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Record W2772137009 · doi:10.1111/tmi.13026

Factors for incomplete adherence to antiretroviral therapy including drug refill and clinic visits among older adults living with human immunodeficiency virus – cross‐sectional study in South Africa

2017· article· en· W2772137009 on OpenAlexaff
Abbie Barry, Nathan Ford, Ziad El‐Khatib

Bibliographic record

VenueTropical Medicine & International Health · 2017
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsMedicineCross-sectional studyAntiretroviral therapyHuman immunodeficiency virus (HIV)SidaVirologyViral diseasePediatricsViral load

Abstract

fetched live from OpenAlex

OBJECTIVES: To assess adherence outcomes to antiretroviral therapy (ART) of recipients ≥50 years in Soweto, South Africa. METHODS: This was a secondary data analysis for a cross-sectional study at two HIV clinics in Soweto. Data on ART adherence and covariates were gathered through structured interviews with HIV 878 persons living with HIV (PLHIV) receiving ART. Logistic regression analysis was used to assess associations. RESULTS: PLHIV ≥50 years (n = 103) were more likely to miss clinic visits during the last six months than PLHIV aged 25-49 (OR 2.15; 95%CI 1.10-4.18). PLHIV ≥50 years with no or primary-level education were less likely to have missed a clinic visit during the last six months than PLHIV with secondary- or tertiary-level education in the same age category (OR 0.3; 95%CI 0.1-1.1), as were PLHIV who did not disclose their status (OR 0.2; 95%CI 0-1.1). There was no evidence of increased risk for non-adherence to ART pills and drug refill visits among older PLHIV. CONCLUSION: Missing a clinic visit was more common among older PLHIV who were more financially vulnerable. Further studies are needed to verify these findings and identify new risk factors associated with ART adherence.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.013
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.135
GPT teacher head0.463
Teacher spread0.328 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations12
Published2017
Admission routes1
Has abstractyes

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