Cognitive Assessment of Young Adults Before and After Initiation of Combination Antiretroviral Therapy
Bibliographic record
Abstract
Objective: In the determination and monitoring of neurocognitive disorders in human immunodeficiency virus (HIV)-positive individuals, there is a need for significantly more practical methods which provide results in a shorter time than the tests that require challenging and specialized expertise. This study aimed to evaluate cognitive functions and the factors affecting them in naïve HIV-positive patients using by Montreal Cognitive Assessment (MoCA) test before and after the initiation of combination antiretroviral therapy. Materials and Methods: HIV-positive, treatment-naïve patients monitored between January-June 2017 were included in the study. The MoCA test was performed at the beginning and the sixth month of the treatment. Results: Forty male patients were included in the study. The mean age was calculated as 29.1±4.0. When the factors affecting the MoCA score were examined, there was a significant relationship between the education level and the MoCA score. Smoking, using alcohol, and substance did not have a significant impact on baseline MoCA values. A significant correlation was found between cluster differentiation 4 (CD4) count and HIV RNA level and attention function. There was a significant increase in the total MoCA score and the MoCA subgroup scores at the end of the sixth month of the treatment. Conclusion: MoCA test is one of the most practical tests that can be applied in a short time period, and it was found useful in evaluating the changes in the cognitive functions of HIV-positive patients during antiretroviral treatment.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| 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".