Lower Frailty Is Associated with Successful Cognitive Aging Among Older Adults with HIV
Bibliographic record
Abstract
Aging with HIV poses unique and complex challenges, including avoidance of neurocognitive disorder. Our objective here is to identify the prevalence and predictors of successful cognitive aging (SCA) in a sample of older adults with HIV. One hundred three HIV-infected individuals aged 50 and older were recruited from the Modena HIV Metabolic Clinic in Italy. Participants were treated with combination antiretroviral therapy for at least 1 year and had suppressed plasma HIV viral load. SCA was defined as the absence of neurocognitive impairment (as defined by deficits in tasks of episodic learning, information processing speed, executive function, and motor skills) depression, and functional impairment (instrumental activities of daily living). In cross-sectional analyses, odds of SCA were assessed in relation to HIV-related clinical data, HIV-Associated Non-AIDS (HANA) conditions, multimorbidity (≥2HANA conditions), and frailty. A frailty index was calculated as the number of deficits present out of 37 health variables. SCA was identified in 38.8% of participants. Despite no differences in average chronologic age between groups, SCA participants had significantly fewer HANA conditions, a lower frailty index, and were less likely to have hypertension. In addition, hypertension (odds ratio [OR] = 0.40, p = .04), multimorbidity (OR = 0.35, p = .05), and frailty (OR = 0.64, p = .04) were significantly associated with odds of SCA. Frailty is associated with the likelihood of SCA in people living with HIV. This defines an opportunity to apply knowledge from geriatric population research to people aging with HIV to better appreciate the complexity of their health status.
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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 | 0.001 | 0.001 |
| 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) | 0.002 | 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".