HIV and aging : age-associated chronic comorbidities among HIV-positive individuals on highly active antiretroviral therapy in British Columbia, Canada
Bibliographic record
Abstract
Background: Highly active antiretroviral therapy (HAART) has transformed HIV from a once fatal condition into a treatable chronic disease. As people with HIV are living longer than in the past, understanding the effects of aging with HIV is of increasing importance. This dissertation aims to explore trends of several chronic diseases during the current HAART era, while also taking into consideration the impact of expanded access to HAART in British Columbia, Canada from 2000-2012. Methods: The studies presented in this dissertation are based on administrative data collected from the Comparative Outcomes and Health Service Utilization Trends (COAST) study. Various analytical methods were used to assess trends of chronic disease incidence of six common chronic diseases: cardiovascular disease (CVD), chronic obstructive pulmonary disease (COPD)/asthma, diabetes mellitus (DM), hypertension (HTN), chronic kidney disease (CKD) and chronic liver disease (CLD). Both studies were retrospective population-based cohort studies of HIV-positive individuals whom accessed HAART and identified as HIV-positive in the COAST study database by validated algorithms. Several measures were employed to determine risks and trends of chronic disease incidence. Results: The results of each study showed that trends and risks of chronic disease incidence were not all consistent. In the first study exploring trends of chronic diseases among 10,210 HIV-positive individuals whom had accessed HAART the adjusted incidence rate for HTN increased over time; CKD and CLD decreased over time; and no trend was observed for CVD, COPD/Asthma and DM. In the second study, among 4,840 HIV-positive individuals who initiated HAART during this period, the relative risk of CLD incidence was reduced in the post- (2006-2012) versus pre- (2000-2005) HAART expansion periods. The relative risk for CVD, DM, HTN, COPD/asthma and CKD were not statistically significant in the post expansion period. Conclusions: Results from this dissertation provide insight on trends and risks of several comorbidities during the current HAART era. Specifically, the results of this dissertation highlight the trend towards increasing incidence of HTN and decreasing incidence of CLD among HIV-positive aging populations. Understanding how chronic comorbidities affect future disability and death among people aging with HIV is an important area of further research.
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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 | 0.002 | 0.006 |
| Science and technology studies | 0.004 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".