Related factors to non-adherence to antiretroviral therapy in HIV/AIDS patients.
Bibliographic record
Abstract
OBJECTIVE: To identify sociodemographic, clinical, and pharmacological factors associated with nonadherence to antiretroviral treatment in patients with human immunodeficiency virus/acquired immunodeficiency syndrome treated between 2017 and 2020 in four cities in Colombia. METHOD: An observational, cross-sectional, retrospective study was conducted of a population of patients with human immunodeficiency virus/acquired immunodeficiency syndrome treated between 2017 and 2020. The Morisky-Green scale, the simplified medication adherence questionnaire, and the simplified scale to detect adherence problems to antiretroviral treatment were applied to determine patient adherence. A binomial multiple logistic regression was performed to evaluate the factors that best explain nonadherence. RESULTS: A total of 9,835 patients were evaluated, of whom 74.4% were men, 71.1% were aged between 18 and 44 years, 76.0% had attended at most secondary school, 78.1% were single, and 97.6% resided in an urban area. After applying three different scales to each patient, 10% of the study population were identified as nonadherent to treatment. The risk of nonadherence was significantly higher in patients who presented any drug- related problem or had an adverse reaction to antiretroviral drugs. CONCLUSIONS: The variables most strongly associated with nonadherence to antiretroviral treatment were drug-related problems, adverse drug reactions, a history of nonadherence to treatment, and psychoactive substance use.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
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".