Towards targeted screening for acute HIV infections in British Columbia
Bibliographic record
Abstract
BACKGROUND: Our objective was to describe the characteristics of acute and established HIV infections diagnosed in the Canadian province of British Columbia. Province-wide HIV testing and surveillance data were analyzed to inform recommendations for targeted use of screening algorithms to detect acute HIV infections. METHODS: Acute HIV infection was defined as a confirmed reactive HIV p24 antigen test (or HIV nucleic acid test), a non-reactive or reactive HIV EIA screening test and a non-reactive or indeterminate Western Blot. Characteristics of unique individuals were identified from the British Columbia HIV/AIDS Surveillance System. Primary drug resistance and HIV subtypes were identified by analyzing HIV pol sequences from residual sera from newly infected individuals. RESULTS: From February 2006 to October 2008, 61 individuals met the acute HIV infection case definition, representing 6.2% of the 987 newly diagnosed HIV infections during the analysis period. Acute HIV infection cases were more likely to be men who have sex with men (crude OR 1.71; 95% CI 1.01-2.89], to have had a documented previous negative HIV test result (crude OR 2.89; 95% CI 1.52-5.51), and to have reported a reason for testing due to suspected seroconversion symptoms (crude OR 5.16; 95% CI 2.88-9.23). HIV subtypes and rates of transmitted drug resistance across all classes of drugs were similar in persons with both acute and established HIV infections. CONCLUSIONS: Targeted screening to detect acute HIV infection is a logical public health response to the HIV epidemic. Our findings suggest that acute HIV infection screening strategies, in our setting, are helpful for early diagnosis in men who have sex with men, in persons with seroconversion symptoms and in previously negative repeat testers.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".