Risk Factors for HIV-Associated Neurocognitive Disorders (HAND) in a Canadian Cohort (P1.321)
Bibliographic record
Abstract
Objective: To determine predictors of HIV-associated neurocognitive disorders (HAND) in a Canadian cohort. Background: Cross-sectional cohort studies have identified multiple risk factors for the development of HIV-associated neurocognitive disorders (HAND). The extent to which these factors contribute to HAND across populations is unclear, particularly in the setting of accessible health care and antiretroviral therapy (ART). Methods: HIV-1 seropositive patients were randomly enrolled in a single-site, prospective cohort study with the diagnosis of HAND as the primary outcome measure. Clinical, neuroimaging and demographic features were interrogated together with the application of a multi-domain neuropsychological battery in all patients. In addition to univariate statistics, principal component analyses (PCA) were used to reduce the number of correlated risk factors into components encompassing patient characteristics. PCA components were used to predict HAND versus non-HAND status in hierarchical logistic regressions. Results: HAND was diagnosed in 63 patients (26[percnt]) and was associated with ethnicity, education, QoL, peak viral load, HIV risk factor, employment status, CPE score, ART adherence, polypharmacy and diabetes compared to non-HAND patients (p<0.05). PCA summarized patient characteristics into eight independent components, explaining 68.62[percnt] of variance across characteristics. Controlling for components composed of demographic or psychosocial variables (ethnicity, birth country, depression, QoL, education and IQ), a logistic regression determined (90.25[percnt] correct HAND diagnosis) that patients with current and nadir CD4+ counts outside the AIDS-defined range were less likely to have HAND compared to patients with AIDS and lower CD4+ counts (OR = 0.51). Older patients with diabetes and cardiovascular disease were more likely to exhibit HAND compared to younger patients without these co-morbidities (OR = 1.91). Conclusions: Controlling for neurocognitively relevant demographic/psychosocial factors, we ascertained the importance of host factors for HAND in this cohort. These findings emphasize that diabetes and cardiovascular disease, especially in older patients, are emerging and reliable predictors of HAND.
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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 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".