Predictors of symptomatic <scp>HIV</scp>‐associated neurocognitive disorders in universal health care
Bibliographic record
Abstract
OBJECTIVES: The aim of the study was to determine the risk factors predictive of symptomatic HIV-associated neurocognitive disorders (sHAND) among HIV-infected patients receiving active medical care. METHODS: Baseline demographic and clinical characteristics were analysed in patients with sHAND (HIV-associated dementia and minor neurocognitive disorder) in a population-based longitudinal cohort of HIV-infected patients with access to universal health care, including combination antiretroviral therapy (cART) from 1999 to 2008. Variables evaluated for their association with sHAND included age and ethnicity, survival duration with HIV-1 infection, vascular disease risk factors, and laboratory indices such as blood CD4 T-cell count at its nadir and at cART initiation, using both univariable and multivariable logistic regression models. RESULTS: A total of 1320 patients were investigated, including the patients diagnosed with sHAND (n = 90) during the study period. In univariable analyses, increased age, increased length of survival with HIV, low nadir CD4 and CD8 T-cell counts, high baseline viral load (> 1,000,000 HIV-1 RNA copies/mL), and African origin were predictive of a diagnosis of sHAND (P < 0.05). In multivariable analysis, increased age, increased length of survival, low nadir CD4 T-cell counts, and high baseline viral load remained predictive of sHAND (P < 0.05). Remarkably, CD4 T-cell counts at cART initiation, hepatitis C virus coinfection, and vascular disease risk factors failed to predict sHAND in both analyses. CONCLUSIONS: Increased age and survival duration, lower nadir CD4 T-cell counts, and higher baseline viral load were consistent predictors of the development of sHAND among persons with HIV/AIDS in universal health care, underscoring the importance of attention to these variables in clinical care.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| 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".