Predictors of mortality within the first year of initiating antiretroviral therapy in urban and rural Kenya: A prospective cohort study

Abstract

IntroductionDespite increased treatment availability, HIV-infected individuals continue to start antiretroviral therapy (ART) late in disease progression, increasing early mortality risk.Materials and methodsNested prospective cohort study within a randomized clinical trial of adult patients initiating ART at clinics in urban Nairobi and rural Maseno, Kenya, between 2013–2014. We estimated mortality incidence rates following ART initiation and used Cox proportional hazards regression to identify predictors of mortality within 12 months of ART initiation. Analyses were stratified by clinic site to examine differences in mortality correlates and risk by location.ResultsAmong 811 participants initiated on ART, the mortality incidence rate within a year of initiating ART was 7.44 per 100 person-years (95% CI 5.71, 9.69). Among 207 Maseno and 612 Nairobi participants initiated on ART, the mortality incidence rates (per 100 person-years) were 12.78 (95% CI 8.49, 19.23) and 5.72 (95% CI 4.05, 8.09). Maseno had a 2.20-fold greater risk of mortality than Nairobi (95% CI 1.29, 3.76; P = 0.004). This association remained [adjusted hazard ratio (HR) = 2.09 (95% CI 1.17, 3.74); P = 0.013] when adjusting for age, gender, education, pre-treatment drug resistance (PDR), and CD4 count, but not when adjusting for BMI. In unadjusted analyses, other predictors (P<0.05) of mortality included male gender (HR = 1.74), age (HR = 1.04 for 1-year increase), fewer years of education (HR = 0.92 for 1-year increase), unemployment (HR = 1.89), low body mass index (BMI<18.5 m/kg2; HR = 4.99), CD4 count <100 (HR = 11.67) and 100–199 (HR = 3.40) vs. 200–350 cells/μL, and pre-treatment drug resistance (PDR; HR = 2.49). The increased mortality risk associated with older age, males, and greater education remained when adjusted for location, age, education and PDR, but not when adjusted for BMI and CD4 count. PDR remained associated with increased mortality risk when adjusted for location, age, gender, education, and BMI, but not when adjusted for CD4 count. CD4 and BMI associations with increased mortality risk persisted in multivariable analyses. Despite similar baseline CD4 counts across locations, mortality risk associated with low CD4 count, low BMI, and PDR was greater in Maseno than Nairobi in stratified analyses.ConclusionsHigh short-term post-ART mortality was observed, partially due to low CD4 count and BMI at presentation, especially in the rural setting. Male gender, older age, and markers of lower socioeconomic status were also associated with greater mortality risk. Engaging patients earlier in HIV infection remains critical. PDR may influence short-term mortality and further studies to optimize management will be important in settings with increasing PDR.

Decrease in late presentation for HIV care in Kinshasa, DRC, 2006–2020

“…The implementation of the WHO and national guidelines led to a significant decrease in time from diagnosis to treatment initiation, as shown in multiple studies in Sub-Saharan Africa [5][6][7]. Although this observation shows the success of the treat all strategy implementation, it should not mask the fact that many other hurdles remain to reach better ART coverage.…”

Incidence and predictors of mortality within the first year of antiretroviral therapy initiation at Debre-Markos Referral Hospital, Northwest Ethiopia: A retrospective follow up study

“…But HIV-infected individuals, especially in Africa including Ethiopia, still hesitates to start the treatment early which results in progression of the disease to the advanced stage. This intern results in risk of early mortality for patients with HIV [ 3 – 5 ].…”

Development and validation of a prognostic nomogram for predicting the survival of HIV/AIDS adults who received antiviral treatment: a cohort between 2003 and 2019 in Nanjing

“…Some clinical indicators (such as WHO clinical stage) with close association with PLHIV survival rate [13] were not included in the nomogram because the laboratory indicators (such as CD4) were more sensitive in predicting survival rate of PLHIV than the clinical indicators. In recent years, many researchers have reported that some laboratory indicators are connected with the survival rate of PLHIV.…”

“…Studies have shown that CD4 + T lymphocytes (CD4), CD8 + T lymphocytes (CD8), and viral load (HIV RNA) before treatment are closely associated with the mortality of PLHIV [5][6][7][8][9][10][11][12][13] . Clinical indicators are reported to have a close association with death risk of PLHIV [5,7−16] .…”