Changes in neurocognitive assessment scores after initiating dolutegravir- versus elvitegravir-based antiretroviral therapy
Bibliographic record
Abstract
This prospective cohort study enrolled people living with HIV initiating antiretroviral therapy (ART) containing the integrase inhibitors, dolutegravir (DTG) or elvitegravir (EVG) and administered the Montreal Cognitive Assessment (MoCA) at baseline and again after approximately six months to compare changes in MoCA scores. The proportion of patients found to have cognitive impairment, as indicated by a MoCA score <26/30, on each agent were also compared and comparisons were made between changes in each domain assessed by the MoCA (visuospatial/executive, naming, attention, language, abstraction, delayed recall, and orientation). Thirty-five evaluable participants were enrolled, 18 on DTG and 17 on EVG. The median [interquartile range(IQR)] age was 44 (32 to 54) years, 63% were male, 57% were African American. The median (IQR) MoCA score at baseline was 25 (23 to 27) with no difference between groups (p=0.249). The median (IQR) change in MoCA score was 0 (−1 to 2) for DTG and 1 (0 to 3) for EVG (p = 0.183). Of those on DTG, 8 (44%) had MoCA scores <26 on follow-up compared to 11 (65%) on EVG (p = 0.229). There were no significant differences in changes in any of the individual MoCA domains.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.001 | 0.001 |
| 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".