Cohort Profile Update: Reflecting back and looking ahead: Updating the Comparative Outcomes and Service Utilization Trends (COAST) Study to include 28 years of linked data from people with and without HIV in British Columbia, Canada
Bibliographic record
Abstract
Introduction: The Comparative Outcomes and Service Utilization Trends (COAST) study compares health outcomes among People With HIV (PWH) and People Without HIV (PWoH) in British Columbia (BC), Canada. The cohort was recently updated to include persons diagnosed with HIV after March 31, 2013, and expanded to broaden research applications. Methods: COAST includes PWH and a 10% random sample of the general population without HIV, all aged ≥19. Our study links an HIV registry to healthcare practitioner billing, hospital and emergency department attendance data, prescription drug dispensations, and a cancer registry. Our cohort update included new sampling strategies, adding data on emergency department visits not previously captured, and extending our follow-up period to 28 years (from 1992 to 2020). COAST now includes 17,119 PWH and 615,264 PWoH. Findings to date: COAST has contributed to our understanding of combination antiretroviral therapy (ART) use, health service utilization, chronic diseases, mental health and substance use disorders, and mortality among PWH in BC. Key findings include earlier age at diagnosis of certain chronic conditions, a higher incidence of mood disorders among PWH, and noteworthy shifts in causes of death among PWH on ART. The updated cohort will provide insights into the changing nature of the population living with HIV in BC and serves as a novel foundation for further research. Future plans: To explore and extend knowledge of the evolving trends among people living and aging with HIV in BC, regular data linkage updates and the inclusion of additional datasets are scheduled every two years.
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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 | 0.013 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.005 | 0.012 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.004 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 0.003 |
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".