa. 310 List of abbreviations 311 ACR Albumin Creatinine Ratio AIDS Acquired Immune Deficiency Syndrome ALHIV Adolescents living with HIV ART Anti-Retroviral Therapy BIS Bioimpedance Spectroscopy BMI Body Mass Index CAKUT Congenital abnormalities of the Kidney and Urinary Tract CALHIV Children and Adolescents living with HIV CAP College of American Pathologists CBC Complete Blood Count CD4 Cluster of differentiation 4 CKD Chronic Kidney Disease CKD-EPI Chronic Kidney Disease Epidemiology Collaboration DM Diabetes Mellitus ESKD End stage kidney disease . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 18 EKFC European Kidney Function Consortium FAS Full Age Spectrum GFR Glomerular Filtration Rate HB Haemoglobin HIV Human Immunodeficiency Virus HIVAN HIV associated Nephropathy HIVICK HIV Immune Complex Kidney Disease HW Health Worker IQR Interquartile Range KDIGO Kidney Disease Improving Global Outcomes KRT Kidney replacement therapy MDRD Modification of Diet in Renal Disease MOH Ministry of Health NCD’s Non-Communicable Diseases PCR Protein Creatinine Ratio PLHIV People Living with HIV AIDS RAAS Renin Angiotensin Aldosterone Systems RCT Randomised Controlled Trials SSA Sub Saharan Africa . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 19 TB Tuberculosis UNAIDS United Nations Joint AIDS program USA United States of America WHO World Health Organization YPLHIV Young People Living with HIV 312 Declarations 313 Ethics approval and consent to participate 314 Ethical approval was received from the Uganda Virus Research Institute (UVRI) Research Ethics 315 Committee (reference number GC/127/946), the Uganda National Council of Science and Technology 316 (HS2578ES) and the London School of Hygiene and Tropical Medicine institutional review board 317 (28797). Information about the study appropriate for adults, semi-literate adults and children was 318 provided in an information booklet that was read to the participants and caregivers. All the participants 319 more than 18 years of age provided a written informed consent. Those below 18 years of age provided 320 assent and their caregivers provided written informed consent. If a child refused to provide assent even 321 after their caregiver had provided consent, that child was not enrolled into the study. All participants had 322 the option to withdraw at any point during the research. All participants with suspected CKD were 323 referred to a nephrologist for management. 324 Consent for publication: Not applicable 325 Availability of data and materials 326 The data supporting the findings of this study are openly available in repository 327 https://datacompass.lshtm.ac.uk/. 328 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 20 Competing interests 329 The authors declare no conflict of interest. 330 Funding 331 Support for research was provided by Fogarty International Centre, National Institutes of Health (grant 332 #2D43TW009771-06) HIV and co-infections in Uganda. HAW is funded by the UK Medical Research 333 Council (MRC) and the UK Department for International Development (DFID) under the MRC/DFID 334 Concordat agreement (Grant 1: MR/R010161/1). EN, Doctoral Research Fellow, NIHR131273 is funded 335 by the NIHR for this research project. The views expressed in this publication are those of the authors and 336 not necessarily those of the NIHR, NHS or the UK Department of Health and Social Care. 337 Authors’ contributions 338 EN, LT, RK, CDC, DN, BC, YCM, HW contributed to the conceptualization and design of the study, data 339 collection, analysis, and interpretation. EN, LT, YK drafted the manuscript. CDC, BC, RK, YCM edited 340 the draft manuscript. HW was responsible for the overall supervision of this work. All authors reviewed 341 and approved the manuscript before submission for publication. 342

343 The authors acknowledge the health workers and peers at the implementing facilities where this data was 344 collected. The HIV program at the participating health facilities is supported by the President’s 345 Emergency Plan for AIDS Relief (PEPFAR) through CDC. 346 347 348

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(which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 25 eGFR<90ml/min/1.73m2 from Cystatin C based Equations eGFR<90ml/min/1.73m2from Serum Creatinine Based Equations CKD EPI 2012 (n=36/494) Schwartz Cystatin (n=291/494) CKDEPI 2021 (n=6/494) Bedside Schwartz (n=140/494) Cockroft Gault (n=68/493) Unadjusted OR Adjusted OR* Unadjusted OR Adjusted OR Unadjusted OR Adjusted OR Unadjusted OR Adjusted OR Unadjusted OR Adjusted OR Age in years 1.14 (1.03-1.25) 1.13 (1.01-1.27) 0.98 (0.94-1.04) 0.99 (0.94-1.04) 1.50 (1.13-1.98) 1.45 (1.01-2.14) 1.40 (1.30-1.51) 1.42 (1.28-1.58) 0.99 (0.94-1.04) 1.08 (0.96-1.22) Age categorized >18 1 1 1 1 1 1 <18 0.47 (0.33-0.92) 1.06 (0.73-1.55) 0.09 (0.01-0.83) 0.17 (0.11-0.26) 0.89 (0.52-1.52) 0.63 (0.23-1.77) Sex Females 1 1 1 1 1 Males 2.42 (1.2-4.92) 2.84 (1.27-6.31) 3.21 (2.18-4.71) 3.13 (2.12-4.65) 0.64 (0.12-3.52) 0.75 (0.11-4.92) 2.22 (1.49-3.32) 3.02 (1.68-5.43) 3.21 (2.18-4.71) 0.32 (0.16-0.60) Blood pressure Normal 1 1 1 1 1 1 1 1 1 Elevated 0.59 (0.17-1.98) 0.41 (0.86-1.90) 1.69 (0.95-2.98) 1.42 (0.79-2.59) 0.07 (0.00-0.63) 0.35 (.-.) 1.19 (0.66-2.17) 1.02 (0.45-2.31) 0.41 (0.21-0.78) 0.26 (0.08-0.80) Hypertensive 0.98 (0.39-2.45) 0.69 (0.26-1.89) 1.25 (0.76-2.06) 1.14 (0.67-1.94) 0.45 (0.04-4.04) 1.61 (0.24,10.63) 2.42 (1.46-4.02) 1.69 (0.89-3.29) 0.73 (0.35-1.50) 0.58 (0.18-1.86) Viral suppression Suppressed 1 1 1 1 1 1 1 Non suppressed 3.11 (1.38-7.04) 3.27 (1.29-8.32) 2.09 (1.11-3.97) 2.29 (1.18-4.44) 1.01 (0.00-7.12) 0.92 (.,.) 0.42 (0.19-0.91) 0.34 (0.13-0.89) 0.63 (0.24-1.64) 0.61 (0.21-1.74) CD4 T cell count at baseline >500 1 1 1 1 1 1 200-500 2.3 (0.98-5.38) 1.41 (0.55-3.59) 1.54 (0.96-2.48) 1.52 (0.03-29.58) 1.86 (1.03-3.04) 0.66 (0.35-1.25) 1.08 (0.56-2.10) <200 3.84 (1.5-9.38) 2.59 (0.97-6.92) 1.76 (0.96-3.22) 5.34 (0.38-75.78) 1.89 (1.04-3.46) 0.65 (0.29-1.44) 1.22 (0.56-2.68) Social Economic Status Least 1 1 1 1 1 Middle 1.03 (0.42-2.49) 0.96 (0.62-1.49) 2.28 (0.81-2.21) 1.34 (0.62-1.49) 1.32 (0.69-2.51) 1.04 (0.56-1.92) . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 26 Highest 1.47 (0.66-3.31) 1.15 (0.74-1.78) 1.85 (1.15-2.99) 1.15 (0.75-1.78) 1.40 (0.75-2.64) 0.81 (0.43-1.52) Body Mass Index Normal 1 1 1 1 1 1 Underweight 1.69 (0.82-3.43) 1.36 (0.92-2.01) 0.29 (0.00-2.30) 0.31 (0.18-0.51) 0.74 (0.32-1.68) 4.03 (2.29-7.09) 7.23 (3.33-15.7) Overweight 1.27 (0.35-4.56) 1.24 (0.63-2.43) 3.11 (0.27-22.51) 1.81 (0.94-3.51) 1.98 (0.68-5.74) 0.19 (0.00-1.12) Weight in Kg 1.02 (0.99-1.04) 1.01 (0.99-1.02) - 1.06 (1.04-1.09) 0.99 (0.96-1.04) Stunting Not stunted 1 1 1 1 1 Stunted 1.42 (0.50-4.02) 0.88 (0.52-1.51) - 0.67 (0.31-1.43) 1.81 (0.87-3.73) Mid Upper Arm Circumference Normal 1 1 1 1 1 Malnourished 1.64 (0.60-4.44) 0.74 (0.40-1.36) - 0.43 (0.18-0.98) 0.82 (0.29-2.39) 4.05 (2.07-7.93) 1.81 (0.79-4.13) Muscle mass Normal 1 1 1 1 1 Abnormal 1.10 (0.41-2.98) 1.28 (0.76-2.18) 3.89 (0.64-23.66) 1.44 (0.84-2.48) 0.96 (0.45-2.05) Proteinuria Negative 1 1 1 1 1 Positive 3.40 (1.7-6.78) 3.71 (1.75-7.88) 1.44 (0.96-2.15) 1.22 (0.11-8.69) 1.49 (0.98-2.27) 1.12 (0.64-1.95) Albumin creatinine ratio 30 1.74 (0.69-4.4) 0.76 (0.43-1.34) 1.67 (0.19-14.6) 0.89 (0.47-1.71) On Tenofovir based regimen No 1 1 1 1 1 Yes 1.45 (0.62-3.41) 0.97 (0.64-1.46) 1.72 (0.19-14.88) 3.22 (1.85-5.61) 1.87 (0.94-3.73) 0.63 (0.36-1.08) Duration on ART in years < 5 1 1 1 1 1 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 27 6 to 10 0.49 (0.17-1.43) 0.79 (0.46-1.39) 0.75 (-,-) 0.92 (0.49-1.71) 0.78 (0.37-1.61) >10 1.11 (0.43-2.89) 1.12 (0.64-1.98) 1.27 (-,-) 1.31 (0.71-2.42) 0.62 (0.11-0.39) . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint 28 . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint . CC-BY-NC 4.0 International licenseIt is made available under a is the author/funder, who has granted medRxiv a license to display the preprint in perpetuity. (which was not certified by peer review) The copyright holder for this preprintthis version posted September 3, 2024. ; https://doi.org/10.1101/2024.09.02.24312932doi: medRxiv preprint