Complex care needs of patients with late-stage HIV disease: A retrospective study
Bibliographic record
Abstract
This retrospective chart review provides a profile of an emerging population of vulnerable HIV patients with complex comorbidities. Data were abstracted from all 83 patients admitted in 2008 to Casey House, a community-based hospital dedicated to supportive and palliative care for persons with HIV in Toronto, Canada. We describe patient characteristics, including medical and psychiatric conditions, and use a Venn diagram and case study to illustrate the frequency and reality of co-occurring conditions that contribute to the complexity of patients ’ health and health care needs. The mean age at admission was 49.2 years (SD10.5). Sixty-seven patients (80.7%) were male. Patients experienced a mean of 5.9 medical comorbidities (SD2.3) and 1.9 psychiatric disorders (lifetime Axis I diagnoses). Forty patients (48.2%) experienced cognitive impairment including HIV-associated dementia. Patients were on a mean of 11.5 (SD5.3) medications at admission; 74.7 % were on antiretroviral medications with 55.0 % reporting full adherence. Current alcohol and drug use was common with 50.6 % reporting active use at admission. Our Venn diagram illustrates the breadth of complexity in the clients with 8.4 % of clients living in unstable housing with three or more medical comorbidities and two or more psychiatric diagnoses. Comprehensive HIV program planning should include interventions that can flexibly adapt to meet the multidimensional and complex needs of this segment of patients. Researchers, policy-makers, and clinicians need to have greater awareness of overlapping medical,
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".