Strengths and Challenges of Various Models of Geriatric Consultation for Older Adults Living With Human Immunodeficiency Virus
Bibliographic record
Abstract
As care of persons living with human immunodeficiency virus (HIV; PWH) has transitioned from management of opportunistic infections to management of conditions associated with older age, new models of geriatric consultation are needed. The authors, who represent 9 clinics across North America and the United Kingdom, provided their insights on models of geriatric consultation for older PWH. Three models of geriatric consultation are delineated: outpatient referral/consultation, combined HIV/geriatric multidisciplinary clinic, and dually trained providers within 1 clinical setting. A patient-centered approach and the use of expertise across disciplines were universally identified as strengths. Logistical barriers and the reluctance of older PWH to see a geriatric care provider were identified as barriers to implementing these models. Although the optimal model of geriatric consultation depends on a region's resources, there is value in augmenting the training of infectious disease providers to include principles of geriatric care.
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 | 0.053 | 0.062 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.004 |
| Scholarly communication | 0.008 | 0.006 |
| Open science | 0.006 | 0.012 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".