Evidence map›Paper›PMID 40208898›Full record

ArticlePloS one2025

Prevalence and factors associated with adverse drug reactions among patients on highly active antiretroviral therapy at a tertiary hospital in south western Uganda: A cross-sectional study.

Nangosya Moses, Sarad Pawar Naik Bukke, Narayana Goruntla, Daniel Chans Mwandah, Bontu Aschale Abebe, Fredrick Atwiine, Muyindike Rhoda Winnie, Tadele Mekuriya Yadesa

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In one paragraph

Article in PloS one, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 4 papers, 1 of them a synthesis that pooled it.

0numbers the graph read from it
0cells of the map it votes in
4citing papers in PubMed, 1 pooled it
–field-weighted citation impact
1 · What the graph read from it

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.

2 · The registry

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.

3 · Its place in the literature

Who cites it

4 citing papers in PubMed, 1 synthesis or guideline pooled it.

  1. Pooled it
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

8 authors.

Nangosya MosesDepartment of Pharmacy, Mbarara University of Science and Technology, Mbarara, Uganda.
Sarad Pawar Naik BukkeDepartment of Pharmaceutics and Pharmaceutical Technology, School of Pharmacy, Kampala International University, Ishaka, Uganda.
Narayana GoruntlaDepartment of Clinical Pharmacy and Pharmacy Practice, School of Pharmacy, Kampala International University, Ishaka, Uganda.
Daniel Chans MwandahDepartment of Pharmacology and Therapeutics, Mbarara University of Science and Technology, Mbarara, Uganda.
Bontu Aschale AbebeSchool of Nursing, Kampala International University, Ishaka, Uganda.
Fredrick AtwiineDepartment of Pharmacy, Mbarara University of Science and Technology, Mbarara, Uganda.ORCID 0009-0009-3257-1266
Muyindike Rhoda WinnieDepartment of Internal Medicine, Mbarara University of Science and Technology, Mbarara, Uganda.
Tadele Mekuriya YadesaDepartment of Pharmacy, Mbarara University of Science and Technology, Mbarara, Uganda.ORCID 0000-0001-5151-2610

Funding

No grant is acknowledged in the PubMed record.

6 · The paper itself

Abstract

backgroundHIV/AIDS remains a global health challenge, with significant prevalence in sub-Saharan Africa. Highly active antiretroviral therapy (HAART) is the mainstay treatment for HIV, and the number of people living with HIV (PLWHIV) on HAART has considerably increased worldwide. The use of HAART has led to improved patient outcomes; however, it is associated with adverse drug reactions (ADRs) and drug-drug interactions (DDIs), which pose serious concerns in the management of patients with HIV. The aim of the study was to determine the prevalence and factors associated with ADRs among patients on HAART. METHODOLOGY: This was a hospital-based cross-sectional study carried out among 312 HIV patients on HAART attending HIV clinics at Mbarara Regional Hospital. Data was collected using an interviewer-administered, semi-structured questionnaire and a review of patient charts. ADRs were assessed for causality and categorized using Naranjo ADR assessment scale into probable, possible and definite, for severity using the modified Hartwig and Siegel criteria into mild, moderate and Severe, and for preventability using Schumock and Thornton criteria into definite, probable and non-preventable. Lexicomp® Drug Interaction Checker software was used to identify and rate clinically significant drug-drug interactions. The prevalence of ADRs and potential DDI was analyzed using descriptive statistics while logistic regression analysis was used to establish the association of variables.

results312 patients were interviewed and their records reviewed. The prevalence of ADRs during this study was 76.0%. On assessment, 78.3% of the ADRs were mild and 76.6% of ADRs were definitely preventable. CD4 count below 200 cells/mm3 (AOR = 1.00, 95% CI: 1.00-1.02; p value = 0.04), primary education level (AOR = 3.27, 95% CI: 1.34-7.95; p value = 0.009), and secondary education level (AOR = 3.64, 95% CI: 1.39-9.52; p value = 0.009) were identified as independent risk factors. Patients who experienced a significant DDI were 5.66 times more likely to experience an ADR (p value = 0.02, 95% CI: 1.32-24.18).

conclusionThere is a high prevalence of adverse drug reactions among patients with HIV on HAART. Low CD4 count and lower education levels are risk factors for ADRs in this population; therefore, tailored interventions to these subgroups should be implemented for early ADR identification and management. Significant drug-drug interactions are highly associated with the occurrence of ADRs among HIV patients on HAART, which calls for intensified pharmacovigilance and pharmaceutical care in this population.

Indexed as

Anti-HIV AgentsAntiretroviral Therapy, Highly ActiveDrug-Related Side Effects and Adverse ReactionsHIV InfectionsAdolescentAdultCross-Sectional StudiesDrug InteractionsFemaleHumansMaleMiddle AgedPrevalenceRisk FactorsTertiary Care CentersUgandaAnti-HIV Agents

Identifiers

PMID40208898
PMCPMC11984723

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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.