&lt;p&gt;Prevalence and Predictors of Virological Failure Among Adults Living with HIV in South Wollo Zone, Northeast Ethiopia: A Retrospective Cohort Study&lt;/p&gt;

Wendie, Teklehaimanot Fentie; Workneh, Birhanu Demeke

doi:10.2147/hiv.s266460

Cited by 11 publications

(12 citation statements)

References 42 publications

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“…This finding was different from studies done in Kombolcha town and South Wollo Zone Ethiopia, where they reported that being divorced or separated had increased risk of virological failure. 36,37 The possible reason for this discrepancy is that in their study, single was kept constant during analysis. Again, we found that a unit decrease in age increases the risk of virological failure after IAC among PLHIV, while a unit increase in age decreases the risk.…”

Section: Discussionmentioning

confidence: 92%

Failure to Attain HIV Viral Suppression After Intensified Adherence Counselling—What Can We Learn About Its Factors?

Mundamshimu¹,

Malale²,

Kidenya³

et al. 2023

IDR

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Background Introduction and expansion of antiretroviral therapy (ART) have turned the tide of HIV pandemic, thus helping people living with HIV (PLHIV) achieve viral suppression. This success may need to be complemented by intensified adherence counseling (IAC) to improve adherence to treatment. However, some PLHIV still face higher than acceptable viral loads despite being on treatment. Purpose We investigated the factors associated with the failure to suppress HIV viral load after three months of IAC sessions. Patients and Methods This cross-sectional study analyzed secondary data from PLHIV-attended care and treatment clinics in Mwanza between January 2018 and December 2019 who had unsuppressed VL after being on ART for at least six months. We identified PLHIV in first-line ART with viral load evaluation before receiving IAC and had viral load results done at 90 days after IAC. We conducted descriptive statistics to examine the magnitude of viral suppression. Wilcoxon signed-rank test used to compare the median viral load before and after IAC sessions, and logistic regressions predicted the factors associated with failure. Results This study included 212 subjects. After intervention, most participants 85.9% (182) had significantly improved adherence compared to baseline. More than half 75.5% (160) of the participants had viral suppression after the intervention. Participants aged 18–25 years (AOR = 5.6, 95% CI, 1.1–29.6), unstable client during ART initiation (AOR = 0.3, 95% CI, 0.13–0.62), and poor adherence to ART (AOR = 4, 95% CI, 1.3–12.3) remained the main predictors of virological failure after IAC intervention. Conclusion Even though virological suppression is influenced by ART adherence, the findings in this study have shown co-existence of other factors to be addressed. Unstable during ART initiation is a new factor identified in this study.

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Section: Discussionmentioning

confidence: 92%

Failure to Attain HIV Viral Suppression After Intensified Adherence Counselling—What Can We Learn About Its Factors?

Mundamshimu¹,

Malale²,

Kidenya³

et al. 2023

IDR

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“…For the meta‐analysis, 47 studies reported data on knowledge of positive serostatus [39,41,44,52–55,58,59,63–65,69,73,77,79–81,83,84,86,91,94,95,97,99,101,102,108,110–113,144,146,149,151,154,157,167,171,178,185,186,188,189], 43 studies reported data on ART use [35,36,39,47,51,55,60,62,67,70,83–85,95,97–99,104,105,107,108,112,142,144–146,148–150,154,161,162,166–168,170,171,181,184–186,188,189] and 74 studies reported data on viral suppression (Table 1 and Table A2) [33,34,37,38,40–43,45,46,48–50,55–57,61,66,68,71,72,74–76,78,82,84,87–90,92,93,95–97,100,103,106–109,143,146,147,149,152–156,158–161,163–165,169,171–177,179,180,182,183,...…”

Section: Resultsmentioning

confidence: 99%

“…Of these, 81 studies were included in the meta‐analysis [33–113] and 29 studies were included in the meta‐synthesis [105,114–141]. Our updated searches identified 48 additional studies for the meta‐analysis [142–189] and 11 additional studies for the meta‐synthesis [190–200], most published in 2020.…”

Section: Resultsmentioning

confidence: 99%

Men missing from the HIV care continuum in sub‐Saharan Africa: a meta‐analysis and meta‐synthesis

et al. 2022

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Introduction:Men are missing along the HIV care continuum. However, the estimated proportions of men in sub-Saharan Africa meeting the UNAIDS 95-95-95 goals vary substantially between studies. We sought to estimate proportions of men meeting each of the 95-95-95 goals across studies in sub-Saharan Africa, describe heterogeneity, and summarize qualitative evidence on factors influencing care engagement. Methods: We systematically searched PubMed and Embase for peer-reviewed articles published between 1 January 2014 and 16 October 2020. We included studies involving men ≥15 years old, with data from 2009 onward, reporting on at least one 95-95-95 goal in sub-Saharan Africa. We estimated pooled proportions of men meeting these goals using DerSimonion-Laird random effects models, stratifying by study population (e.g. studies focusing exclusively on men who have sex with men vs. studies that did not), facility setting (healthcare vs. community site), region (eastern/southern Africa vs. western/central Africa), outcome measurement (e.g. threshold for viral load suppression), median year of data collection (before vs. during or after 2017) and quality criteria. Data from qualitative studies exploring barriers to men's HIV care engagement were summarized using meta-synthesis. Results and discussion: We screened 14,896 studies and included 129 studies in the meta-analysis, compiling data over the data collection period. Forty-seven studies reported data on knowledge of serostatus, 43 studies reported on antiretroviral therapy use and 74 studies reported on viral suppression. Approximately half of men with HIV reported not knowing their status (0.49 [95% CI, 0.41-0.58; range, 0.09-0.97]) or not being on treatment (0.58 [95% CI, 0.51-0.65; range, 0.07-0.97]), while over three-quarters of men achieved viral suppression on treatment (0.79 [95% CI, 0.77-0.81; range, 0.39-0.97]. Heterogeneity was high, with variation in estimates across study populations, settings and outcomes. The meta-synthesis of 40 studies identified three primary domains in which men described risks associated with engagement in HIV care: perceived social norms, health system challenges and poverty. Conclusions: Psychosocial and systems-level interventions that change men's perceptions of social norms, improve trust in and accessibility of the health system, and address costs of accessing care are needed to better engage men, especially in HIV testing and treatment.

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“…According to recent research conducted in Sub-Saharan Africa, the proportion of individuals who experienced virological failure ranged from 11 to 47% [ 26 – 29 ]. 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 ].…”

Section: Introductionmentioning

confidence: 99%

“…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.…”

Section: Introductionmentioning

confidence: 99%

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

Mamo

Yilma

Fekadie

et al. 2023

BMC Med Inform Decis Mak

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Background Treatment with effective antiretroviral therapy (ART) reduces viral load as well as HIV-related morbidity and mortality in HIV-positive patients. Despite the expanded availability of antiretroviral therapy around the world, virological failure remains a serious problem for HIV-positive patients. Thus, Machine learning predictive algorithms have the potential to improve the quality of care and predict the needs of HIV patients by analyzing huge amounts of data, and enhancing prediction capabilities. This study used different machine learning classification algorithms to predict the features that cause virological failure in HIV-positive patients. Method An institution-based secondary data was used to conduct patients who were on antiretroviral therapy at the University of Gondar Comprehensive and Specialized Hospital from January 2020 to May 2022. Patients’ data were extracted from the electronic database using a structured checklist and imported into Python version three software for data pre-processing and analysis. Then, seven supervised classification machine-learning algorithms for model development were trained. The performances of the predictive models were evaluated using accuracy, sensitivity, specificity, precision, f1-score, and AUC. Association rule mining was used to generate the best rule for the association between independent features and the target feature. Result Out of 5264 study participants, 1893 (35.06%) males and 3371 (64.04%) females were included. The random forest classifier (sensitivity = 1.00, precision = 0.987, f1-score = 0.993, AUC = 0.9989) outperformed in predicting virological failure among all selected classifiers. Random forest feature importance and association rules identified the top eight predictors (Male, younger age, longer duration on ART, not taking CPT, not taking TPT, secondary educational status, TDF-3TC-EFV, and low CD4 counts) of virological failure based on the importance ranking, and the CD-4 count was recognized as the most important predictor feature. Conclusion The random forest classifier outperformed in predicting and identifying the relevant predictors of virological failure. The results of this study could be very helpful to health professionals in determining the optimal virological outcome.

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<p>Prevalence and Predictors of Virological Failure Among Adults Living with HIV in South Wollo Zone, Northeast Ethiopia: A Retrospective Cohort Study</p>

Cited by 11 publications

References 42 publications

Failure to Attain HIV Viral Suppression After Intensified Adherence Counselling—What Can We Learn About Its Factors?

Failure to Attain HIV Viral Suppression After Intensified Adherence Counselling—What Can We Learn About Its Factors?

Men missing from the HIV care continuum in sub‐Saharan Africa: a meta‐analysis and meta‐synthesis

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

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