O12.4 Diagnosis of Learning Disability is Associated with Approximately 2-Fold Increase in Neurocognitive Impairment in People Living with HIV
Bibliographic record
Abstract
Background Milder forms of HIV-associated neurocognitive disorders (HAND) remain prevalent and can often be difficult to diagnose. Assessment of pre-morbid ability and consideration of morbidity factors remain important to diagnosis of HAND. Among relevant pre-morbid conditions, presence of learning and academic problems in school and diagnosis of learning disabilities (LD) have not been systematically studied in relation to neurocognitive impairment and self-reported cognitive symptoms in HIV. Methods We examined an urban city cohort of 903 people living with HIV infection referred for assessment of HAND. Patients were classified as having no learning disabilities (n= 474), learning or academic difficulties in school (n= 352) or having a diagnosis of learning disability or ADHD (n=77). Participants’ level of depressive symptoms (Beck Depression Inventory), cognitive symptoms (Patient’s Assessment of Own Functioning), and neuropsychological status (based on comprehensive neurocognitive testing of complex attention, learning and memory, psychomotor efficiency and executive functioning) were compared across the three groups classified according to presence and absence of learning difficulties and LD. Results Logistic regression models were used to assess the odds of global neurocognitive impairment (based on global deficit score). When depression, cognitive symptoms and LD were modeled together, both cognitive symptoms (OR: 1.08, 95% CI: [1.05, 1.10]) and diagnosis of a learning disability (OR: 1.77, 95% CI [1.06, 2.95]) were significant (p < 0.01). Conclusions Diagnosis of learning disability, but not academic difficulties, is associated with increased odds of neurocognitive impairment among people living with HIV, independently of depression and cognitive symptoms (both correlated; r= 0.58, p < 0.001) with cognitive symptoms also associated with the presence of neurocognitive impairment. Our results emphasize the importance of taking into consideration the diagnosis of learning disabilities when conducting assessment and diagnosis of HAND.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".