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Clinical hypotheses:
The increasing number of people aging with HIV is a matter of fact. Differences in prevalence of comorbidities between the general population and HIV-positive patients are mainly driven by duration of HIV infection rather than chronological age of HIV+ patients.
People aging with HIV display heterogeneous health conditions. Host factors and duration of HIV infection are associated with increased risk of MM, independently from chronological age and these factors are responsible of the prevalence difference of comorbidities and MM in comparison to the general population.
Objectives:
The study objective is to assess the prevalence of, and risk factors for, individual co-morbidities and multi morbidity (MM) between HIV-positive patients with similar duration of HIV infection, but 30 years difference. We compared estimates across both groups to a matched community-based cohort sampled from the general population.
Full description
This study is a case-control study, including antiretroviral therapy (ART)-experienced patients, coming from the two following cohorts:
Aging-Young patients will be matched to Aging-Old patients considering gender and HIV duration (within 1 year interval) (This is the most important matching criteria. The exact number of year of HIV duration since HIV test is the major criteria). An HIV negative test within 5 years prior HIV diagnosis is required in the selection of patients from MHMC to avoid an unpredicted HIV time exposure in these patients.
Then, Aging-young and Aging-old patients will be age, gender matched with a 1: 3 ratio with CINECA (Consorzio Interuniversitario di Calcolo) "ARNO" records (control group, called "HIV-negative group"). The study will analyse 200 HIV Aging-Young and 200 HIV Aging-Old patients in comparison to 1200 controls.
In the first set of analyses, the prevalence of non-infectious comorbidities (NICM) and multimorbidities (MM) in HIV Aging-Young and in HIV Aging-Old groups will be compared to those of HIV-negative group using multivariable logistic regression models. In the second set of analyses, the probability of MM in the HIV Aging-Young cohort will be compared to the HIV Aging-Old one, using multivariable logistic regression models.
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Inclusion criteria
HIV Aging-Old patients will be selected at Modena HIV metabolic Clinic. 200 consecutive patients who satisfy the following criteria:
HIV Aging-Young patients will be selected at Romanian HIV Cohort. 200 consecutive patients who satisfy the following criteria:
Exclusion criteria
131 participants in 3 patient groups
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Data sourced from clinicaltrials.gov
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