Agreement between self-reported knowledge and medical record data.

People living with HIV (PLWH) see their providers quarterly to go over their laboratory results and discuss problems with antiretroviral treatment (ART) regimens. Our purpose was to determine whether socially and economically marginalized PLWH were accurate in self-reporting their most recent CD4 count, viral load, and ART regimen, and whether demographic differences influenced self-reporting. We conducted a secondary data analysis based on results from (N = 200) PLWH. We found moderate agreement for CD4 count (k = .58), and viral load (k = .43), but only 43% were able to recall their ART regimens accurately. PLWH ≥ age 50 (k = .77) and those with health insurance coverage (k = .61) were more accurate to self-report CD4. Women were more accurate in reporting viral load than men (k = .53, p = .003 vs. k = .38). These findings suggest that PLWH need multiple modalities of education to relate CD4 counts, viral load, and ART regimens to their personal health understanding.

Identification of fatigue biomarkers in treated and treatment-naive HIV patients: preliminary results.

Objective assessment in human immunodeficiency virus (HIV)-related fatigue has been elusive because the biological mechanisms are not well characterized. We tried to identify low-abundance plasma proteins that correlate with self-reported fatigue intensity in people living with HIV. We used plasma samples from 32 patients with HIV with varying degrees of fatigue who were either treated with nucleoside reverse transcriptase inhibitors or treatment naïve. The plasma samples were enriched for low-abundance proteins and trypsinized. The peptides were analyzed using shotgun proteomics. Five targets correlated with severity of fatigue: apolipoprotein A-1 (ApoA1), apolipoprotein B (ApoB), histine-rich glycoprotein, alpha-1 B glycoprotein, and orosomucoid 2. These targets were selected based on total abundance and spectral count differences, and ApoA1 and ApoB were analyzed via Western blots to verify the mass spectrometry results. ApoA1 levels were higher in untreated patients, while ApoB results suggested a possible positive trend in treated patients. Further analysis is needed to identify additional low-abundance proteins and confirm already-identified proteins as potential fatigue biomarkers.