Prevalence and type of drug-drug interactions involving ART in patients attending a specialist HIV outpatient clinic in Kampala, Uganda.
J Antimicrob Chemother 2015;
70:3317-22. [PMID:
26286575 PMCID:
PMC4652684 DOI:
10.1093/jac/dkv259]
[Citation(s) in RCA: 10] [Impact Index Per Article: 1.1] [Reference Citation Analysis] [Abstract] [Track Full Text] [Download PDF] [Figures] [Journal Information] [Subscribe] [Scholar Register] [Received: 03/12/2015] [Accepted: 07/28/2015] [Indexed: 11/30/2022] Open
Abstract
Objectives
Scale-up of HIV services in sub-Saharan Africa has rapidly increased, necessitating evaluation of medication safety in these settings. Drug–drug interactions (DDIs) involving antiretrovirals (ARVs) in sub-Saharan Africa are poorly characterized. We evaluated the prevalence and type of ARV DDIs in Ugandan outpatients and identified the patients most at risk.
Methods
A total of 2000 consecutive patients receiving ARVs at the Infectious Diseases Institute, Kampala were studied. The most recent prescription for each patient was screened for clinically significant DDIs using www.hiv-druginteractions.org. Univariable and multivariable logistic regression were used to identify risk factors for DDIs. A screening tool was developed using significant risk factors and tested in a further 500 patients.
Results
Clinically significant DDIs were observed in 374 (18.7%) patients, with a total of 514 DDIs observed. Only 0.2% of DDIs involved a contraindicated combination. Comedications commonly associated with DDIs were antibiotics (4.8% of 2000 patients), anthelmintics (2.2%) and antifungals (3.5%). Patient age, gender, CD4 count and weight did not affect risk of DDIs. In multivariable analysis, the patient factors that independently increased risk of DDIs were two or more comedications (P < 0.0001), a PI-containing ARV regimen (P < 0.0001), use of an anti-infective (P < 0.0001) and WHO clinical stage 3–4 (P = 0.04). A scoring system based on having at least two of these risk factors identified between 75% and 90% of DDIs in a validation cohort.
Conclusions
Significant ARV DDIs occur at similar rates in resource-limited settings and developed countries; however, the comedications frequently causing DDIs differ. Development of tools that are relevant to particular settings should be a priority to assist with prevention and management of DDIs.
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