Time to lost to follow-up and its predictors among adult patients receiving antiretroviral therapy retrospective follow-up study Amhara Northwest Ethiopia
Bibliographic record
Abstract
Antiretroviral therapy lowers viral load only when people living with HIV maintain their treatment retention. Lost to follow-up is the persistent major challenge to the success of ART program in low-resource settings including Ethiopia. The purpose of this study is to estimate time to lost to follow-up and its predictors in antiretroviral therapies amongst adult patients. Among registered HIV patients, 542 samples were included. Data cleaning and analysis were done using Stata/SE version 14 software. In multivariable Cox regression, a p-value < 0.05 at 95% confidence interval with corresponding adjusted hazards ratio (AHR) were statistically significant predictors. In this study, the median time to lost to follow-up is 77 months. The incidence density of lost to follow-up was 13.45 (95% CI: 11.78, 15.34) per 100 person-years. Antiretroviral therapy drug adherence [AHR: 3.04 (95% CI: 2.18, 4.24)], last functional status [AHR: 2.74 (95% CI: 2.04, 3.67)], and INH prophylaxis [AHR: 1.65 (95% CI: 1.07, 2.56) were significant predictors for time to lost to follow-up. The median time to lost was 77 months and incidence of lost to follow-up was high. Health care providers should be focused on HIV counseling and proper case management focused on identified risks.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".