Associations between Depressive Symptomatology and Neurocognitive Impairment in HIV/AIDS
Bibliographic record
Abstract
OBJECTIVE: Mood disorders and neurocognitive impairments are debilitating conditions among patients with HIV/AIDS. How these comorbidities interact and their relationships to systemic factors remain uncertain. Herein, we investigated factors contributing to depressive symptomatology (DS) in a prospective cohort of patients with HIV/AIDS in active care that included neuropsychological assessment. METHODS: Among patients with HIV/AIDS receiving combination antiretroviral therapy (cART) and ongoing clinical assessments including measures of sleep, health-related quality of life (HQoL), neuropsychological testing, and mood evaluation (Patient Health Questionnaire-9 [PHQ-9]) were performed. Univariate and multivariate analyses were applied to the data. RESULTS: In 265 persons, 3 categories of DS were established: minimal (PHQ-9: 0-4; n = 146), mild (PHQ-9: 5-9; n = 62), and moderate to severe (PHQ-9: 10+; n = 57). Low education, unemployment, diabetes, reduced adherence to treatment, HIV-associated neurocognitive disorders (HAND), low health-related quality of life (HQoL), reduced sleep times, and domestic violence were associated with higher PHQ-9 scores. Motor impairment was also associated with more severe DS. In a multinomial logistic regression model, only poor HQoL and shorter sleep duration were predictive of moderate to severe depression. In this multivariate model, the diagnosis of HAND and neuropsychological performance (NPz) were not predictive of DS. CONCLUSIONS: Symptoms of depression are common (45%) in patients with HIV/AIDS and represent a substantial comorbidity associated with multiple risk factors. Our results suggest that past or present immunosuppression and HAND are not linked to DS. In contrast, sleep quality and HQoL are important variables to consider in screening for mood disturbances among patients with HIV/AIDS and distinguishing them from neurocognitive impairments.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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".