Undernutrition increased the risk of loss to follow-up among adults living with HIV on ART in Northwest Ethiopia: a retrospective cohort study
Bibliographic record
Abstract
This study aims to examine the effect of undernutrition on loss to follow-up (LTFU) in adults living with human immunodeficiency virus (HIV) receiving antiretroviral therapy (ART) in Ethiopia. We conducted an institution-based retrospective cohort study using medical records of 844 adults living with HIV receiving ART between June 2014 and June 2020 at Debre Markos Comprehensive Specialized Hospital (Northwest Ethiopia). The effect of undernutrition on LTFU was examined using a proportional hazards regression model after adjusting potential confounders. The significance level was set at p < 0.05. At the end of the study period, 109 (12.9%) participants were considered LTFU, with an overall LTFU incidence of 5.3 per 100 person-years (95% CI 4.4, 6.4). The incidence of LTFU was higher in undernourished participants (8.2 per 100 person-years) compared to well-nourished participants (4.3 per 100 person-years). After adjusting for potential confounders, the adjusted risk of LTFU among undernourished participants was two times higher than in their well-nourished counterparts (AHR [adjusted hazard ratio]: 2.1, 95% CI 1.4, 3.2). This study found that undernutrition significantly increased the risk of LTFU among adults living with HIV on ART.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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 source (direct Gemma or distilled Codex), 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".