ArticleMedicine2021
Prevalence and factors associated with HIV-1 drug resistance mutations in treatment-experienced patients in Nairobi, Kenya: A cross-sectional study.
Article in Medicine, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 14 papers.
What it found
Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.
The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
The trial behind it
Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.
Who cites it
14 citing papers in PubMed, 22 citations in OpenAlex.
- Prevalence and factors associated with drug resistance mutations among HIV - 1 patients failing to achieve virological suppression on second line treatment in Tanzania.BMC infectious diseases · 2026Article
- Nationwide patterns of HIV drug resistance and high viral load in Sub-Saharan African countries.The Journal of antimicrobial chemotherapy · 2026Article
- Article
- Pre-treatment and acquired HIV drug resistance in Hunan: a cross-sectional analysis of a growing challenge.BMC infectious diseases · 2025Article
- Patterns of Reverse Transcriptase Inhibitor Resistance Mutations in People Living with Human Immunodeficiency Virus in Libreville, Gabon.Tropical medicine and infectious disease · 2025Article
- HIV drug resistance, early treatment outcomes and impact of guidelines compliance after protease inhibitor-based second-line failure in a dedicated resistance clinic in western Kenya: a retrospective cohort study.Journal of the International AIDS Society · 2025Article
- Experiences of nurses in patient adherence to antiretoroviral therapy in Mpumalanga, South Africa.African journal of primary health care & family medicine · 2025Article
- Article
- Article
- Virologic Nonsuppression and HIV Drug Resistance Among People Who Inject Drugs and Their Sexual and Injecting Partners in Kenya.AIDS research and human retroviruses · 2024Article
- Factors associated with viral load non-suppression among treatment-experienced pre-teenage children living with HIV in Kenya: a nationwide population-based cohort study, 2015-2021.EClinicalMedicine · 2024Article
- A Machine Learning Approach to Predict HIV Viral Load Hotspots in Kenya Using Real-World Data.Health data science · 2023Article
- Early warning indicators of HIV drug resistance in the southern highlands region of Tanzania: Lessons from a cross-sectional surveillance study.PLOS global public health · 2023Article
- Net charge and position 22 of the V3 loop are associated with HIV-1 tropism in recently infected female sex workers in Nairobi, Kenya.Medicine · 2022Article
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
7 authors at 2 institutions in 1 country.
Funding
Abstract
abstractAn estimated 1.5 million Kenyans are HIV-seropositive, with 1.1 million on antiretroviral therapy (ART), with the majority of them unaware of their drug resistance status. In this study, we assessed the prevalence of drug resistance to nucleoside reverse transcriptase inhibitors (NRTIs), nucleoside reverse transcriptase inhibitors (NNRTIs), and protease inhibitors, and the variables associated with drug resistance in patients failing treatment in Nairobi, Kenya.This cross-sectional study utilized 128 HIV-positive plasma samples obtained from patients enrolled for routine viral monitoring in Nairobi clinics between 2015 and 2017. The primary outcome was human immunodeficiency virus type 1 (HIV-1) drug resistance mutation counts determined by Sanger sequencing of the polymerase (pol) gene followed by interpretation using Stanford's HIV Drug Resistance Database. Poisson regression was used to determine the effects of sex, viral load, age, HIV-subtype, treatment duration, and ART-regimen on the primary outcome.HIV-1 drug resistance mutations were found in 82.3% of the subjects, with 15.3% of subjects having triple-class ART resistance and 45.2% having dual-class resistance. NRTI primary mutations M184 V/I and K65R/E/N were found in 28.8% and 8.9% of subjects respectively, while NNRTI primary mutations K103N/S, G190A, and Y181C were found in 21.0%, 14.6%, and 10.9% of subjects. We found statistically significant evidence (P = .013) that the association between treatment duration and drug resistance mutations differed by sex. An increase of one natural-log transformed viral load unit was associated with 11% increase in drug resistance mutation counts (incidence rate ratio [IRR] 1.11; 95% CI 1.06-1.16; P < .001) after adjusting for age, HIV-1 subtype, and the sex-treatment duration interaction. Subjects who had been on treatment for 31 to 60 months had 63% higher resistance mutation counts (IRR 1.63; 95% CI 1.12-2.43; P = .013) compared to the reference group (<30 months). Similarly, patients on ART for 61 to 90 months were associated with 133% higher mutation counts than the reference group (IRR 2.33; 95% CI 1.59-3.49; P < .001). HIV-1 subtype, age, or ART-regimen were not associated with resistance mutation counts.Drug resistance mutations were found in alarmingly high numbers, and they were associated with viral load and treatment time. This finding emphasizes the importance of targeted resistance monitoring as a tool for addressing the problem.
Indexed as
Identifiers
What OpenQuestion holds
Registered trials
Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.