Cohort profile: the LHIV-Manitoba clinical cohort of people living with HIV in Manitoba, Canada
Bibliographic record
Abstract
Purpose The LHIV-Manitoba cohort was developed as a way to provide a comprehensive source of HIV-related health information in the central Canadian Prairie province of Manitoba. The cohort will provide important information as we aim to better understand local HIV epidemiology and address key knowledge and practice gaps in HIV prevention, treatment and care programming in the province. Participants In total, 890 individuals, aged 18 or older and living or receiving HIV care in Manitoba are enrolled in the cohort. A complete clinical dataset exists for 725 participants, which includes variables on sociodemographic characteristics, comorbidities and co-infections, self-reported HIV exposure categories and HIV clinical indicators. A limited clinical dataset exists for an additional 165 individuals who were enrolled posthumously. 97.5% of cohort participants’ clinical records are linked to provincial administrative health datasets. Findings to date The average age of cohort participants is 49.7 years. Approximately three-quarters of participants are male, 42% self-identified as white and 42% as Indigenous. The majority of participants (64%) reported condomless vaginal sex as a risk exposure for HIV. Nearly one-fifth (18%) of participants have an active hepatitis C virus infection and the cohort’s median CD4 count increased from 316 cells/mm3 to 518 cells/mm3 between time of entry into care and end of the first quarter in 2019. Future plans The LHIV-Manitoba cohort is an open cohort, and as such, participant enrolment, data collection and analyses will be continually ongoing. Future analyses will focus on the impact of provincial drug plans on clinical outcomes, determinants of mortality among cohort participants and deriving estimates for a local HIV care cascade.
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How this classification was reachedexpand
Direct model labels (unvalidated)
Per-model category and study-design labels from the labeling rounds. They are machine output, unvalidated, and the disagreement between models ships as data. No study design here is MEDLINE-validated yet.
| Model arm | Categories | Study design | Confidence |
|---|---|---|---|
| gemma | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | low |
| gpt | no category Domain: not available · Genre: Empirical About the Canadian research system: no · About a Canadian topic: yes | Observational | high |
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 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.006 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.002 |
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, unvalidatedLabeled directly by 2 models reading the full record.
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".