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Logo of nihpaAbout Author manuscriptsSubmit a manuscriptHHS Public Access; Author Manuscript; Accepted for publication in peer reviewed journal;
 
J Acquir Immune Defic Syndr. Author manuscript; available in PMC 2013 December 1.
Published in final edited form as:
PMCID: PMC3494783
NIHMSID: NIHMS405319

Prevalence of Proteinuria and Elevated Serum Cystatin C among HIV-infected Adolescents in the Reaching for Excellence in Adolescent Care and Health (REACH) Study

Abstract

Objective

In the United States (US), kidney dysfunction is prevalent in almost 30% of HIV-infected patients and is an independent predictor of mortality. Proteinuria and elevated serum cystatin C (eCysC) are used as markers of kidney disease in the general population; however, the prevalence of these markers in HIV-infected adolescents is largely unknown.

Methods

This study includes 304 HIV-infected adolescents from the Reaching for Excellence in Adolescent Care and Health (REACH) cohort, an observational study of adolescents recruited from 13 US cities. Clinical and demographic characteristics of participants were evaluated as correlates of proteinuria, a urine protein to creatinine ratio (UP/Cr) of ≥200 mg/g. Select univariate predictors were assessed to determine the association with urinary protein excretion and serum cystatin C in multivariable linear regression models and proteinuria and elevated serum cystatin C (eCysC ≥ 75th percentile) in multivariable logistic regression models.

Results

Overall, 19.1% of the participants had proteinuria while 23.7% had an eCysC. Low CD4+ T-lymphocyte counts (<200 cells/mm3) were significantly associated with a greater UP/Cr in linear models and with proteinuria in logistic regression models. CD4+ T-lymphocyte counts <500 cells/mm3 were significantly associated with a greater serum cystatin C concentration in linear models and with eCysC in logistic regression models.

Conclusion

Proteinuria among HIV-infected adolescents in REACH was approximately two-fold greater than healthy US adolescents. Both proteinuria and eCysC are associated with CD4+ T-lymphocyte counts. Further studies investigating early markers of kidney disease and the association with immune status and inflammation in adolescents are needed.

Keywords: HIV, adolescent, kidney, CD4+ T-cells, proteinuria, serum cystatin C

Introduction

Combination antiretroviral therapy (cART) has significantly improved the longevity and disease care management of HIV-infected individuals over the last decade.1,2 However, age-related complications, including chronic kidney disease (CKD) tend to occur more frequently and at an earlier age among HIV-infected patients compared to the general public. Kidney function is abnormal in up to 30% of HIV-infected patients3, while as many as 10% of HIV-infected patients suffer from CKD which may not be symptomatic until late into the disease progression.4 Two large cohorts in the United States—the HIV Epidemiology Research Study (HERS) and the Women’s Interagency HIV Study (WIHS)—demonstrated a 2 to 2.5-fold risk of death among HIV-infected women with proteinuria or a serum creatinine ≥ 1.4 mg/dL.5,6 HIV care guidelines recommend regular assessment of kidney function. 3

Individuals with CD4+ T-lymphocyte cell (CD4+ T-cell) counts less than 200 cells/mm3 are at high risk for HIV-1-related morbidity and mortality, including kidney disease. Prior to the advent of cART, CKD was largely a result of HIV-associated nephropathy (HIVAN), a disease manifestation associated with black race, high viral load (VL), and a low CD4+ T-cell count.7 In the past decade, widespread use of cART has reduced the incidence of HIVAN;8 however, other renal pathologies have emerged.9 While cART is used to improve the overall health status of HIV-infected individuals, including reduction in kidney disease progression, it has also been associated with pathological kidney manifestations10,11 and nephrotoxicity.9,11,12 Drug metabolism and excretion are a major function of the kidney; thus, cART agents alone or in combination with other medications may result in kidney impairment leading to end-stage renal disease (ESRD).10,12 While the nephrotoxic effects of specific combinations of cART are uncertain, examining kidney dysfunction markers in HIV-infected adolescents, with or without cART, could provide valuable insight.

Proteinuria has been used as a surrogate marker of CKD13 and is defined as a spot urine protein to urine creatinine ratio of ≥200 mg/g. The prevalence of proteinuria in adults in the general population in the US ranges from 6–10%,14,15 while various studies in the US and abroad have demonstrated a higher prevalence of proteinuria in HIV-infected adults ranging from 17–45%16,17 and 21–33% in children.18,19 Likewise, due to the significant limitations of serum creatinine-based glomerular filtration rate (GFR) estimation in individuals with HIV, serum cystatin C has emerged as a marker for both the evaluation of GFR and the detection of drug-induced kidney injury.20 Independent of GFR, serum cystatin C concentration is associated with C-reactive protein, HIV VL and CD4+ T-cell count.2123 However, studies evaluating the accuracy of serum cystatin C for estimating GFR among HIV-infected individuals are limited and thus the use of serum cystatin C alone or as a component in GFR estimation in the HIV-infected population remains uncertain.20

Studies have shown that HIV-associated nephropathy (HIVAN) is a common cause of CKD in HIV-infected adults and children.24,25 To date, most studies of kidney disease in HIV-infected patients have been conducted in adults and studies of kidney disease markers in HIV-infected adolescents are lacking. One recent study has found that reduction of the HIV VL by antiretroviral therapy (ART) may prevent progression of proteinuria and improve the clinical outcome of HIV-infected youth.18 Our study explored the association of clinical and demographic factors with proteinuria and serum cystatin C among HIV-infected adolescents.

Methods

Study Population Characteristics

This study involves HIV-infected adolescents, who participated in the Reaching for Excellence in Adolescent Care and Health (REACH) cohort. In brief, the REACH study is an observational study that included 352 adolescents (13 to 19 years old) who acquired HIV-1 through risk behaviors, mainly sexual activities (perinatal transmission or blood product contamination were excluded), recruited from 15 clinical sites in 13 US cities from 1995–2001.26,27 Urine and serum samples were collected at all visits and stored at −80 °C; however, in this cross-sectional analysis we only included the serum and urine sample from a single visit. Due to pregnancy at baseline or sample depletion, we obtained serum and urine specimens from the earliest visit available that met the inclusion criteria. Participant data for HIV and other health-related clinical evaluations, including documentation of demographics, risk behaviors, medical history, and immunological outcomes were extracted from the REACH database and sorted and matched by participant identifier and visit number. Four men seroconverted during the study follow-up and biological specimens were unavailable from 44 individuals, leading to exclusion from this analysis. Overall, samples from 304 REACH participants, obtained during non-pregnant visits, were included in the current analysis. Body mass index (BMI) was calculated using weight and height measurements and values were characterized into standard weight status categories.27 At the time of the study visit, cART was defined as a combination of two nucleoside reverse transcriptase inhibitors (NRTIs) and either a protease inhibitor (PI) or a non-nucleoside reverse transcriptase inhibitor (NNRTI). This study was approved by the University of Alabama at Birmingham Institutional Review Board.

Immunomarkers and HIV-Specific Testing

Viral load was measured in a centralized laboratory using either nucleic acid sequence-based amplification (NASBA, lower limit = 400 copies/mL) or NucliSens assays (Organon Teknika, Durham, NC, lower limit = 80 copies/mL). Quantitative immunophenotyping of CD4+ and CD8+ T-lymphocyte counts was determined at the individual clinical sites in certified laboratories using AIDS Clinical Trials Group (ACTG) standardized flow cytometry protocols.28,29 Samples for quantitative immunophenotyping of CD8+CD38+ T-cells were analyzed centrally every 6 months at the Immunology Core Laboratory at The Children’s Hospital of Philadelphia after overnight shipping as previously reported. 29 The clinical status of participants at baseline was determined using the absolute CD4+ T-cell count categorized as follows—0–200 cells/mm3 (low), 200–499 cells/mm3 (medium), and ≥ 500 cells/mm3 (high).

Kidney Markers and Estimation of Kidney Function

Serum and urine creatinine were analyzed enzymatically on previously frozen samples using an in vitro clinical diagnostic integrated system, the Siemens Dimension Vista 1500 (Siemens Healthcare Diagnostics Inc., Deerfield, IL), at the University of Maryland (Baltimore, MD) in conjunction with National Institute of Standards and Technology’s (NIST) Standard Reference Material (SRM) 967 traceable to isotope dilution mass spectrometry analysis.30,31 Additional testing included urine protein and serum cystatin C which were measured using automated nephelometric assay methodology on the same system (Siemens Healthcare Diagnostics Inc., Deerfield, IL). The spot urine protein and creatinine were used to calculate a ratio, in milligrams of protein to grams of creatinine, as an estimation of 24-hr urinary protein excretion (UP/Cr). A ratio of ≥200 mg/g was defined as abnormal urinary protein excretion or proteinuria, as recommended by the Kidney Disease Outcomes Quality Initiative of the National Kidney Foundation (KDOQI/NKF).32

Statistical Analysis

For the participants’ visit, demographic and clinical parameters were characterized for participants with and without proteinuria. Correlative analysis of each kidney marker—UP/Cr in mg/g, serum creatinine in mg/dL and serum cystatin C in mg/L—was performed. Regression model outcomes included log-transformed UP/Cr ratio and serum cystatin C for linear regression models; while proteinuria, a UP/Cr ≥200 mg/g, and elevated serum cystatin C (eCysC), ≥0.783 mg/L – corresponding to the 75th percentile cutoff, were the outcomes for logistic regression models. The 75th percentile age-adjusted CysC was not significantly different from the unadjusted values. Both linear and logistic regression models included CD4+ T-cell count as the primary predictor (categories low, medium, and high) and adjusted for a priori-selected covariates chosen based on previous literature and those found to be statistically significant at (p<0.10) in univariate analyses. Additionally, independent variables exhibiting collinearity with CD4+ T-cell count, the main predictor of interest, were excluded. Three models were evaluated for each outcome. The first model was adjusted for age, gender, and race/ethnicity. The second model consisted of variables included in the first model in addition to BMI category. Lastly, model 3 included model 2 covariates while adjusting for cART use. Final adjusted and unadjusted models were also performed (data shown in supplementery tables 1 and 2) All statistical analyses were performed using SAS version 9.2 (SAS Institute Inc, Cary, North Carolina).

Results

Of the 304 participants included in this study, the mean age was 18 ± 1 year and 75% of participants were non-Hispanic black females. Participants were predominantly normal weight according to BMI (45%) and more than half of the cohort reported that they had (ever) smoked cigarettes (67%) and drank alcohol (58%). There were no significant differences for proteinuria status by gender, smoking status, alcohol use, cART status, viral load, absolute CD8+ or CD8+CD38 + T-cell counts, or serum creatinine. There were significant differences (p<0.10) for proteinuria status by age, race/ethnicity, BMI category, CD4+ T-cell count, and serum cystatin C (Table 1).

Table 1
Demographic and clinical characteristics of HIV-infected participants with and without proteinuria

Correlative analysis of UP/Cr in mg/g with serum creatinine in mg/dL yielded a Pearson correlation (r) (95% CI) of 0.22 (0.11–0.33). However, the correlation was much higher among those with low CD4+ T-cell counts, r = 0.77(0.51–0.89) and not quite significant in the medium and high CD4+ T-cell count groups. The overall correlation between serum cystatin C in mg/L and serum creatinine in mg/dL was 0.46 (0.36–0.55). There was a graded statistically significant correlation between serum cystatin C and serum creatinine with descending CD4+ T-cell count category, r = 0.79 (0.55–0.90), 0.44 (0.15–0.65), and 0.31 (0.18–0.42), respectively. The overall Pearson correlation between serum cystatin C and UP/Cr was 0.43 (0.33–0.52); however, the correlation was higher among individuals with low CD4+ T-cell counts, r = 0.81 (0.58–0.91).

Proteinuria

Of the participants in this study, 19.1% had proteinuria. The geometric mean of UP/Cr was 221 mg/g, 148 mg/g, and 134 mg/g among participants with low, medium, and high CD4+ T-cell count categories, respectively (Figure 1, top panel). The prevalence of proteinuria was 42%, 19%, and 16% among the three levels of CD4+ T-cells, respectively (Figure 1, bottom panel). After adjustment for age, gender, and race/ethnicity in linear regression, the beta coefficient ± SE for low and medium CD4+ T-cell count versus high CD4+ T-cell counts were 0.53 ± 0.12 and 0.10 ± 0.09, respectively. With the addition of BMI in model 2 and HAART in model 3, the change in the beta coefficients was unremarkable (Table 2).

Figure 1
Geometric mean of UP/Cr values by CD4+ T-lymphocyte count (low, medium and high) (top panel) and Prevalence of Proteinuria for REACH Participants (bottom panel)
Table 2
Association of Urine Protein to Creatinine Ratio (mg/g) with medium (200–499 cells/mm3) and low (<200 cells/mm3) versus high (≥500 cells/mm3) CD4+ T-lymphocyte count (CD4+ T-cells). Top panel shows the Beta coefficient and standard ...

In logistic regression models, with high CD4+ T-cell count as the referent category, the OR (95% CI) for proteinuria in participants with low CD4+ T-cell counts was 3.7 (1.5–8.9) in the unadjusted model (Supplementary Table 1), 4.4 (1.6–11.6) in the first model, 3.2 (1.2–8.8) in the second model, 3.2 (1.2–8.7) in the third model (Table 2). Age and race/ethnicity were significant predictors of proteinuria in all models. Participant BMI category significantly predicted proteinuria in models 2–3, with underweight and normal weight individuals being most likely to present with proteinuria.

Serum Cystatin C

Of the participants in this study, 23.7% had an eCysC value ≥ 0.783mg/L (≥ 75th percentile). Mean values for serum cystatin C were 0.78 mg/L, 0.75 mg/L, and 0.71 mg/L among participants with low, medium, and high CD4+ T-cell counts, respectively (Figure 2, top panel). The prevalence of eCysC was 33%, 40%, and 20%, respectively in the three groups (Figure 2, bottom panel). Linear regression models for serum cystatin C demonstrated an increase in value as the category of CD4+ T-cell count decreased from high to low. After adjustment for age, gender, and race/ethnicity, the beta coefficient ± SE for low and medium CD4+ T-cell count versus high CD4+ T-cell count were 0.06 ± 0.03 and 0.05 ± 0.02, respectively (Table 3). After controlling for BMI in model 2, cART in model 3, the change in beta coefficient values was minimal (Table 3). Gender was statistically significant in all of the linear regression models (e.g., 0.78 mg/L in males versus 0.72 mg/L in females, p-value <0.001 in the overall adjusted model) (Supplementary Table 2). In logistic regression models, a CD4+ T-cell count <500 cells/mm3 was associated with an elevated serum cystatin C. The OR (95% CI) for low and medium CD4+ T-cell count was 1.9 (0. 7–4.9) and 3.5 (1.7–7.3) in model 1; 2.4 (0.84–6.6) and 3.5 (1.7–7.5) in model 2; and 2.7 (0.93–7.6) and 3.8 (1.8–8.1), respectively in the final model (Table 3).

Figure 2
Mean Serum Cystatin C Values by Tertile (low, medium, high) of CD4+ T-lymphocyte count (top panel) and Prevalence of Elevated Serum Cystatin C for REACH Participants (bottom panel)
Table 3
Association of serum cystatin C (mg/L) with medium (200–499 cells/mm3) and low (<200 cells/mm3)versushigh (≥500 cells/mm3) CD4+ T-lymphocyte count (CD4+ T-cells). Top panel shows the Beta coefficient and standard error using linear ...

Discussion

In the current study, the prevalence of proteinuria among HIV-infected adolescents who participated in the REACH cohort was 19.1%, almost two times the prevalence in healthy U.S. adolescents.33 Logistic regression analyses revealed age, race/ethnicity, BMI category, and low CD4+ T-cell count as significant predictors of proteinuria; in the linear regression with the natural log-transformed UP/Cr ratio as the dependent variable, there was an inverse relationship between both BMI category and CD4+ T-cell count category with UP/Cr. The association with risk factors such as severity of HIV-infection and nutrition status inferred by these relationships is similar to what other studies have demonstrated in different HIV-infected adult populations.34,35 Diabetes and hypertension are known cardiovascular and kidney disease risk factors associated with proteinuria in the general population and among those who are HIV-infected.36,37 In the US, the prevalence of diabetes and hypertension in adolescents is <2%; 38 consequently, although these data were not available, hypertension and diabetes are expected to be minimal among the adolescents in this cohort. Other factors such as the metabolic syndrome, exposure to multiple medications over time, or myopathic disorders related to HIV may also play a role in the development of proteinuria and subsequent kidney dysfunction.23,39

Our finding that low CD4+ T-cell count was associated with proteinuria is consistent with other US studies among various HIV-infected populations.17,18,4042 REACH participants with abnormal urinary protein excretion were more likely to be young, underweight or normal weight, and non-black individuals. However, the association of race/ethnicity in these models is most likely a result of a small number of non-black individuals and should be interpreted cautiously. In contrast to other studies conducted in the general population,43,44 the association of low BMI with proteinuria and kidney dysfunction, is more common among those with HIV-infection.34,35,45,46 In addition, body fat distributions in HIV-infected children and adolescents have demonstrated patterns associated with cardiovascular disease risk and it is possibly related to specific antiretroviral drugs.47,48 Association between low BMI and proteinuria has also been reported in at least one other study and was explained as being due to advanced renal disease.35 However, in our study, renal impairment was not advanced enough for the association to be interpreted in this way. Consequently, in our study, BMI category could potentially be a proxy for the relation of nutritional status and body fat distribution, sicker individuals, and disease progression among those with HIV-infection.

Classification of the REACH cohort by proteinuria status demonstrated a significant difference between mean serum cystatin C (p=0.01), 0.77 mg/L in those with proteinuria versus 0.71 mg/L in those with normal urinary protein excretion, respectively. The values obtained for serum creatinine and cystatin C were both slightly lower than those reported from NHANES III, including non-Hispanic blacks with values reported as 0.76 mg/dL for serum creatinine and 0.80 mg/L for serum cystatin C, respectively.49 This difference may be due to the differences in study populations as the mean age of our cohort was 18 years compared to 15 years in NHANES III. Additionally, there have been changes in calibration and sensitivity of the methods during the last 5 years;50 however, this should not result in differential misclassification.

Our final model in logistic regression analyses revealed a greater likelihood of an eCysC among participants that were obese, non-black, male gender, and had an elevated VL. In contrast to the logistic regression results for proteinuria in which a low CD4+ T-cell count (<200 cells/mm3) was found to be a strong predictor, participants with medium CD4+ T-lymphocyte counts (200–499 cells/mm3) were most likely to have an eCysC. In linear regression models with serum cystatin C as the dependent variable, least square mean comparisons demonstrated similar findings. Participants with both low and medium CD4+ T-cell counts demonstrated significantly higher serum cystatin C concentrations than those with high CD4+ T-cell counts. Serum cystatin C derived GFR estimating equations have not been validated in healthy children and adolescent populations; however they have shown greater sensitivity and accuracy in those with kidney dysfunction, particularly in those with a GFR <90mL/min/1.73 m2.51 In this study, estimated GFRs were calculated using different equations.5255 At higher GFRs, serum creatinine estimates are less precise and cystatin C provides more valid estimation.56 GFR estimates as calculated from serum creatinine and/or serum cystatin C are known to be unreliable for values >60 ml/min/1.73m2; thus, those that are calculated to be >60 ml/min/1.73m2 are generally reported as such in clinical laboratory reports. The majority of participants in the REACH cohort had an estimated glomerular filtration rate (eGFR) over 60 ml/min/1.73m2. Therefore, we selected to report serum cystatin C values rather than an eGFR calculated from serum cystatin C. Elevated serum cystatin C is associated with many of the abnormalities present in moderate to advanced CKD.56 Recent data presented by the Chronic Kidney Disease Epidemiology Collaboration (CKD-EPI) suggest that cystatin C should not replace creatinine for GFR estimation in general practice; however, it may be useful in specific cases, such as confirmation of the diagnosis of CKD in patients with a decreased GFR as estimated from creatinine and more accurate estimation of GFR in patients with muscle wasting or chronic illness.57 Studies have shown that serum cystatin C is higher in those who are HIV-infected when compared to uninfected individuals and that there is a correlation with viral load,58 as found in our analyses, and inflammatory markers.23 It is unclear if the biological associations of serum cystatin C are with HIV-infection or kidney disease. While the finding should be cautiously interpreted, it is possible that these are potential kidney disease progression indicators in HIV-infected adolescents.

Gupta et. al., reported the association of the percent of activated CD8+CD38+HLA-DR+ with proteinuria in HIV-infected adults, but not with absolute counts or other T-cell markers of immune activation.59 In our study, we did not observe any association between immune activation by way of CD8+CD38+ T-cells, viral load, and proteinuria. The extent of viral replication has been shown to be a strong determinant of kidney disease,60 along with peripheral CD4+ T-cell count.34,61 The correlations of CD4+ T-cell count and viral load with proteinuria could be high among adults. There seems to be less variation and overall lower VL among non-white females in our adolescent population compared to other studies.26 Further, it is often challenging to distinguish antiretroviral-related kidney toxicity from direct effects of HIV-1 infection on the kidney or from a multitude of non-HIV-related kidney diseases.62 If suppression of viral replication is the mechanism by which antiretroviral medications have a beneficial effect on kidney disease, the inclusion of CD4+ T-cell count would be expected to minimize the estimated relationship between these medications and progression of nephropathy by controlling for mechanism of effect. Alternatively, although we adjusted for cART, the efficacy of antiretroviral medications may not be uniform across antiretroviral classes. Variations in effect due to the use of different antiretrovirals and other issues such as compliance however would bias the investigation of this association toward the null.

The current study has potential limitations. We were unable to assess causality because of the study’s observational cross-sectional design. In addition, the assessment of proteinuria was determined from spot urine samples as opposed to a timed or 24-h urine collection; however, spot urine measurement has been shown to perform well at detecting abnormal urinary protein excretion in those with HIV, and the one time collection avoids error introduced by inadequate collections over time.57 Another limitation is that proteinuria was measured at only one time-point. This may lead to misclassification of some individuals with regard to proteinuria status as the NKF/KDOQI guidelines recommend a second measurement to confirm the persistence of proteinuria.62 Additionally, the study population was primarily composed of women and our results may not be generalizable to a broader population. In support of the study’s internal validity, evaluation of participant descriptors for those not included in the study demonstrated similar characteristics as the majority of the missing individuals were normal weight (44.8%), non-Hispanic black females (72.4%) with a mean age of 17 years old. In addition, REACH participants not included in the study presented with an average CD4+ T-cell count of 532 ± 273 cells/mm3 and 41.4% were on cART. Despite study limitations, the REACH Cohort has several notable strengths, including being a representative sample of urban HIV-infected adolescents in the US. In addition, serum and urine measurements in this study were conducted at a central laboratory following standardized procedures.

In conclusion, in the current study, kidney disease as indicated by proteinuria was present in 19.1 % of the HIV-infected adolescents participating in REACH. HIV-infected adolescents in the REACH cohort with a low CD4+ T-cell count and low BMI were more likely to be diagnosed with proteinuria. In REACH, there were significant correlations with increasing serum cystatin C concentration including low and medium CD4+ T-cell counts and a high BMI. With the level of current evidence, the added value of serum cystatin C in assessment of kidney dysfunction in HIV-infected adolescents will have to be both clinically useful and economically acceptable for its widespread adoption.20 Early detection of kidney disease in HIV-infected adolescents would allow for appropriate evaluation and treatment, as well as modification of medication regimens to avoid systemic toxicity and worsening of kidney function. Further studies investigating earlier markers of kidney damage and systemic therapies targeting kidney disease risk in this vulnerable population are warranted.

Supplementary Material

Acknowledgments

Source of Funding: The REACH study (1994–2001) was supported by the National Institute of Child Health and Human Development (U01-HD32830), with supplemental funding from the NIAID, the National Institute on Drug Abuse, and the National Institute of Mental Health. This work was also supported in part by the Adolescent Trials Network for HIV/AIDS Interventions (ATN) which is funded by the National Institutes of Health through NICHD (5 U01 HD040533).

The study was scientifically reviewed by the ATN’s Therapeutic Leadership Group. Network, scientific and logistical support was provided by the ATN Coordinating Center (C. Wilson, C. Partlow) at the University of Alabama at Birmingham. We thank the REACH investigators, staff, and participants for their valuable contributions (listed in J Adolescent Health 2001; 29: S5–S6). The parent study and this sub-study conformed to the procedures for informed consent (parental permission was obtained wherever required) approved by institutional review boards at all sponsoring organizations and to human-experimentation guidelines set forth by the United States Department of Health and Human Services.

Footnotes

Presented in part at the 19th Conference on Retroviruses and Opportunistic Infections (CROI) meeting in Seattle, March 5th–8th, 2012

Conflict of Interest: The authors have no conflict of interest to disclose.

References

1. Seal PS, Jackson DA, Chamot E, Willig JH, Nevin CR, Allison JJ, Raper JL, Kempf MC, Schumacher JE, Saag MS, Mugavero MJ. Temporal trends in presentation for outpatient HIV medical care 2000–2010: implications for short-term mortality. Journal of general internal medicine. 2011 Jul;26(7):745–750. [PMC free article] [PubMed]
2. Centers for Disease Control and Prevention (CDC) HIV surveillance--United States, 1981–2008. Morbidity and mortality weekly report. 2011 Jun 3;60(21):689–693. [PubMed]
3. Gupta SK, Eustace JA, Winston JA, Boydstun, Ahuja TS, Rodriguez RA, Tashima KT, Roland M, Franceschini N, Palella FJ, Lennox JL, Klotman PE, Nachman SA, Hall SD, Szczech LA. 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. Clinical infectious diseases: an official publication of the Infectious Diseases Society of America. 2005 Jun 1;40(11):1559–1585. [PubMed]
4. Fernando SK, Finkelstein FO, Moore BA, Weissman S. Prevalence of chronic kidney disease in an urban HIV infected population. The American journal of the medical sciences. 2008 Feb;335(2):89–94. [PubMed]
5. Szczech LA, Hoover DR, Feldman JG, Cohen MH, Gange SJ, Gooze L, Rubin NR, Young MA, Cai X, Shi Q, Gao W, Anastos K. Association between renal disease and outcomes among HIV-infected women receiving or not receiving antiretroviral therapy. Clinical infectious diseases: an official publication of the Infectious Diseases Society of America. 2004 Oct 15;39(8):1199–1206. [PubMed]
6. Wyatt CM, Hoover DR, Shi Q, Seaberg E, Wei C, Tien PC, Karim R, Lazar J, Young MA, Cohen MH. Microalbuminuria is associated with all-cause and AIDS mortality in women with HIV infection. Journal of acquired immune deficiency syndromes (1999) 2010;55(1):73. [PMC free article] [PubMed]
7. Winston JA. HIV and CKD epidemiology. Advances in chronic kidney disease. 2010 Jan;17(1):19–25. [PubMed]
8. Lucas GM, Eustace JA, Sozio S, Mentari EK, Appiah KA, Moore RD. Highly active antiretroviral therapy and the incidence of HIV-1-associated nephropathy: a 12-year cohort study. Aids. 2004 Feb 20;18(3):541–546. [PubMed]
9. Lescure FX, Flateau C, Pacanowski J, Brocheriou I, Rondeau E, Girard PM, Ronco P, Pialoux G, Plaisier E. HIV-associated kidney glomerular diseases: changes with time and HAART. Nephrology, dialysis, transplantation: official publication of the European Dialysis and Transplant Association - European Renal Association. 2012 Jan 16; [PubMed]
10. Kalyesubula R, Perazella MA. Nephrotoxicity of HAART. AIDS research and treatment. 2011;2011:562790. [PMC free article] [PubMed]
11. Daugas E, Rougier JP, Hill G. HAART-related nephropathies in HIV-infected patients. Kidney international. 2005 Feb;67(2):393–403. [PubMed]
12. Maggi P, Bartolozzi D, Bonfanti P, Calza L, Cherubini C, Di Biagio A, Marcotullio S, Montella F, Montinaro V, Mussini C. Renal Complications in HIV Disease: Between Present and Future. AIDS reviews. 2012;14(1):37. [PubMed]
13. Stoycheff N, Pandya K, Okparavero A, Schiff A, Levey AS, Greene T, Stevens LA. Early change in proteinuria as a surrogate outcome in kidney disease progression: a systematic review of previous analyses and creation of a patient-level pooled dataset. Nephrology, dialysis, transplantation: official publication of the European Dialysis and Transplant Association - European Renal Association. 2011 Mar;26(3):848–857. [PMC free article] [PubMed]
14. Garg AX, Kiberd BA, Clark WF, Haynes RB, Clase CM. Albuminuria and renal insufficiency prevalence guides population screening: results from the NHANES III. Kidney international. 2002 Jun;61(6):2165–2175. [PubMed]
15. Coresh J, Selvin E, Stevens LA, Manzi J, Kusek JW, Eggers P, Van Lente F, Levey AS. Prevalence of chronic kidney disease in the United States. JAMA: the journal of the American Medical Association. 2007 Nov 7;298(17):2038–2047. [PubMed]
16. Estrella MM, Parekh RS, Astor BC, Bolan R, Evans RW, Palella FJ, Jr, Jacobson LP. Chronic kidney disease and estimates of kidney function in HIV infection: a cross-sectional study in the multicenter AIDS cohort study. Journal of acquired immune deficiency syndromes. 2011 Aug 15;57(5):380–386. [PMC free article] [PubMed]
17. Yanik EL, Lucas GM, Vlahov D, Kirk GD, Mehta SH. HIV and proteinuria in an injection drug user population. Clinical journal of the American Society of Nephrology: CJASN. 2010 Oct;5(10):1836–1843. [PubMed]
18. Chaparro AI, Mitchell CD, Abitbol CL, Wilkinson JD, Baldarrago G, Lopez E, Zilleruelo G. Proteinuria in children infected with the human immunodeficiency virus. The Journal of pediatrics. 2008 Jun;152(6):844–849. [PubMed]
19. Esezobor CI, Iroha E, Onifade E, Akinsulie AO, Temiye EO, Ezeaka C. Prevalence of Proteinuria Among HIV-infected Children Attending a Tertiary Hospital in Lagos, Nigeria. Journal of Tropical Pediatrics. 2010 Jun 1;56(3):187–190. [PubMed]
20. Gagneux-Brunon A, Mariat C, Delanaye P. Cystatin C in HIV-infected patients: promising but not yet ready for prime time. Nephrology, dialysis, transplantation: official publication of the European Dialysis and Transplant Association -European Renal Association. 2012 Apr;27(4):1305–1313. [PubMed]
21. Choi A, Scherzer R, Bacchetti P, Tien PC, Saag MS, Gibert CL, Szczech LA, Grunfeld C, Shlipak MG. Cystatin C, albuminuria, and 5-year all-cause mortality in HIV-infected persons. American journal of kidney diseases: the official journal of the National Kidney Foundation. 2010 Nov;56(5):872–882. [PMC free article] [PubMed]
22. Overton ET, Patel P, Mondy K, Bush T, Conley L, Rhame F, Kojic EM, Hammer J, Henry K, Brooks ftSSIJT. Cystatin C Baseline Renal Function Among HIV-Infected Persons in the SUN Study. . AIDS Research and Human Retroviruses. 2012 [PubMed]
23. Neuhaus J, Jacobs DR, Jr, Baker JV, Calmy A, Duprez D, La Rosa A, Kuller LH, Pett SL, Ristola M, Ross MJ, Shlipak MG, Tracy R, Neaton JD. Markers of inflammation, coagulation, and renal function are elevated in adults with HIV infection. The Journal of infectious diseases. 2010 Jun 15;201(12):1788–1795. [PMC free article] [PubMed]
24. Wyatt CM, Klotman PE. HIV-1 and HIV-Associated Nephropathy 25 Years Later. Clinical journal of the American Society of Nephrology: CJASN. 2007 Jul;2(Suppl 1 Supplement 1):S20–24. [PubMed]
25. Purswani MU, Chernoff MC, Mitchell CD, Seage GR, 3rd, Zilleruelo G, Abitbol C, Andiman WA, Kaiser KA, Spiegel H, Oleske JM. The ICST. Chronic kidney disease associated with perinatal HIV infection in children and adolescents. Pediatric nephrology. 2012 Feb 26;:1–9. [PMC free article] [PubMed]
26. Wilson CM, Houser J, Partlow C, Rudy BJ, Futterman DC, Friedman LB. Adolescent Medicine HIVARN. The REACH (Reaching for Excellence in Adolescent Care and Health) project: study design, methods, and population profile. The Journal of adolescent health: official publication of the Society for Adolescent Medicine. 2001 Sep;29(3 Suppl):8–18. [PubMed]
27. Rogers AS, Futterman DK, Moscicki AB, Wilson CM, Ellenberg J, Vermund SH. The REACH Project of the Adolescent Medicine HIV/AIDS Research Network: design, methods, and selected characteristics of participants. The Journal of adolescent health: official publication of the Society for Adolescent Medicine. 1998 Apr;22(4):300–311. [PubMed]
28. Wilson CM, Ellenberg JH, Douglas SD, Moscicki AB, Holland CA. Reach Project Of The Adolescent Medicine HIVARN. CD8+CD38+ T cells but not HIV type 1 RNA viral load predict CD4+ T cell loss in a predominantly minority female HIV+ adolescent population. AIDS Res Hum Retroviruses. 2004 Mar;20(3):263–269. [PubMed]
29. Douglas SD, Rudy B, Muenz L, Starr SE, Campbell DE, Wilson C, Holland C, Crowley-Nowick P, Vermund SH. T-lymphocyte subsets in HIV-infected and high-risk HIV-uninfected adolescents: retention of naive T lymphocytes in HIV-infected adolescents. The Adolescent Medicine HIV/AIDS Research Network. Archives of pediatrics & adolescent medicine. 2000 Apr;154(4):375–380. [PubMed]
30. Dodder NG, Tai SS, Sniegoski LT, Zhang NF, Welch MJ. Certification of creatinine in a human serum reference material by GC-MS and LC-MS. Clinical chemistry. 2007 Sep;53(9):1694–1699. [PubMed]
31. Myers GL, Miller WG, Coresh J, Fleming J, Greenberg N, Greene T, Hostetter T, Levey AS, Panteghini M, Welch M, Eckfeldt JH. National Kidney Disease Education Program Laboratory Working G. Recommendations for improving serum creatinine measurement: a report from the Laboratory Working Group of the National Kidney Disease Education Program. Clinical chemistry. 2006 Jan;52(1):5–18. [PubMed]
32. Levey AS, Coresh J, Balk E, Kausz AT, Levin A, Steffes MW, Hogg RJ, Perrone RD, Lau J, Eknoyan G. National Kidney F. National Kidney Foundation practice guidelines for chronic kidney disease: evaluation, classification, and stratification. Annals of internal medicine. 2003 Jul 15;139(2):137–147. [PubMed]
33. Hogg RJ, Furth S, Lemley KV, Portman R, Schwartz GJ, Coresh J, Balk E, Lau J, Levin A, Kausz AT, Eknoyan G, Levey AS. National Kidney Foundation’s Kidney Disease Outcomes Quality I. National Kidney Foundation’s Kidney Disease Outcomes Quality Initiative clinical practice guidelines for chronic kidney disease in children and adolescents: evaluation, classification, and stratification. Pediatrics. 2003 Jun;111(6 Pt 1):1416–1421. [PubMed]
34. Msango L, Downs JA, Kalluvya SE, Kidenya BR, Kabangila R, Johnson WD, Jr, Fitzgerald DW, Peck RN. Renal dysfunction among HIV-infected patients starting antiretroviral therapy. Aids. 2011 Jul 17;25(11):1421–1425. [PMC free article] [PubMed]
35. Emem CP, Arogundade F, Sanusi A, Adelusola K, Wokoma F, Akinsola A. Renal disease in HIV-seropositive patients in Nigeria: an assessment of prevalence, clinical features and risk factors. Nephrology, dialysis, transplantation: official publication of the European Dialysis and Transplant Association - European Renal Association. 2008 Feb;23(2):741–746. [PubMed]
36. de Zeeuw D, Parving HH, Henning RH. Microalbuminuria as an early marker for cardiovascular disease. Journal of the American Society of Nephrology: JASN. 2006 Aug;17(8):2100–2105. [PubMed]
37. Jotwani V, Li Y, Grunfeld C, Choi AI, Shlipak MG. Risk Factors for ESRD in HIV-Infected Individuals: Traditional and HIV-Related Factors. American journal of kidney diseases: the official journal of the National Kidney Foundation. 2011 Dec 27; [PMC free article] [PubMed]
38. Chavers BM, Rheault MN, Foley RN. Kidney function reference values in US adolescents: National Health And Nutrition Examination Survey 1999–2008. Clinical journal of the American Society of Nephrology: CJASN. 2011 Aug;6(8):1956–1962. [PubMed]
39. Tien PC, Choi AI, Zolopa AR, Benson C, Tracy R, Scherzer R, Bacchetti P, Shlipak M, Grunfeld C. Inflammation and mortality in HIV-infected adults: analysis of the FRAM study cohort. Journal of acquired immune deficiency syndromes. 2010 Nov;55(3):316–322. [PMC free article] [PubMed]
40. Fulop T, Olivier J, Meador RS, Hall J, Islam N, Mena L, Henderson H, Schmidt DW. Screening for chronic kidney disease in the ambulatory HIV population. Clinical nephrology. 2010 Mar;73(3):190–196. [PubMed]
41. Gupta SK, Smurzynski M, Franceschini N, Bosch RJ, Szczech LA, Kalayjian RC. Team ACTGLLRTS. The effects of HIV type-1 viral suppression and non-viral factors on quantitative proteinuria in the highly active antiretroviral therapy era. Antiviral therapy. 2009;14(4):543–549. [PMC free article] [PubMed]
42. Szczech LA, Gange SJ, van der Horst C, Bartlett JA, Young M, Cohen MH, Anastos K, Klassen PS, Svetkey LP. Predictors of proteinuria and renal failure among women with HIV infection. Kidney international. 2002 Jan;61(1):195–202. [PubMed]
43. de Jong PE, Verhave JC, Pinto-Sietsma SJ, Hillege HL. group Ps. Obesity and target organ damage: the kidney. International journal of obesity and related metabolic disorders: journal of the International Association for the Study of Obesity. 2002 Dec;26 (Suppl 4):S21–24. [PubMed]
44. Chen J, Muntner P, Hamm LL, Jones DW, Batuman V, Fonseca V, Whelton PK, He J. The metabolic syndrome and chronic kidney disease in U.S. adults. Annals of internal medicine. 2004 Feb 3;140(3):167–174. [PubMed]
45. Deti EK, Thiebaut R, Bonnet F, Lawson-Ayayi S, Dupon M, Neau D, Pellegrin JL, Malvy D, Tchamgoue S, Dabis F, Morlat P. Groupe d’Epidemiologie Clinique du SeA. Prevalence and factors associated with renal impairment in HIV-infected patients, ANRS C03 Aquitaine Cohort, France. HIV medicine. 2010 May;11(5):308–317. [PubMed]
46. Menezes AM, Torelly J, Jr, Real L, Bay M, Poeta J, Sprinz E. Prevalence and risk factors associated to chronic kidney disease in HIV-infected patients on HAART and undetectable viral load in Brazil. PloS one. 2011;6(10):e26042. [PMC free article] [PubMed]
47. Lindsey JC, Jacobson DL, Li H, Houseman EA, Aldrovandi GM, Mulligan K. Using Cluster Heat Maps to Investigate Relationships Between Body Composition and Laboratory Measurements in HIV-Infected and HIV-Uninfected Children and Young Adults. Journal of acquired immune deficiency syndromes. 2012;59(3):325–328. [PMC free article] [PubMed]
48. Jacobson DL, Patel K, Siberry GK, Van Dyke RB, DiMeglio LA, Geffner ME, Chen JS, McFarland EJ, Borkowsky W, Silio M, Fielding RA, Siminski S, Miller TL. Pediatric HIVACS. Body fat distribution in perinatally HIV-infected and HIV-exposed but uninfected children in the era of highly active antiretroviral therapy: outcomes from the Pediatric HIV/AIDS Cohort Study. The American journal of clinical nutrition. 2011 Dec;94(6):1485–1495. [PubMed]
49. Groesbeck D, Kottgen A, Parekh R, Selvin E, Schwartz GJ, Coresh J, Furth S. Age, gender, and race effects on cystatin C levels in US adolescents. Clinical journal of the American Society of Nephrology: CJASN. 2008 Nov;3(6):1777–1785. [PubMed]
50. Larsson A, Hansson LO, Flodin M, Katz R, Shlipak MG. Calibration of the Siemens cystatin C immunoassay has changed over time. Clinical chemistry. 2011;57(5):777. [PubMed]
51. Zappitelli M, Parvex P, Joseph L, Paradis G, Grey V, Lau S, Bell L. Derivation and validation of cystatin C-based prediction equations for GFR in children. American journal of kidney diseases: the official journal of the National Kidney Foundation. 2006 Aug;48(2):221–230. [PubMed]
52. Levey AS, Coresh J, Greene T, Stevens LA, Zhang YL, Hendriksen S, Kusek JW, Van Lente F. Chronic Kidney Disease Epidemiology C. Using standardized serum creatinine values in the modification of diet in renal disease study equation for estimating glomerular filtration rate. Ann Intern Med. 2006 Aug 15;145(4):247–254. [PubMed]
53. Schwartz GJ, Haycock GB, Edelmann CM, Jr, Spitzer A. A simple estimate of glomerular filtration rate in children derived from body length and plasma creatinine. Pediatrics. 1976 Aug;58(2):259–263. [PubMed]
54. Schwartz GJ, Work DF. Measurement and estimation of GFR in children and adolescents. Clinical journal of the American Society of Nephrology: CJASN. 2009 Nov;4(11):1832–1843. [PubMed]
55. Stevens LA, Coresh J, Schmid CH, Feldman HI, Froissart M, Kusek J, Rossert J, Van Lente F, Bruce RD, 3rd, Zhang YL, Greene T, Levey AS. Estimating GFR using serum cystatin C alone and in combination with serum creatinine: a pooled analysis of 3,418 individuals with CKD. American journal of kidney diseases: the official journal of the National Kidney Foundation. 2008 Mar;51(3):395–406. [PMC free article] [PubMed]
56. Muntner P, Vupputuri S, Coresh J, Uribarri J, Fox CS. Metabolic abnormalities are present in adults with elevated serum cystatin C. Kidney international. 2009 Jul;76(1):81–88. [PMC free article] [PubMed]
57. Inker LA, Schmid CH, Tighiouart H, Eckfeldt JH, Feldman HI, Greene T, Kusek JW, Manzi J, Van Lente F, Zhang YL, Coresh J, Levey AS. Estimating Glomerular Filtration Rate from Serum Creatinine and Cystatin C. New England Journal of Medicine. 2012;367(1):20–29. [PubMed]
58. Jaroszewicz J, Wiercinska-Drapalo A, Lapinski TW, Prokopowicz D, Rogalska M, Parfieniuk A. Short communication Does HAART improve renal function? An association between serum cystatin C concentration, HIV viral load and HAART duration. Antiviral therapy. 2006;11:641–645. [PubMed]
59. Gupta SK, Komarow L, Gulick RM, Pollard RB, Robbins GK, Franceschini N, Szczech LA, Koletar SL, Kalayjian RC. Proteinuria, creatinine clearance, and immune activation in antiretroviral-naive HIV-infected subjects. The Journal of infectious diseases. 2009 Aug 15;200(4):614–618. [PMC free article] [PubMed]
60. Choi AI, Shlipak MG, Hunt PW, Martin JN, Deeks SG. HIV-infected persons continue to lose kidney function despite successful antiretroviral therapy. Aids. 2009 Oct 23;23(16):2143–2149. [PMC free article] [PubMed]
61. Baker JV, Peng G, Rapkin J, Abrams DI, Silverberg MJ, MacArthur RD, Cavert WP, Henry WK, Neaton JD. Terry Beirn Community Programs for Clinical Research on A. CD4+ count and risk of non-AIDS diseases following initial treatment for HIV infection. Aids. 2008 Apr 23;22(7):841–848. [PMC free article] [PubMed]
62. Atta MG, Deray G, Lucas GM. Antiretroviral nephrotoxicities. Seminars in nephrology. 2008 Nov;28(6):563–575. [PubMed]
63. Coresh J, Astor BC, McQuillan G, Kusek J, Greene T, Van Lente F, Levey AS. Calibration and random variation of the serum creatinine assay as critical elements of using equations to estimate glomerular filtration rate. American journal of kidney diseases: the official journal of the National Kidney Foundation. 2002;39(5):920–929. [PubMed]