What problems associated with ageing are seen in a specialist service for older people living with HIV?
Bibliographic record
Abstract
OBJECTIVES: By 2030 the majority of the people living with HIV in the United Kingdom will be over the age of 50. HIV services globally must adapt to manage people living with HIV as they age. Currently these services are often designed based on data from the wider population or from the experiences of HIV clinicians. This article aims to help clinicians designing inclusive HIV services by presenting the most common needs identified during the first year of a specialist clinic for older people living with HIV at the Ian Charleson Day Centre, Royal Free Hospital in London, United Kingdom. METHODS: The records of all thirty-five patients attending the inaugural nine sessions were reviewed. RESULTS: The median age of attendees was 69 (53-93) with 77% being male, 63% being White, 49% being heterosexual and 97% being virally suppressed respectively. The majority (83%) met the criteria for frailty using the Fried frailty phenotype. Eighteen issues linked to ageing were identified with the most common being affective symptoms (51%), memory loss (37%) and falls (29%). CONCLUSIONS: Whilst older people living with HIV are a heterogeneous group frailty is common and appears to present earlier. HIV services either need to adapt to meet these additional needs or must support users in transitioning to existing services. We feel that our multidisciplinary model is successful in identifying problems associated with ageing in people living with HIV and could be successfully replicated elsewhere.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".