Table 3. Factors independently associated with urine biomarker concentrations among HIV-infected WIHS participants (N=908).
| IL-18 | KIM-15 | NGAL | ACR | ||||
|---|---|---|---|---|---|---|---|
|
|
|||||||
| % Estimate (95% CI)1 | % Estimate (95% CI) | % Estimate (95% CI) | % Estimate (95% CI) |
||||
|
| |||||||
| Full Model2 | Full Model +ACR+eGFRCys3 |
Full Model2 | Full Model +ACR+eGFRCys3 |
Full Model2 | Full Model +ACR+eGFRCys3 |
Full Model +eGFRCys4 |
|
| Demographics | |||||||
| Age (per decade) | −6 (−14, 3) | −11 (−19, −3) + | −8 (−18, 3) | −13 (−22, −3)* | −11 (−20, −2)* | −19 (−27, −9) ▲ | −9 (−20, 4) |
| African-American6 | 59 (34, 88)▲ | 63 (38, 92) ▲ | −5 (−22, 16) | −1 (−18, 20) | 58 (29, 94) ▲ | 60 (31, 96) ▲ | 43 (12, 83) + |
| Other Race6 | 48 (20, 81) + | 51 (23, 84) ▲ | 4 (−18, 30) | 7 (−14, 34) | 24 (−2, 58) | 32 (5, 67)* | 7 (−20, 44) |
| Traditional | |||||||
| Hypertension | - | - | 31 (12, 54) ▲ | 23 (5, 44) + | 25 (2, 52)* | 8(−11, 31) | 69 (31, 118) ▲ |
| Diabetes | - | - | - | - | - | - | 43 (5, 95)* |
| LDL (per 10 mg/dL) | - | - | - | - | 2 (0, 5)* | 3 (1, 6)* | - |
| HDL (per 10 mg/dL) | −5 (−9, −2) + | −5 (−8, −1)* | - | - | - | - | - |
| Current Smoking | - | - | 15 (0, 32)* | 7 (−7, 22) | 23 (6, 43) + | 19 (1, 40)* | −28 (−40, −12) + |
| HIV-related | |||||||
| CD4 Count (per doubling) |
−8 (−13, −3) + | −8 (−13, −3) + | −8 (−13, −2) + | −5 (−11, 0) | −7 (−12, 0)* | −5 (−10, 1) | |
| Viral Load7 | 15 (8, 22) ▲ | 12 (6, 20) ▲ | - | - | - | - | 10 (1, 19)* |
| NNRTI Use | - | - | - | - | - | - | 57 (29, 91) ▲ |
| Other | |||||||
| HCV Infection | 30 (13, 49)+ | 20 (4, 39)* | 20 (3, 40)* | 11 (−5, 29) | - | - | - |
| Heroin Use | - | 39 (2, 90)* | 32 (−2, 78) | - | - | - | |
Results for each model displayed as percent estimate (95% confidence interval). Percent estimate represents estimated percentage difference in biomarker attributable to each factor, after performing stepwise multivariable linear regression. All analyses were performed using log-transformed mean urine values; results are back-transformed to produce % estimates.
Adjusted for demographics and the factors displayed under each respective biomarker.
Adjusted for demographics, the factors displayed under each biomarker, ACR and eGFRCys.
Multivariate model for ACR adjusts for eGFRCys in addition to listed covariates.
Multivariate model for KIM-1 adjusts for menopause in addition to listed covariates.
Versus Caucasian
per 10-fold increase
denote P-value <.05, <.01, <.001, respectively
Abbreviations: ACR, albumin-to-creatinine ratio; HCV, hepatitis C virus; HDL, high-density lipoprotein; eGFRCys, estimated glomerular filtration rate calculated using cystatin C; IL-18, interleukin-18; KIM-1, kidney injury molecule-1; NGAL, neutrophil gelatinase-associated lipocalin. NNRTI, non-nucleoside reverse transcriptase inhibitor.