Rate and predictors of HIV virological failure among adults on first-line antiretroviral treatment in Dar Es Salaam, Tanzania

Abstract

Introduction: Monitoring resistance to first line Antiretroviral therapy (ART) is crucial in preventing accumulation of viral mutations following the implementation of the World Health Organization “treat all” initiative. We estimated the rate and predictors of virological treatment failure among adults living with HIV/AIDS in Dar es Salaam, Tanzania.
 Methodology: A retrospective cohort study involving adults aged 18 and above receiving first line ART in Dar as Salaam between 2016 and 2018 were recruited using multistage random sampling. Clinical and laboratory data were extracted from Care and Treatment Clinic database-2 (CTC2) followed by participant’s interviews. Adjusted Cox-regression modelling was used to determine independent predictors of treatment failure.
 Results: A total of 340 participants with mean age of 37 were recruited. Overall, 10.59% had virological failure and the rate of failure was 5.24 (95% CI:3.72; 7.27) per 100 person-months at risk with a median failure time of 18 months. Independent predictors of treatment failure were being a male (Adjusted hazard ratio (aHR) 2.78, 95%CI:1.16;6.63), having used treatment for less than two years (aHR, 12.48, 95%CI:3.64-22.71) and co-infection with Tuberculosis (aHR 2.1, 95%CI: 1.0;5.9).
 Conclusions: HIV virological failure occurs early during treatment in this population. Male clients, co-infected with Tuberculosis were at higher risk of ART failure within two years of treatment. Substantial stride has been made towards the achievement of the last UNAIDS 90 goal but tailored counseling and close monitoring of HIV/TB co-infected male clients following ART initiation could accelerate efforts to close the gap. Further studies on pre-treatment drug resistance mutations are called for.

Machine learning to predict virological failure among HIV patients on antiretroviral therapy in the University of Gondar Comprehensive and Specialized Hospital, in Amhara Region, Ethiopia, 2022

“…Accordingly, male HIV patients were more likely to develop virological failure as compared to females. This study is in line with the research studies conducted in Kumasi, Ghana [ 26 ], Morocco [ 79 ], Dar Es Salaam, Tanzania [ 36 ], and the Tigray region, Ethiopia [ 80 ] that stated that virological failure was more common in male HIV patients than female HIV patients. The possible reasons might be excessive alcohol consumption, low clinic attendance for ART, and low health-seeking behavior in male patients [ 31 , 36 , 80 ].…”

“…Furthermore, in Ethiopia, studies reported that virologic failure rates ranged from 5.4 to 19% [ 30 – 32 ]. Several studies have found that socio-demographic predictors (age, gender, marital status, religion), clinical-related predictors (low BMI, TB co-infection), and treatment-related predictors (excessive dose frequency, poor medication adherence) can all influence virological failure in HIV patients [ 30 , 33 – 36 ]. However, the predictors of virological failure varied between studies.…”

Determinants of Virologic Failure Among Adult Hiv Patients on First Line Atiretroviral Treatment at Oromia, Central Ethiopia: 2022 a Case –control Study

“…20 Similarly, this result is comparable with study conducted at Dar Es salaam Tanzania, which revealed HIV positive on rst line ART, Clients who have history of TB co-infection had odds of 2.1 to develop virologic failure compared to clients with no history of TB co-infection. 27 This may be due to the fact that, like HIV, TB infection also attacks white blood cells which lead to synergistic effect with HIV to minimize CD4 count and facilitate for HIV replication which leads to HIV virologic failure.…”

Innovative, rapid, high-throughput method for drug repurposing in a pandemic –a case study of SARS-CoV-2 and COVID-19

“…Drugs with multiple sites of activity are essentially ‘combination therapies’ and therefore may be expected to show a high threshold for viruses to develop resistance. For example, although the rate of resistant mutation is unknown with SARS-CoV-2, it is estimated as 1 in 10 6 for HIV-1 virus 24–26 . This suggests that a three-drug combination with different sites of action will acquire 1 in 10 18 resistant viruses: a number much higher than the possible viral loads in the body.…”