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AIDS Care ; 28(7): 913-8, 2016 07.
Article in English | MEDLINE | ID: mdl-26855169

ABSTRACT

Antiretroviral therapy (ART)-naïve patients are vulnerable to becoming lost-to-care (LTC) because they are not monitored as often as patients on treatment. We examined data from 19,461 HIV positive adults at 10 HIV clinics in Democratic Republic of Congo (DRC), Cameroon, and Burundi participating in the Phase 1 International epidemiologic Databases to Evaluate AIDS Central Africa (IeDEA-CA) study. Patients were LTC if they were ART-naïve and did not return within 7 months of the end of data collection. Logistic regression was used to obtain odds ratios (ORs) and 95% confidence intervals (CIs) for risk factors associated with LTC. Of 5353 ART-naïve patients, 4420 (83%) were LTC and 933 (17%) were in-care. The odds of being LTC were greatest among patients from DRC (OR = 2.16, CI: 1.64-2.84, p < .0001), males (OR = 1.39, CI: 1.15-1.69, p = .0009), and ages 18-49 (OR = 1.45, CI: 1.16-1.82, p = .001). The odds of being LTC were least among patients with a WHO Clinical Stage of 1 or 2 (OR = 0.65, CI: 0.55-0.77, p < .0001) and in a perceived concordant relationship (OR = 0.61, CI: 0.43-0.87, p < .0001). LTC patients were more likely to have characteristics associated with higher risk for HIV transmission and progression. Many entered care at advanced stages and were less likely to know their partner's serostatus. Greater efforts to retain ART-naïve patients may increase earlier initiation of ART.


Subject(s)
Antiretroviral Therapy, Highly Active , HIV Infections , Adult , Antiretroviral Therapy, Highly Active/methods , Antiretroviral Therapy, Highly Active/statistics & numerical data , Burundi/epidemiology , Cameroon/epidemiology , Democratic Republic of the Congo/epidemiology , Drug Monitoring/methods , Drug Monitoring/statistics & numerical data , Female , HIV Infections/drug therapy , HIV Infections/epidemiology , HIV Infections/psychology , Humans , Logistic Models , Male , Middle Aged , Patient Compliance/statistics & numerical data , Patient Dropouts/statistics & numerical data , Risk Factors
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