Back

Archi-Prevaleat project. A National cohort of color-Doppler ultrasonography of the epi-aortic vessels in Patients Living with HIV

Maggi, P.; Ricci, E. D.; Muccini, C.; Galli, L.; Celesia, B. M.; Ferrara, S.; Salameh, Y.; Basile, R.; Di Filippo, G.; Taccari, F.; Tartaglia, A.; Castagna, A.

2022-08-03 hiv aids
10.1101/2022.08.02.22278263 medRxiv
Show abstract

ObjectivesTo evaluate the prevalence of carotid intima-media thickness and plaques in a cohort of persons living with HIV, the role of cardiovascular risk factors, the impact of the antiretroviral regimens, and the difference between naive and experienced patients in the onset of carotid lesions. MethodsThis project was initiated in 2019 and involves eight Italian Centers. Carotid changes were detected using a power color-Doppler ultrasonography with 7.5 MHz probes. The following parameters are evaluated: intima-media thickness of both the right and left common and internal carotids: Data regarding risk factors for CVD, HIV viral load, CD4+ cell counts, serum lipids, glycaemia, and body mass index. The associations between pathological findings and potential risk factors were evaluated by logistical regression, with odds ratios (OR) and 95% confidence intervals (95% CI). ResultsAmong 1147 evaluated patients, aged 52 years on average, 347 (30.2%) had pathological findings (15.8% plaques and 14.5% IMT). Besides usual risk factors, such as older age, male sex, and dyslipidemia, CD4+ cell nadir <200 cells/mL (OR 1.51, 95% CI 1.14-1.99) and current use of raltegravir (OR 1.54, 95% CI 1.01-2.36) were associated with higher prevalence of pathological findings. ConclusionsOur data show that the overall percentage of carotid impairments nowadays remains high. Color-Doppler ultrasonography could play a pivotal role in identifying and quantifying atherosclerotic lesions among persons living with HIV, even at a very premature stage, and should be included in the algorithms of comorbidity management of these patients.

Matching journals

The top 3 journals account for 50% of the predicted probability mass.

50% of probability mass above

"Similar papers" are the closest papers from that journal in the model's embedding space. They show what the match is built on, but the ranking comes mostly from a classifier over the whole training set, not from these examples alone.