Prevalence and Predictors of Hospitalizations Among HIV-Infected and At-Risk HIV-Uninfected Women

J Acquir Immune Defic Syndr. 2017 Jun 1;75(2):e27-e35. doi: 10.1097/QAI.0000000000001278.

Abstract

Objectives: We evaluated the Veterans Aging Cohort Study (VACS) Index score, an index composed of age, CD4 count, viral load, hemoglobin, Hepatitis C coinfection, Fibrosis Index-4, and estimated glomerular filtration rate, and psychosocial and clinical risk factors for all-cause hospitalization among HIV-infected women on highly active antiretroviral therapy and HIV-uninfected women.

Methods: Data were collected from 2008 to 2014 from 1585 highly active antiretroviral therapy-experienced HIV infected and 692 uninfected women. Cox proportional hazards regression evaluated predictors of first hospitalization over 2 years.

Results: Among HIV-infected women, VACS Index score (per 5 points) [adjusted hazard ratio (aHR) 1.08; 95% confidence interval (CI): 1.06 to 1.11], Centers for Epidemiologic Studies-Depression (CESD) scores ≥16 (aHR 1.61; 95% CI: 1.30 to 1.99), smoking (aHR 1.26; 95% CI: 1.02 to 1.55), abuse history (aHR 1.52; 95% CI: 1.20 to 1.93), diabetes (aHR 1.63; 95% CI: 1.31 to 2.04), and black race (aHR 1.28; 95% CI: 1.03 to 1.59) increased risk of hospitalization. Among HIV-uninfected women, VACS Index score (aHR 1.08; 95% CI: 1.03 to 1.13), CESD scores ≥16 (aHR 1.38; 95% CI: 1.02 to 1.86), diabetes (aHR 2.15; 95% CI: 1.57 to 2.95), and black race (aHR 1.61; 95% CI: 1.15 to 2.24) predicted subsequent hospitalization.

Conclusions: Psychosocial and clinical factors were associated with risk of hospitalization independently of the VACS Index score. Additional research on contextual and psychosocial influences on health outcomes among women is needed.

Publication types

  • Research Support, N.I.H., Extramural

MeSH terms

  • Antiretroviral Therapy, Highly Active*
  • CD4 Lymphocyte Count
  • Female
  • HIV Infections / epidemiology*
  • HIV Infections / immunology
  • HIV Infections / therapy
  • Hospitalization / statistics & numerical data*
  • Humans
  • New York City / epidemiology
  • Population Surveillance
  • Prevalence
  • Proportional Hazards Models
  • Viral Load / drug effects*