Would CLSI M53-A have helped in the diagnosis of HIV in Canada? Results of the performance of Canadian laboratories participating in a recent NLHRS proficiency testing panel containing HIV-1 antigen positive (antibody negative) and HIV-2 samples
Bibliographic record
Abstract
INTRODUCTION: The Clinical and Laboratory Standards Institute recently published M53-A, Criteria for Laboratory Testing and Diagnosis of Human Immunodeficiency Virus (HIV) Infection; Approved Guideline (2011), which includes a state of the art algorithm for identifying HIV-1 acute and HIV-2 infections. To assess the ability of Canadian laboratories to detect these sample types and the impact of M53-A, the National Laboratory for HIV Reference Services distributed a special proficiency testing panel. METHODS: HIVS425-2012Nov22 was sent to 42 laboratories across Canada. It contained one HIV negative sample (B), two HIV-1 positive samples (A and E), one HIV-2 positive sample (C) and one HIV-1/2 antibody negative-HIV-1 antigen positive sample (D). Data was collected and analyzed using DigitalPT; a standardized on-line tool. RESULTS: Forty-one laboratories returned results. Sample B (HIV negative) was identified by 95% of laboratories (39/41) and samples A and E (HIV-1 positive) by 98% (40/41). No laboratory identified sample C as HIV-2 positive, although 85% (35/41) detected reactivity prompting a referral for further testing. The remaining laboratories identified sample C as HIV-1 positive (4), indeterminate (1) or gave no final status (1). Sample D (HIV antibody negative-antigen positive) was correctly identified by two laboratories as HIV-1 antigen positive while 78% (32/41) detected reactivity, recommending further testing. One laboratory did not provide a final status. Alarmingly, six laboratories called this sample HIV negative. CONCLUSION: Although there is a high quality of HIV testing across Canada, introduction of the M53-A guideline would further improve the ability of laboratories to diagnose HIV-1 acute and HIV-2 infection.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".