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Objectives: The aim of this study was to evaluate the agreement between self-reported sleep measures and insomnia with objectively measured sleep parameters in people with HIV (PWH) and HIV-negative individuals., Design: A cross-sectional analysis of PWH and lifestyle-similar HIV-negative individuals., Methods: Self-reported measures included time spent in bed, sleep onset latency and a validated insomnia questionnaire. Objective measures were assessed via 7-days/nights of actigraphy data to determine average and intra-individual variability of several sleep measures (including time spent in bed and onset latency). Spearman's correlation coefficient and Cohen's κ were used to assess the agreement between self-reported and actigraphy-assessed measures. Associations between insomnia and actigraphy-assessed sleep parameters were evaluated using partial least-square discriminant analysis (PLS-DA)., Results: We found fair correlation between self-reported and actigraphy-assessed time spent in bed in 342 PWH (rs = 0.46) and 119 HIV-negative individuals (rs = 0.48). Among PWH, the correlation did not differ by age, education, depressive symptoms and self-reported insomnia (all P > 0.05), but was stronger in men (P = 0.05) and in those with a BMI of at least 25 kg/m2 (P < 0.001). Agreement between self-reported and actigraphy-assessed sleep onset latency was poor in both PWH (κ = 0.002, P = 0.49) and HIV-negative individuals (κ = 0.009, P = 0.65). According to PLS-DA, self-reported insomnia most strongly correlated with intra-individual variability of sleep duration, movement index and efficiency., Conclusion: We report poor-to-fair agreement between self-reported and actigraphy-assessed sleep measures in PWH. Insomnia symptoms correlated with regularity of sleep duration, quality and efficiency. These findings highlight the importance of both patient-reported and objective measures of daily sleep variation, for better understanding sleep disorders in PWH., (Copyright © 2021 Wolters Kluwer Health, Inc. All rights reserved.)

Objective: To determine comorbidity indices in people with HIV (PWH) and lifestyle-similar HIV-negative controls., Design: Cross-sectional analysis of the Pharmacokinetic and clinical Observations in PeoPle over fiftY cohort study in the United Kingdom and Ireland., Methods: The Elixhauser Comorbidity Index (ECI), Charlson Comorbidity Index and the Comorbidity Burden Index were compared between older PWH and HIV-negative controls using the Mann-Whitney U test; the magnitude of the difference between groups was quantified using the r effect size., Results: The 699 PWH and 304 HIV-negative controls were predominantly male (87.5% vs. 64.0%), white (86.3% vs. 90.0%) and had median ages of 57 and 58 years, respectively. Among PWH, the median (interquartile range) CD4 T-cell count was 624 (475, 811) cells/μl; 98.7% were on antiretroviral therapy. The median (interquartile range) ECI was 0 (0, 8) and 0 (-3, 1), Charlson Comorbidity Index was 2 (1, 5) and 1 (0, 1) and Comorbidity Burden Index 8.6 (2.2, 16.8) and 5.9 (0.6, 10.8), respectively. While all three indices were significantly higher in PWH than in controls (P < 0.001 for each), the magnitude of the differences between the two groups were small to medium, with effect sizes (95% confidence interval) of 0.21 (0.16, 0.27), 0.38 (0.32, 0.42) and 0.18 (0.11, 0.23), respectively., Conclusion: These three comorbidity indices are higher in PWH compared with HIV-negative controls, although the magnitude of differences between groups were small. Differences in the ECI, reportedly associated with poorer coronavirus disease 2019 outcomes, were driven by more individuals with HIV being within the higher end of the range.

Aims: To assess associations of comorbidity patterns observed in people living with HIV (PLWH) with risk factors and health outcomes., Methods: Common patters of comorbidities in PLWH participating in the Pharmacokinetic and Clinical Observations in People Over Fifty study were determined using principal component analysis and a severity score for each pattern was derived. Associations between each pattern's severity score and risk factors were assessed using median regression. The independent associations of patterns' severity scores with self-reported physical and mental health (SF-36 summary scores) were assessed using linear regression, with functional impairment (Lawton IADL < 8) and hospitalization in last year using logistic regression and with number of general practitioner visits using Poisson regression., Results: A total of 1073 PLWH were analysed: 85.2% male, median (interquartile range) age 52 (47-59) years, 98% on therapy. Duration of HIV was associated with higher severity in 4/6 of patterns: cardiovascular diseases, mental health problems, metabolic disorders and chest/other infections (all P ≤ 0.001). Prior AIDS was associated with higher severity scores for the same patterns and for the pattern of cancers (P < 0.001). The pattern of cardiovascular diseases was associated with poorer physical health (P = 0.02), higher risk of functional impairment (P = 0.02) and hospitalization (P < 0.001) and with higher number of general practitioner visits (P < 0.001). Severity of mental health (all P < 0.001) and of chest/other infections patterns negatively affected all the five health outcomes., Conclusion: Common patterns of comorbidities seen in PLWH appear to have different risk factors and to differently affect health outcomes. These findings may assist the development of targeted intervention to prevent, treat and manage the increasingly prevalent multimorbidity in PLWH.

Objectives: Despite successful antiretroviral therapy, people living with HIV (PLWH) may show signs of premature/accentuated aging. We compared established biomarkers of aging in PLWH, appropriately chosen HIV-negative individuals, and blood donors, and explored factors associated with biological age advancement., Design: Cross-sectional analysis of 134 PLWH on suppressive antiretroviral therapy, 79 lifestyle-comparable HIV-negative controls aged 45 years or older from the Co-morBidity in Relation to AIDS (COBRA) cohort, and 35 age-matched blood donors., Methods: Biological age was estimated using a validated algorithm based on 10 biomarkers. Associations between 'age advancement' (biological minus chronological age) and HIV status/parameters, lifestyle, cytomegalovirus (CMV), hepatitis B (HBV) and hepatitis C virus (HCV) infections were investigated using linear regression., Results: The average (95% CI) age advancement was greater in both HIV-positive [13.2 (11.6-14.9) years] and HIV-negative [5.5 (3.8-7.2) years] COBRA participants compared with blood donors [-7.0 (-4.1 to -9.9) years, both P's < 0.001)], but also in HIV-positive compared with HIV-negative participants (P < 0.001). Chronic HBV, higher anti-CMV IgG titer and CD8 T-cell count were each associated with increased age advancement, independently of HIV-status/group. Among HIV-positive participants, age advancement was increased by 3.5 (0.1-6.8) years among those with nadir CD4+ T-cell count less than 200 cells/μl and by 0.1 (0.06-0.2) years for each additional month of exposure to saquinavir., Conclusion: Both treated PLWH and lifestyle-comparable HIV-negative individuals show signs of age advancement compared with blood donors, to which persistent CMV, HBV co-infection and CD8+ T-cell activation may have contributed. Age advancement remained greatest in PLWH and was related to prior immunodeficiency and cumulative saquinavir exposure.