Bibliographic record
Abstract
Over 60,000 Canadians are infected with human immunodeficiency virus (HIV). Greater than 50% of these individuals will develop a neurological disorder despite the availability of highly active antiretroviral therapy. HIV causes nervous system disease at all stages of infection with adverse effects on quality of life, adherence to medications, employment and survival. These disorders include opportunistic infections in addition to distinct HIV-associated neurological syndromes and undesirable treatment-related effects. The latter two groups of disorders are often undiagnosed and untreated in both adolescents and adults. Direct HIV infection of central nervous system causes HIV-associated dementia, which is a progressive subcortical dementia. HIV infection of the peripheral nervous system produces a painful sensory neuropathy termed distal sensory polyneuropathy, which may be exacerbated by several antiretroviral drugs. Other important HIV-induced neurological disorders include vacuolar myelopathy and an increased risk of seizures. Future issues that will confound the presentation and treatment of HIV-induced nervous system disorders include the increasing prevalence of drug-resistant HIV strains, increasing age of HIV-infected patients, hepatitis C virus co-infection and the Immune Reconstitution Inflammatory Syndrome. Herein, we review the clinical presentations, underlying pathogenesis and treatments of this burgeoning group of neurological disorders.
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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) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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".