Neurocognitive Impairment in Patients with HIV and Depression in Nigeria
Bibliographic record
Abstract
HIV has been associated with neurocognitive impairment which may be due to the direct effect of the virus, indirect effect or due to medications side effects or due to a combination of factors. HIV and depression have been shown separately to have neurocognitive deficits. Aim: Determine the prevalence of NCI and factors associated with it among depressed and non-depressed patients with HIV on combined antiretroviral treatment (cART). Methodology. A descriptive comparative cross-sectional study was conducted among People living with HIV (PLHIV) at Aminu Kano Teaching Hospital in Kano State, northern Nigeria. Participants were grouped into HIV with depression and HIV without depression groups based on current diagnosis using the depression module of the MINI International Neuropsychiatric Interview (MINI)-7th edition. A multi-domain neuropsychological battery (MDNPT) of 5 tests (assessed 5 cognitive domains) was used to diagnose Neurocognitive impairment. Results: Fifty-seven percent of the study sample were females, and the mean age of the participants was 37.54 (±10.04) years with an age range of 18-65 years. The prevalence of NCI was 74% among the depressed 68.3% among the non-depressed group (p=0.484). Years of education and IHDS score were significantly associated with NCI in the depressed group (p < 0.05 respectively). While among the non-depressed group, Years of education, average monthly income and IHDS score were significantly associated with NCI (p < 0.05 respectively). Conclusion: Neurocognitive impairment occurs in HIV-positive patients but is worsened by a depressive disorder. There is a need to adequately assess and treat HIV patients with depression. Treatment may improve neurocognitive impairment in depressed HIV patients.
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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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 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".