Chronic kidney disease (CKD) is defined by either reduced glomerular filtration rate (GFR) or by the presence of proteinuria. CKD has become an important comorbidity among human immunodeficiency virus (HIV)-infected persons.1 As the survival with HIV infection lengthens, the prevalence of CKD is projected to increase steadily.2 Proteinuria is often the earliest manifestation of CKD and is far more prevalent in HIV-infected persons than in similarly aged HIV-negative controls.3 In addition, among HIV-infected persons, proteinuria is strongly associated with death, cardiovascular disease (CVD), and end-stage renal disease (ESRD).4–7 Previous cross-sectional studies have found that proteinuria is more prevalent among HIV-infected patients who are black8,9 and have depressed CD4 lymphocyte count.10 However, few if any studies have evaluated the risk factors of incident proteinuria in HIV-infected patients. To the best of our knowledge, studies have neither examined the risk factors for proteinuria stratified by race nor compared risk factors for mild versus severe proteinuria among HIV-infected patients. In our prior work,11 we have found that the exposure to tenofovir, a first-line treatment of HIV infection, was associated with increased risk of kidney disease events. In this article, our focus is on the associations of race and other risk factors for incident proteinuria in the HIV-infected patients. The purpose of our study was, therefore, to assess the clinical and demographic factors associated with the development of proteinuria in a prospective cohort of HIV-infected veterans. We hypothesized that both HIV-related and traditional CKD risk factors would contribute to proteinuria risk, and that the magnitude of risk factors would differ between black and white patients.
We conducted a retrospective cohort study of HIV-infected veterans in the Department of Veterans' Affairs (VA) HIV Clinical Case Registry (CCR) between 1997 and 2011. We studied the association between risk factors and development of incident proteinuria in this national sample of HIV-infected US veterans. Geographically, the Veterans Health Administration (VHA) is national in scope and offers low-cost comprehensive clinical services to US veterans.12 The VA HIV CCR actively monitors all HIV-infected persons receiving care in the VA nationally, and automatically extracts demographic, clinical, laboratory, pharmacy, utilization, and death information from the VA electronic medical record to a centralized database.13
We identified 65,675 HIV-infected persons receiving ambulatory care in the VA since 1984. Among these individuals, 30,632 patients initiated antiretroviral (ARV) therapy in the modern era of combination ARV therapy (after 1997). Inclusion criteria for patients for this study were HIV-infected veterans who were treatment-naive (ie, no prior exposure to any ARV) at the time they entered clinical care in the VHA system, and who subsequently received mono or combined ARV after 1997 with regular care and laboratory monitoring. We included patients with defined race of black or white excluding those of other races or missing race. We excluded patients with prevalent kidney failure (receipt of chronic dialysis treatment or kidney transplant), and those who did not have at least 1 outpatient visit and at least 1 follow-up proteinuria assessment. We also excluded those with proteinuria present at baseline, leaving 21,129 patients in the analytic cohort. Baseline was defined as the date of starting antiretroviral therapy, and they were followed until the first occurrence of proteinuria or death.
The primary outcome was the time from baseline to the time of the first occurrence of proteinuria, defined as 2 consecutive urinalyses demonstrating a dipstick reading of 1+ (30 mg/dL) or higher. As a second outcome, we defined “severe proteinuria” as 2 consecutive dipstick measures of 2+ (100 mg/dL) or higher. For both outcomes, the event was deemed to have occurred at the time of the second of the 2 consecutively positive urinalyses.
Predictors and Covariates
Predictor variables were factors hypothesized to be associated with proteinuria in HIV-infected patients. Demographic predictors included age, sex, and race, and traditional risk factors included diabetes, hypertension, CVD, dyslipidemia, and estimated GFR (eGFR). The HIV-related characteristics included illicit drug use, CD4 lymphocyte count, HIV RNA level, and hepatitis B and hepatitis C coinfection. Additional candidate predictors included body mass index (BMI), low-density lipoprotein, high-density lipoprotein, total cholesterol, and serum glucose. Age was categorized as <30, 30–40, 41–50, 51–60, and >60 years. BMI was categorized as <20, 20–25, 26–30, and >30 kg/m2. Absolute CD4 lymphocyte count was categorized as ≤200 cells per cubic millimeter and >200 cells per cubic millimeter. Plasma HIV RNA level was categorized as ≤400 copies per milliliter, 401–10,000 copies per milliliter, 10,001–100,000 copies per milliliter, and >100,000 copies per milliliter. Chronic hepatitis B was defined as a positive surface antigen test (HBsAg), and chronic hepatitis C was defined as a positive antibody test.
Demographic characteristics were obtained from the VA or Medicare health plan databases.14 Diabetes, hypertension, CVD, smoking, and HIV-related characteristics were ascertained by validated algorithms using a combination of ambulatory diagnoses, physician problem lists, hospitalization discharge diagnoses, procedures, laboratory results, and medication prescriptions.15–19 Tobacco use was defined by inpatient or outpatient diagnostic codes; questions regarding tobacco use are mandatory in VA clinical care. eGFR was calculated using the 4-variable Modification of Diet in Renal Disease (MDRD) Study equation based on age, gender, race, and serum creatinine level20; the MDRD Study equation remains in clinical use in the VA laboratory reporting system. Baseline eGFR was defined as the average of the first 2 consecutive eGFR measurements after starting ARV therapy separated by at least 3 months. Estimated GFR levels above 120 mL/min/1.73 m2 were capped at this level, as higher estimates are unlikely to be accurate or precise.21 At any given time, the most recent previous measurement was used to define time-dependent covariates.
Baseline characteristics of the black and white HIV-infected veterans were compared using χ2 tests for categorical variables and Wilcoxon rank-sum tests for continuous variables. Poisson regression models were used to calculate the unadjusted rates of incident proteinuria (per 1000 person-years), stratified for age and race, and rates adjusted for gender, BMI, diabetes, hypertension, dyslipidemia, CVD, smoking, eGFR, illicit drug use, lower CD4 lymphocyte count, higher HIV viral load, and coinfection with hepatitis B and hepatitis C. We investigated the combined effect of risk factors associated with the development of proteinuria in subjects with multiple-record data using the Fine–Gray competing risk analysis.22 In our cohort, failure could occur due to the onset of proteinuria (failure of interest), or death. To account for the potential bias due to the competing risk of death before onset of proteinuria, we performed the Fine–Gray competing risk analysis, which extends the Cox proportional hazards model to competing risk data by simultaneously evaluating hazards for the primary (proteinuria) and competing (death) events. Assumptions of proportional hazards were examined by computing the Schoenfeld residuals.22,23 We also stratified our analysis by year of diagnosis to determine whether the relative contributions of traditional CKD risk factors and HIV-related factors to proteinuria risk changed over time. We conducted a supplemental analysis (competing robustness of the primary results). Tests for interaction were performed using cross-product terms between race and time-dependent characteristics of interest in the model. Because of the observed differences in the association of age and race with proteinuria, analyses were also stratified by black and white race.
We also investigated whether differences in durable viral suppression between blacks and whites partially underlay the differences in proteinuria risk. To evaluate this, we ran our competing risk model initially adjusting for the demographic characteristics and then controlled for all the potential confounders and the viral load. The viral load was controlled in a time-updated fashion, so this would account for changes over time in the viral suppression status.
Because the frequency of obtaining urine dipsticks may be different in black and white patients, we adjusted our model for the number of times the patient was assessed for proteinuria.
Analyses were conducted using STATA, version 11 (StataCorp, College Station, TX) and SAS 9.3 (SAS Institute Inc., Cary, NC).
Among 21,129 included HIV-infected veterans, median age was 47 years, 97.4% were men, and 52.7% were black. In general, black patients were less likely to have dyslipidemia and more likely to have hepatitis C virus (HCV), had lower CD4 lymphocyte count, and higher HIV RNA levels (Table 1).
A total of 7031 proteinuria outcomes were observed during the study follow-up (median duration = 5.3 years, interquartile range = 2.3–9.2). The median time between 2 proteinuria measurements was 5 months (interquartile range = 3–13).
As shown in Figure 1, unadjusted association of age with rate of incident proteinuria per 1000 person years differed by race, with a U-shaped association of proteinuria and age in blacks, and a nearly monotonic association in whites. Although blacks appeared to have higher rates of proteinuria within each age category relative to whites, the race difference was greatest among patients younger than 30 years and gradually diminished with increasing age. Furthermore, the rates were not significantly different at ages older than 60 years. This finding persisted after multivariate adjustment, and the age-specific rates of incident proteinuria per 1000 person-years for both blacks and whites are shown in Table 2. The rate ratio for proteinuria in the age group younger than 30 years was 1.96 [95% confidence interval (CI): 1.67 to 2.30], indicating that blacks were approximately 2 times more likely to have proteinuria than whites in our cohort.
After multivariable adjustment in the competing risk model, low BMI <20 kg/m2, diabetes, hypertension, dyslipidemia, CVD, and low eGFR before the development of proteinuria were all associated with a greater risk of proteinuria (Table 3). HIV-related risk factors were also associated with proteinuria risk: plasma HIV RNA levels >100,000 copies per milliliter, CD4 lymphocyte count ≤200 cells per cubic millimeter, hepatitis C, and hepatitis B virus. We did not observe significant interactions between race and the other covariates (P interaction >0.05 in fully adjusted models) except for the interaction between age and race for the risk of proteinuria (P < 0.001) and eGFR and race (P = 0.0012) in our multivariable analysis. Although higher eGFR was associated with a lower risk of proteinuria in both blacks and whites, the association was somewhat stronger in whites [hazard ratio (HR) (95% CI) = 0.91 (0.89 to 0.94) vs. HR (95% CI) = 0.95 (0.93 to 0.96)].
In race-stratified analysis, the hazard ratios associated with the risk factors were similar in blacks and whites. Table 4 shows the further exploration of the race differences for risk of proteinuria using age-stratified multivariable analysis. The results showed a 2-fold for blacks versus whites among participants younger than 30 years. With increasing age, the risk associated with race difference lost its significance. Given the nonlinear association with age, we also ran our multivariable competing risk model for time to proteinuria with a linear and a quadratic term for age rather than the age categories as shown in Table 3. For estimating the risk of proteinuria, the adjusted HR for black versus white was 1.38 (95% CI: 1.31 to 1.45).
Additional analyses stratified by the year of HIV diagnosis showed a lower incidence among those diagnosed in more recent years. However, risk factor associations with proteinuria were generally consistent across the 4 time periods (see Table S2, Supplemental Digital Content, http://links.lww.com/QAI/A551). Black race was consistently associated with an elevated risk of proteinuria across years of follow-up relative to whites; the hazard ratio for blacks relative to whites was 1.46 (95% CI: 1.33 to 1.60) among persons diagnosed before 1997, 1.60 (1.45 to 1.75) for diagnosis between 1997 and 1999, 1.55 (1.40 to 1.71) for diagnosis between 2000 and 2003, and 1.44 (1.28 to 1.62) for diagnosis after 2003.
On evaluating whether differences in durable viral suppression between blacks and whites partially underlay the differences in proteinuria risk, we found that the race effect was significant regardless of the effect of durable viral suppression both in simple demographic-adjusted analysis [1.39 (1.33 to 1.46)] and in adjusted models excluding viral load [1.50 (1.43 to 1.58)]. Rather the race effect strengthened after adjusting the model for viral load [1.51 (1.43 to 1.59)].
We were concerned that race might influence ascertainment of urine protein, so we adjusted for number of times the patient was assessed for proteinuria. The association of black race with proteinuria risk remained significantly stronger in this adjusted model [HR (95% CI): 1.50 (1.43 to 1.59)].
Of the 21,129 HIV-infected individuals in the cohort who had urine analyses documented, 1390 developed severe proteinuria (Table 5). Severe proteinuria was defined as 2 consecutive dipstick measures of 2+ (100 mg/dL) or higher. After adjustment for confounders, individuals of black race had a 2-fold risk of severe proteinuria compared with white individuals. In this analysis, the interaction of race and age was less striking (P = 0.002). The model indicated that as age increased by a decade, the risk of severe proteinuria observed for the race difference decreased by 19%. Among the traditional risk factors for kidney disease, hypertension, diabetes, CVD, and lower eGFR were each associated with higher risk of severe proteinuria. Multivariable-adjusted associations of the HIV disease risk factors such as low CD4 lymphocyte count, high viral load, hepatitis C, and hepatitis B coinfections with severe proteinuria were also stronger.
In the stratified analysis, risk factors had similar associations among blacks and whites. HIV RNA level had a somewhat stronger association in blacks than in whites (P for interaction = 0.08).
Proteinuria is part of the definition of CKD and is a risk marker for progression to ESRD.24 Previous literature found that higher levels of proteinuria are independently associated with risk of ESRD at all levels of eGFR.25 Our study examined the risk factors for proteinuria among a large cohort of HIV-infected veterans. Black race has been found to be a strong risk factor for advanced HIV-associated nephropathy,5,10 but little data are available on the risk of developing proteinuria in HIV-infected individuals. In addition, fewer studies have been conducted in the era of highly effective ARV therapy in large number of patients. One such study is our previous work on the association of tenofovir, a first-line treatment of HIV infection that is currently used in half of all the antiretroviral regimens, with proteinuria.11 To our knowledge, our study is the largest cohort of HIV-infected veterans used to date to investigate the risk factors for the development of proteinuria.
Our study demonstrates a significant effect of race on the incidence of proteinuria and severe proteinuria. Furthermore, we found that the higher risk of incident proteinuria in blacks was particularly evident in younger age groups. In our cohort, the younger blacks compared with the younger whites were not under control for hypertension and diabetes (see Table S1, Supplemental Digital Content, http://links.lww.com/QAI/A551). Another potential reason could be that risks in younger blacks are driven by early susceptibility due to genetic polymorphic difference [ie, interaction of apolipoprotein L1 (APOL1) genotype] that may contribute to the increasing risk of proteinuria.26,27 Several studies have demonstrated significant disparities in highly active antiretroviral therapy (HAART) utilization according to race. HIV-infected blacks present for care in more advanced stages of disease28 and are less likely to receive HAART than are HIV-infected whites, even among patients in care.29 The differences in proteinuria risk across races could be further attributed to the differences in durable viral suppression between blacks and whites as demonstrated in our study. Because black race is a strong risk factor for HIV-associated renal disease, as has previously been documented,7,30 and young black men are disproportionately affected,31 the stronger association of black race with proteinuria in the younger groups is not surprising. Nevertheless, these striking racial differences with age in the development of proteinuria among patients with HIV highlight the critical need for studies devoted to the understanding of underlying disease mechanisms for HIV-related kidney disease, particularly among blacks.
Previous studies investigating predictive factors of CKD have identified hypertension and diabetes to be independently related to CKD.32,33 It is noteworthy that in the competing risk framework, the key established kidney and cardiovascular risk factors of kidney dysfunction were associated with the risk of incident proteinuria, including dyslipidemia and CVD along with diabetes and hypertension. Interestingly, in our study, these traditional risk factors exhibited a stronger association with severe proteinuria.
Our study also demonstrated that several HIV-related risk factors including elevated HIV RNA level, absolute CD4 lymphocyte count, hepatitis C, and hepatitis B coinfection are associated with proteinuria, and their association is much stronger with severe proteinuria. Our finding of higher HIV RNA levels and lower CD4 lymphocyte counts predictive of proteinuria in multivariable analysis was consistent with the findings from the Women's Interagency HIV Study.10 The significance of HIV RNA level and CD4 lymphocyte count in this analysis supports the hypothesis that HIV-related renal diseases34,35 represent a direct infection of the virus within the kidney and viral suppression caused by HAART likely results in improvement or stabilization of renal function.21 In this cohort, a positive test for the hepatitis C antibody was also an independent predictor of proteinuria.
Our study is unique as it is a large national registry investigating incident proteinuria with the relatively uniform health care system available to US veterans and the reliable data source for both the predictor variables and the outcome of proteinuria. Due to the large size, we have substantial power in our cohort to compare risk factors among the black and white veterans. Prior studies that have identified risk factors of proteinuria in HIV infection were cross-sectional and therefore causality cannot be inferred. Our database includes 21,129 HIV-infected veterans who met the inclusion criteria and were followed for a median duration of 5.3 years. This represents the largest study to evaluate incident proteinuria with longitudinal data on urine protein excretion in black and white race.
Despite the strengths mentioned of this study, there are certain limitations. First, this study is predominantly in male veterans receiving care in the Department of VA Health Care System, so results may not be generalizable to women, nonveterans, or racial and ethnic groups other than blacks and whites. Second, assessment of proteinuria was at discretion of clinicians and not part of a protocol. Third, we did not study any specific glomerular or tubular markers of injury due to sustained proteinuria. Fourth, we cannot determine the role of APOL1 genotype as a determinant of risk for proteinuria in the HIV-infected blacks. Previous studies, however, have demonstrated an 8%–13% prevalence of the APOL1 genotype in HIV-infected blacks.26,27 Fifth, we excluded patients with missing race information and those who reported being American Indians/Native Alaskan, Pacific Islander/Native Hawaiian, or Asian (19%) from our cohort. Sixth, we did not have HCV RNA data to confirm chronic HCV infection, and it is likely that hepatitis C resolved in some patients.
In summary, we found remarkably strong associations between black race and incident proteinuria that were strongest among younger HIV-infected individuals and for the outcome of severe proteinuria. These differences raise the need to understand the alarmingly high risk of proteinuria in blacks. Furthermore, clinicians should recognize that both the traditional and HIV-related risk factors are important contributors to the onset of proteinuria. The potential impact of these results includes the possibility of improving intervention and prevention/control and delay the onset of proteinuria.
The Centers for Disease Control and Prevention (CDC) CKD Surveillance Team consists of members groups led by the University of California, San Francisco [Neil Powe (PI), Michael Shlipak, Tanushree Banerjee, Rebecca Scherzer, Chi-yuan Hsu, Kirsten Bibbins-Domingo, Charles McCulloch, Deidra Crews, Vanessa Grubbs, Delphine Tuot], University of Michigan [Rajiv Saran (PI), Diane Steffick, Brenda Gillespie, William Herman, Friedrich Port, Bruce Robinson, Vahakn Shahinian, Jerry Yee, Eric Young, William McClellan, Ann O'Hare, Anca Tilea, and Melissa Fava], and CDC [Desmond Williams (Technical Advisor), Nilka Ríos Burrows, Mark Eberhardt, Nicole Flowers, Linda Geiss, Regina Jordan, Juanita Mondeshire, Bernice Moore, Gary Myers, Meda Pavkov, Deborah Rolka, Sharon Saydah, Anton Schoolwerth, Rodolfo Valdez, and Larry Waller].
1. Gupta SK, Eustace JA, Winston JA, et al.. Guidelines for the management of chronic kidney disease in HIV
-infected patients: recommendations of the HIV
Medicine Association of the Infectious Diseases Society of America. Clin Infect Dis. 2005;40:1559–1585.
2. Schwartz EJ, Szczech LA, Ross MJ, et al.. Highly active antiretroviral therapy and the epidemic of HIV
+ end-stage renal disease. J Am Soc Nephrol. 2005;16:2412–2420.
3. Gardner L, Holmberg SD, Williamson JM, et al.; HIV
Epidemiology Research Study Group. Development of proteinuria
or elevated serum creatinine and mortality in HIV
-infected women. J Acquir Immune Defic Syndr. 2003;32:203–209.
4. Gupta SK, Mamlin BW, Johnson CS, et al.. Prevalence of proteinuria
and the development of chronic kidney disease in HIV
-infected patients. Clin Nephrol. 2004;61:1–6.
5. Szczech LA. Renal diseases associated with human immunodeficiency virus infection: epidemiology, clinical course and management. Clin Infect Dis. 2001;33:115–119.
6. Culleton BF, Larson MG, Parfrey PS, et al.. Proteinuria
as a risk factor for cardiovascular disease and mortality in older population: a prospective study. Am J Med. 2000;109:1–8.
7. Jotwani V, Li Y, Grunfeld C, et al.. Risk factors for ESRD in HIV
-infected individuals: traditional and HIV
-related factors. Am J Kidney Dis. 2012;59:628–635.
8. Szczech LA, Grunfeld C, Scherzer R, et al.. Microalbuminuria in HIV
infection. AIDS. 2007;21:1003–1009.
9. Lucas GM, Lau B, Atta MG, et al.. Chronic kidney disease incidence, and progression to end-stage renal disease, in HIV
-infected individuals: a tale of two races. J Infect Dis. 2008;197:1548–1557.
10. Szczech LA, Gange SJ, van der Horst C, et al.. Predictors of proteinuria
and renal failure among women with HIV
infection. Kidney Int. 2002;61:195–202.
11. Scherzer R, Estrella M, Li Y, et al.. Association of tenofovir exposure with kidney disease risk in HIV
infection. AIDS. 2012;26:867–875.
12. Ashton CM, Souchek J, Petersen NJ, et al.. Hospital use and survival among Veterans Affairs beneficiaries. N Engl J Med. 2003;349:1637–1646.
13. Backus LI, Gavrilov S, Loomis TP, et al.. Clinical Case Registries: simultaneous local and national disease registries for population quality management. J Am Med Inform Assoc. 2009;16:775–783.
14. Sohn MW, Zhang H, Arnold N, et al.. Transition to the new race
/ethnicity data collection standards in the Department of Veterans Affairs. Popul Health Metr. 2006;4:7.
15. Go AS, Chertow GM, Fan D, et al.. Chronic kidney disease and the risks of death, cardiovascular events, and hospitalization. N Engl J Med. 2004;351:1296–1305.
16. Miller DR, Safford MM, Pogach LM. Who has diabetes? Best estimates of diabetes prevalence in the Department of Veterans Affairs based on computerized patient data. Diabetes Care. 2004;27(suppl 2):B10–B21.
17. Goulet JL, Fultz SL, McGinnis KA, et al.. Relative prevalence of comorbidities and treatment contraindications in HIV
-mono-infected and HIV
/HCV-co-infected veterans. AIDS. 2005;19(suppl 3):S99–S105.
18. Strader DB, Wright T, Thomas DL, et al.. Diagnosis, management, and treatment of hepatitis C. Hepatology. 2004;39:1147–1171.
19. Justice AC, Lasky E, McGinnis KA, et al.; VACS 3 Project Team. Medical disease and alcohol use among veterans with human immunodeficiency infection: a comparison of disease measurement strategies. Med Care. 2006;44(suppl 2):S52–S60.
20. Levey AS, Coresh J, Balk E, et al.; National Kidney Foundation. National Kidney Foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Ann Intern Med. 2003;139:137–147.
21. Longenecker CT, Scherzer R, Bacchetti P, et al.. HIV
viremia and changes in kidney function. AIDS. 2009;23:1089–1096.
22. Fine JP, Gray RJ. A proportional hazards model for the subdistribution of a competing risk. J Am Stat Assoc. 1999;94:496–509.
23. Klein J, Moeschberger M. Survival Analysis, in Techniques for Censored and Truncated Data. New York: Springer; 1997.
24. Lea J, Greene T, Hebert L, et al.; African American Study of Kidney Disease and Hypertension Study Group. The relationship between magnitude of proteinuria
reduction and risk of end-stage renal disease: results of the African American Study of kidney disease and hypertension. Arch Intern Med. 2005;165:947–953.
25. Hemmelgarn BR, Manns BJ, Lloyd A, et al.. Relation between kidney function, proteinuria
, and adverse outcomes. JAMA. 2010;303:423–439.
26. Genovese G, Friedman DJ, Ross MD, et al.. Association of trypanolytic ApoL1 variants with kidney disease in African Americans. Science. 2010;329:841–845.
27. Estrella MM, Wyatt CM, Pearce CL, et al.. Host APOL1 genotype is independently associated with proteinuria
infection. Kidney Int. 2013;84:834–840.
28. Keruly JC, Moore RD. Immune status at presentation to care did not improve among antiretroviral-naive persons from 1990 to 2006. Clin Infect Dis. 2007;45:1369–1374.
29. Gebo KA, Fleishman JA, Conviser R, et al.. Racial and gender disparities in receipt of highly active antiretroviral therapy persist in a multistate sample of HIV
patients in 2001. J Acquir Immune Defic Syndr. 2005;38:96–103.
30. Choi AI, Rodriguez RA, Bacchetti P, et al.. The impact of HIV
on chronic kidney disease outcomes. Kidney Int. 2007;72:1380–1387.
32. Flandre P, Pugliese P, Cuzin L, et al.; New AIDS Data Group. Risk factors of chronic kidney disease in HIV
-infected patients. Clin J Am Soc Nephrol. 2011;6:1700–1707.
33. Dalrymple LS, Katz R, Kestenbaum B, et al.. Chronic kidney disease and the risk of end-stage renal disease versus death. J Gen Intern Med. 2011;26:379–385.
34. Szczech LA, Hoover DA, Feldman JG, et al.. Association between renal disease and outcomes among HIV
-infected women receiving or not receiving antiretroviral therapy. Clin Infect Dis. 2004;39:1199–1206.
35. Rhee MS, Schmid CH, Stevens LA, et al.. Risk factors for proteinuria
-infected and –uninfected Hispanic drug users. Am J Kidney Dis. 2008;52:683–690.
HIV; proteinuria; race
Supplemental Digital Content
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