A North American multilaboratory study of CD4 counts using flow cytometric panleukogating (PLG): A NIAID-DAIDS Immunology Quality Assessment Program Study
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: The global HIV/AIDS pandemic and guidelines for initiating anti-retroviral therapy (ART) and opportunistic infection prophylaxis demand affordable, reliable, and accurate CD4 testing. A simple innovative approach applicable to existing technology that has been successfully applied in resource-challenged settings, PanLeukogated CD4 (PLG), could offer solutions for cost saving and improved precision. METHODS: Day-old whole blood from 99 HIV+ donors was simultaneously studied in five North-American laboratories to compare the performance of their predicate methods with the dual-platform PLG method. The predicate technology included varying 4-color CD45/CD3/CD4/CD8 protocols on different flow cytometers. Each laboratory also assayed eight replicate specimens of day-old blood from 10 to 14 local donors. Bias and precision of predicate and PLG methods was studied between- and within-participating laboratories. RESULTS: Significantly (P < 0.0001) improved between-laboratory precision/coefficient of variation (CV%) was noted using the PLG method (overall median 9.3% vs. predicate median CV 13.1%). Within-laboratory precision was also significantly (P < 0.0001) better overall using PLG (median 4.6% vs. predicate median CV 6.2%) and in 3 of the 5 laboratories. PLG counts tended to be 11% smaller than predicate methods (P < 0.0001) for shipped (median of predicate-PLG = 31) and local specimens (median of predicate-PLG = 23), both overall and in 4 of 5 laboratories (median decreases of 4, 16, 20, and 21% in shipped specimens); the other laboratory had a median increase of 5%. CONCLUSION: Laboratories using predicate CD4 methods similar to those in this study could improve their between-laboratory and their within-laboratory precision, and reduce costs, by switching to the PLG method after adequate training, if a change (usually, a decrease) in CD4 counts is acceptable to their health systems.
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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 | 0.003 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.000 |
| Bibliometrics | 0.002 | 0.009 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.001 | 0.001 |
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 it