Late diagnosis of HIV infection: the role of age and sex.
BACKGROUND
Late diagnosis of human immunodeficiency virus (HIV) infection is detrimental to infected persons and to the public health. The objective of this study was to identify factors associated with late diagnosis of HIV infection, defined as an initial CD4 count <200 cells/microL, in a cohort of recently diagnosed persons. Additionally, we evaluated factors associated with HIV infection being diagnosed during hospitalization.


METHODS
This was a cross-sectional study of a university-based HIV clinic in the southeastern US. Patients with newly diagnosed HIV infection evaluated at the Duke University HIV clinic between October 2002 and August 2004 were included in this analysis. Socio-demographic variables, site of HIV diagnosis, opportunistic infections present at diagnosis, initial CD4 count, and initial HIV RNA level were recorded for study subjects.


RESULTS
Forty-nine percent of subjects met the immunologic definition of AIDS at the time of HIV diagnosis (CD4 count <200 cells/microL). In multivariable logistic regression analyses, older patients were more likely to be diagnosed with a CD4 count <200 cells/microL (adjusted odds ratio [AOR] 1.72, 95% confidence interval [CI], 1.12-2.64, P=.01), and older patients (AOR 1.79, 95% CI, 1.07-3.12, P=.03) and women (AOR 6.74, 95% CI, 2.08-21.81, P=0.001) were more likely to be diagnosed during hospitalization.


CONCLUSIONS
Late diagnosis of HIV infection is a considerable problem, particularly for older patients. Inpatient diagnosis of HIV infection is significantly more common among women and older patients. Improved HIV testing strategies may allow for more timely diagnosis of HIV infection, which may benefit both the infected individual and society.
Mugavero
Michael J
MJ
Division of Infectious Diseases and International Health, Department of Medicine, University of Alabama at Birmingham, USA.
Castellano
Chelsea
C
Edelman
David
D
Hicks
Charles
C
D000293:Adolescent; D000328:Adult; D017677:Age Distribution; D015331:Cohort Studies; D003430:Cross-Sectional Studies; D005260:Female; D015658:HIV Infections / Q000175:diagnosis* / Q000453:epidemiology*; D006760:Hospitalization / Q000706:statistics & numerical data; D006801:Humans; D016015:Logistic Models; D008297:Male; D008875:Middle Aged; D015999:Multivariate Analysis; D009657:North Carolina / Q000453:epidemiology; D016017:Odds Ratio; D017678:Sex Distribution