The role of cognitive reserve in protecting cognitive ability in people with HIV
Bibliographic record
Abstract
Cognitive reserve is a potential explanation for the disparity between brain pathology and its clinical manifestations.The main objective of this study was to estimate, based on published studies, the strength of the association between cognitive reserve and cognitive performance in individuals with HIV.A systematic literature search using Ovid MEDLINE, PsychINFO, and EMBASE was performed to identify studies published between 1990 and 2016 that quantified the association between cognitive reserve and cognitive performance in HIV.A random-effects metaanalysis was used to compute a summary estimate (Cohen's d ) with 95% confidence intervals (CI) and 95% prediction intervals (PI).The risk of bias and quality of reporting in the studies were indicated by the Appraisal tool for Cross-Sectional Studies (AXIS).Ten observational studies were deemed eligible.The pooled effect size was 0.9 (95% CI: 0.7-1.0;95% PI: 0.4-1.4) with marked heterogeneity studies [Cochran's Q (df = 9) = 28.0,p = .0009;I 2 statistic = 67.4%].Risk-of-bias appraisal showed that non-response bias was never addressed and the items associated with selection bias were only partially met.The association between cognitive reserve and cognitive performance suggests that building reserve through non-pharmacological interventions could be a potentially effective way of combating cognitive impairment in people with HIV.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".