Predictors of depression recovery in HIV-infected individuals managed through measurement-based care in infectious disease clinics
Section snippets
Background
The number of pepole living with HIV/AIDS (PLWHA) has grown rapidly over the past decade, largely due to increased access to and effectiveness of antiretroviral therapies (ART) (UNAIDS, 2012). As a result, life expectancies have increased and the burden of opportunistic infections has decreased (Bor et al., 2013, Jahn et al., 2008, Mills et al., 2011). An unforeseen and unwelcome consequence of these results is that the number of PLWHA who develop noncommunicable diseases has increased (Mocroft
Methods
Data for the present analysis come from a randomized controlled trial to evaluate the effectiveness of evidence-based antidepressant management integrated into HIV care in improving antiretroviral adherence (the SLAM DUNC Study), described in detail elsewhere (Pence et al., 2012). Briefly, HIV-infected patients receiving medical care at one of four U.S. infectious diseases clinics were eligible to participate if they were English-speaking, ages 18–65, screened positive for depression (score≥10)
Demographic characteristics of the study population
The demographic and clinical variables at baseline in the study population are shown in Table 1. Our population was predominantly male and most individuals were on ART. Almost 27% of patients on ART were non-adherent at baseline. The majority of patients had a viral load that was suppressed at baseline, but 31% did not. In terms of comorbidities, depression alone was present in 28% of patients, 40% had comorbid depression and anxiety, 13% had comorbid depression and substance abuse, and 19% had
Discussion
Our study shows predictors of outcomes for HIV-infected individuals with depression enrolled in a MBC protocol from typical infectious disease clinics. As summarized in Fig. 1, several factors negatively affected recovery from depression in response to our intervention. We note that our study is an exploratory analysis and may not have been powered to determine predictors of recovery with clear statistical significance. However, we were still able to identify some predictors which had HRs with
Funding/support
This work was supported by grant R01MH086362 of the National Institute of Mental Health and the National Institute for Nursing Research, National Institutes of Health, Bethesda, MD, USA. Support for the design and conduct of the study was also provided by the NIH-funded Centers for AIDS Research at the University of North Carolina at Chapel Hill, Duke University, and the University of Alabama at Birmingham (P30- AI50410, P30-AI064518, and P30-AI027767). BNG is supported by NC TRACS Institute,
Role of the sponsors
None of the financial sponsors were directly responsible for the design, conduct or reporting of the study.
Author contributions
NAS participated in review of data for analysis and wrote, edited, and submitted the manuscript. AB conducted all data analyses and reviewed and edited the manuscript. BNG and BWP were involved in the design and execution of the original SLAMDUNC study, as well as in the design of data analyses and manuscript review.
Acknowledgments
We gratefully acknowledge the contributions of the SLAM DUNC study staff, providers, and participants. We also would like to acknowledge the contributions of Julie O’Donnell PhD, who provided additional data analysis support for this manuscript.
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