Mortality Among HIV-Infected Adults on Antiretroviral Therapy in Southern Uganda

Abstract

Background: Monitoring and evaluation of clinical programs requires assessing patient outcomes. Numerous challenges complicate these efforts, the most insidious of which is loss to follow-up (LTFU). LTFU is a composite outcome, including individuals out of care, undocumented transfers, and unreported deaths. Incorporation of vital status information from routine patient outreach may improve the mortality estimates for those LTFU.

Settings: We analyzed routinely collected clinical and patient tracing data for individuals (15 years or older) initiating antiretroviral treatment between January 2014 and December 2018 at 2 public HIV care clinics in greater Rakai, Uganda.

Methods: We derived unadjusted mortality estimates using Kaplan-Meier methods. Estimates, adjusted for unreported deaths, applied weighting through the Frangakis and Rubin method to represent outcomes among LTFU patients who were successfully traced and for whom vital status was ascertained. Confidence intervals were determined through bootstrap methods.

Results: Of 1969 patients with median age at antiretroviral treatment initiation of 31 years (interquartile range: 25-38), 1126 (57.2%) were female patients and 808 (41%) were lost. Of the lost patients, 640 patient files (79.2%) were found and reviewed, of which 204 (31.8%) had a tracing attempt. Within the electronic health records of the program, 28 deaths were identified with an estimated unadjusted mortality 1 year after antiretroviral treatment initiation of 2.5% (95% CI: 1.8% to 3.3%). Using chart review and patient tracing data, an additional 24 deaths (total 52) were discovered with an adjusted 1-year mortality of 3.8% (95% CI: 2.6% to 5.0%).

Conclusions: Data from routine outreach efforts by HIV care and treatment programs can be used to support plausible adjustments to estimates of client mortality. Mortality estimates without active ascertainment of vital status of LTFU patients may significantly underestimate program mortality.