HLA B51 is associated with faster AIDS progression among newly diagnosed HIV‐infected individuals in Manitoba, Canada
Bibliographic record
Abstract
Human leucocyte antigen (HLA) alleles influence the rate of CD4 decline among HIV-infected individuals. We investigated the association between HLA B35 and HLA B51 and the rate of CD4 decline and/or opportunistic infections, among 294 HIV-positive individuals from Manitoba, Canada. All individuals presenting with a CD4 count >200 cells μL(-1) , who had at least two CD4 counts, and no evidence of co-infection were included. Individuals bearing HLA B35 or HLA B51 were compared to controls. A multivariate model demonstrated that HLA B35 allele was associated with a hazard ratio of 2.05 (95% CI 1.31-3.18) for reaching AIDS and HLA B51 allele with HR of 2.03 (95% CI 1.18-3.49) for reaching the same end-point. High prevalence of HLA B35 was seen in the patient population receiving care in Manitoba. Our observations confirm the association of HLA B35 with rapid disease progression. We report, for the first time, faster CD4 decline among individuals with HLA B51 allele.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".