Trends of hospitalisations rates in a cohort of HIV-infected persons followed in an Italian hospital from 1998 to 2016

S. Bellino, A. Borghetti, Francesca Lombardi, L. Camoni, Arturo Ciccullo, Gianmaria Baldin, S. Belmonti, Davide Moschese, S. Lamonica, Roberto Cauda, P. Pezzotti, Simona Di Giambenedetto

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7 Citazioni (Scopus)


Here we evaluated hospitalisation rates and associated risk factors of human immunodeficiency virus (HIV)-infected individuals who were followed up in an Italian reference hospital from 1998 to 2016. Incidence rates (IR) of hospitalisations were calculated for five study periods from 1998 to 2016. The random-effects Poisson regression model was used to assess risk factors for hospitalisation including demographic and clinical characteristics. To consider that more events may occur for the same subject, multiple failure-time data analysis was also performed for selected causes using the Cox proportional hazards model. We evaluated 2031 patients. During 13 173 person-years (py) of follow-up, 3356 hospital admissions were carried out for 756 patients (IR: 255 per 1000 py). IR decreased significantly over the study period, from 634 in 1998-2000 to 126 per 1000 py in 2013-2016. Major declines were detected for AIDS-defining events, non-HIV/AIDS-related infections and neurological diseases. Older age, female sex, longer HIV duration and HCV coinfection were associated with a higher hospitalisation risk, whereas higher CD4 nadir and antiretroviral therapy were associated with a reduced risk. Influence of advanced HIV disease markers declined over time. Hospitalisation rates decreased during the study period in most causes. The relative weight of hospitalisations for non-AIDS-related tumours, cardiovascular, respiratory and kidney diseases increased during the study period, whereas those for AIDS-defining events declined.
Lingua originaleEnglish
pagine (da-a)e89-e89
Numero di pagine1
RivistaEpidemiology and Infection
Stato di pubblicazionePubblicato - 2019


  • Causes for hospitalisation
  • HIV
  • Poisson regression model
  • cohort study
  • hospitalisation rates
  • multiple failure-time data analysis


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