| Literature DB >> 24516530 |
Joseph B Margolick1, Lisa P Jacobson2, George J Schwartz3, Alison G Abraham2, Annie T Darilay2, Lawrence A Kingsley4, Mallory D Witt5, Frank J Palella6.
Abstract
OBJECTIVE: Formulae used to estimate glomerular filtration rate (GFR) underestimate higher GFRs and have not been well-studied in HIV-infected (HIV(+)) people; we evaluated the relationships of HIV infection and known or potential risk factors for kidney disease with directly measured GFR and the presence of chronic kidney disease (CKD).Entities:
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Year: 2014 PMID: 24516530 PMCID: PMC3917840 DOI: 10.1371/journal.pone.0086311
Source DB: PubMed Journal: PLoS One ISSN: 1932-6203 Impact factor: 3.240
Characteristics of the study sample at the time of iohexol-based glomerular filtration rate (iGFR) determination.
| Characteristic | HIV(−) | HIV(+) | Overall | ||||
| (N = 258) | (N = 455) | (N = 713) | |||||
| Median (IQR) or % | |||||||
| Black (%) | 33 | 36 | 35 | ||||
| Age, yr | 54 (48–61) | 51 (46–57) | 52 (47–58) | ||||
| Height, m | 1.76 (1.71–1.82) | 1.76 (1.71–1.80) | 1.76 (1.71–1.81) | ||||
| Weight, kg | 83.4 (74.7–93.6) | 79.0 (71.2–88.9) | 80.8 (72.4–91.0) | ||||
| Body-Mass Index, kg/m2
| 26.8 (24.2–29.9) | 25.8 (23.5–28.5) | 26.3 (23.8–29.0) | ||||
| Body surface area, m2
| 2.04 (1.91–2.19) | 1.98 (1.86–2.11) | 2.01 (1.87–2.14) | ||||
| Serum creatinine, mg/dl | 0.88 (0.78–1.01) | 0.87 (0.75–1.02) | 0.88 (0.76–1.01) | ||||
| Proteinuria | 4.7 | 19.3 | 14.0 | ||||
| HCV-infected (%) | 12 | 15 | 14 | ||||
| History of diabetes mellitus (%) | 14 | 18 | 17 | ||||
| History of hypertension (%) | 70 | 66 | 67 | ||||
| History of dyslipidemia | 88 | 96 | 93 | ||||
| GFR (MDRD) (ml/min/1.73 m2) | 95 (82–110) | 99 (85–117) | 97 (83–115) | ||||
| GFR (CKD-Epi) (ml/min/1.73 m2) | 98 (86–109) | 102 (91–113) | 101 (88–111) | ||||
| GFR (iohexol) (ml/min/1.73 m2) | 106 (96–119) | 109 (92–125) | 107 (94–123) | ||||
| History of AIDS (%) | 15 | ||||||
| HIV RNA <50 copies/mL (%) | 80 | ||||||
| CD4 lymphocyte count (cells/uL) | 536 (384–737) | ||||||
| Tenofovir use (%) | Never | 22 | |||||
| Former | 14 | ||||||
| Current | 64 | ||||||
HCV = hepatitis C virus.
P-value <0.05 (χ2-test or Kruskal-Wallis or Median test for comparison between HIV(−) and HIV(+)).
Figure 1Distribution of iohexol-based GFR (iGFR) by age and HIV serostatus.
Boxplots indicate distribution of iGFR values for each category of age (in 5 year increments) and HIV serostatus; gray figures for HIV-uninfected and black figures for HIV-infected. Percentiles that are presented are the 2.5%, 5%, 10%, 25%, 50%, 75%, 90%, 95% and 97.5%. Horizontal dashed lines indicate 90 and 60 ml/min/1.73 m2. The percentages of the data for each box that are below 90 ml/min/1.73 m2 are given. The numbers (N) of observations contributing to each box are provided at the bottom of the graph.
Factors associated with mean iohexol-based GFR (iGFR) in the Multicenter AIDS Cohort Study, results from linear regression models.
| Univariate Analysis | Multivariate Analysis | ||||
| Characteristic | All | HIV-infected | |||
| iGFR mean (S.E.) | P-value | Diff (95% CI) | Diff (95% CI) | ||
| Age | <40 yr | 123 (2.5) | ND | ND | |
| 40–49 yr | 113 (1.5) |
| |||
| 50–59 yr | 108 (1.4) |
| |||
| ≥60 yr | 93 (2.0) |
| |||
| Age (per 10 years) | not applicable |
| − | − | |
| Race | Non-black | 108 (1.1) | Ref | Ref | |
| Black | 108 (1.6) | 0.69 | −3.5 (−7.4, 0.2) | −3.3 (−7.9, 1.4) | |
| HIV and AIDS | No HIV | 107 (1.4) | Ref | ||
| HIV(+) without AIDS | 110 (1.2) | 0.13 | <0.1 (−3.4, 3.5) | Ref | |
| HIV(+) with AIDS | 101 (3.4) | 0.07 | − | −5.9 (−11.9, 0.2) | |
| Hepatitis C virus | Not infected | 109 (1.0) | Ref | Ref | |
| Infected | 102 (2.6) |
| − | − | |
| History of diabetes | No | 109 (1.0) | Ref | Ref | |
| Yes | 104 (2.5) |
| −2.1 (−6.6, 2.4) | −1.5 (−7.4, 4.4) | |
| History of hypertension | No | 111 (1.4) | Ref | Ref | |
| Yes | 106 (1.2) |
| 2.4 (−1.4, 6.2) | 1.02 (−3.6, 5.6) | |
| History of dyslipidemia | No | 108 (3.3) | ND | ND | |
| Yes | 108 (0.9) | 0.97 | |||
| Proteinuria | No | 111 (0.9) | ND | ND | |
| Yes | 87 (2.8) |
| |||
| HIV RNA | Undetectable | 108 (1.3) | ND | Ref | |
| Detectable | 111 (2.7) | 0.37 | −1.7 (−7.4, 3.9) | ||
| CD4 T cell count/uL | <300 | 111 (3.3) | ND | Ref | |
| 300–500 | 106 (2.5) | 0.12 | −5.7 (−12.4, 1.1) | ||
| >500 | 109 (1.4) | 0.54 | −4.1 (−10.5, 2.4) | ||
| HAART regimen | PI | 108 (1.3) | ND | ND | |
| NNRTI but no PI | 110 (2.6) | 0.65 | |||
| HAART duration (per year) | not applicable | 0.12 | ND | −0.1 (−0.9, 0.5) | |
| Tenofovir use | Never | 110 (2.5) | ND | Ref | |
| Former | 100 (3.9) |
| − | ||
| Current | 110 (1.4) | 0.85 | −3.5 (−8.9, 1.8) | ||
| Tenofovir exposure | None | 110 (2.5) | ND | ND | |
| >0 to 4 years | 109 (1.8) | 0.62 | |||
| >4 years | 107 (1.9) | 0.32 | |||
*Data given in ml/min/1.73 m2.
Bold indicates significant at P<.05.
ND = not included in the multivariate analysis.
Ref = reference value for the variable.
**Not included in multivariate analysis because of lack of independence from the other variables.
PI = protease inhibitor.
NNRTI = non-nucleoside reverse transcriptase inhibitor.
Figure 2Comparative analysis of risk factors for low GFR (≤90 ml/min/1.73 m2) in MACS participants, using iohexol-based GFR (blue) or estimated GFR (brown).
Odds ratios (solid boxes) and 95 percent confidence intervals (bars) were obtained from multivariate logistic regression models. HCV = Hepatitis C Virus infection. Diabetes = diabetes mellitus. HBP = high blood pressure.
Figure 3Multivariate predictions of CKD stage 1 or greater using either iohexol-based GFR (iGFR) or estimated GFR (eGFR), for (A) all participants and (B) HIV-infected (HIV(+)) participants only.
Odds ratios (solid boxes) and 95 percent confidence intervals (bars) were obtained from multivariate logistic regression models.