Cognitive impairment among HIV-infected adults on antiretroviral therapy in Indonesia
Bibliographic record
Abstract
Introduction: Human immunodeficiency virus (HIV) infection and its related complications remain a health problem in developing countries.Cognitive impairment is a complication of HIV infection and is often undetected.Untreated cognitive impairment can lead to decreased quality of life.This study aimed to determine the prevalence of cognitive impairment among HIV-infected patients and its associated risk factors. Material and methods:A cross-sectional study was conducted at Wahidin Sudirohusodo Hospital Makassar Indonesia, from October to December 2020.It involved 93 HIV outpatients aged 18-59 years.Cognitive impairment was determined by the Montreal cognitive assessment (MoCA) test.Blood samples were taken for CD4, anti-HCV, and routine blood tests.Nadir (lowest ever) CD4 and antiretroviral therapy (ART) information were obtained from patient medical records.Data were analysed using SPSS version 22.The statistical tests used were the chi-square test and multiple logistic regression.Results: Cognitive impairment was found in 47.3% of subjects.Bivariate analysis found a significant relationship between age 41-59 years (p = 0.025), nadir CD4 count < 200 cells/μl (p = 0.001), and anaemia (p = 0.04) with cognitive impairment.Multivariate analysis showed that the most significant factors associated with cognitive impairment were nadir CD4 count < 200 cells/μl (OR 4.4; 95% CI: 1.75-11.17)and age 41-59 years (OR 3.0; 95% CI: 1.01-8.73). Conclusions:The prevalence of cognitive impairment was found to be high in HIV-infected adults receiving ART.Low nadir CD4 count (40 years old) was identified as a risk factor associated with impaired cognitive function.
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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 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".