African regional external quality assessment for CD4 T-cell enumeration: Development, outcomes, and performance of laboratories
Bibliographic record
Abstract
BACKGROUND: An independent African Regional External Quality Assessment Scheme (AFREQAS) was implemented from Johannesburg. The aim was to establish a network of CD4 laboratories supporting HIV/AIDS anti-retroviral therapy programs and improve the quality of regional CD4 testing with EQA assessment, feedback, remedial action, and technical training. The overall performance from 2002 to 2006 (Trials 1-20) is reported, together with cumulative longitudinal performance of the different CD4 methods used. METHODS: Stabilized blood samples with "normal" and/or "low" CD4 values were shipped over 20 Trials. Data was analyzed for each trial including trimmed mean, standard deviation, and percentage coefficient of variation (%CV); "Residual" and SDI values were also calculated for each participating laboratory for both absolute CD4 counts (CD4abs) and CD4 percentage of lymphocytes values (CD4%/Ly). Standardized individual laboratory SDI values across 20 trials were analyzed according to CD4 method. RESULTS: Average participation was 91.5%. Overall AFREQAS between-laboratory reproducibility (trimmed %CV) was 10.5% and 9.1% for absolute CD4 and CD4%/Ly, respectively. For the respective CD4abs and CD4%/Ly values in the trials where "normal" material was shipped trimmed %CV of 10.9 and 7.3% were noted, and in "low" value shipments %CV of 13.8% and 12.4% were noted. Cumulative absolute CD4 SDI analysis revealed the best between-laboratory precision amongst FACSCount and PanLeucogating (PLG-CD4) users (both SD of SDI = <1.2 and %CV of <<8%). Dual Platform or Single Platform algorithm-based systems and certain volumetric methods (laboratories who used Partec CyFlow instruments) had higher numbers of outlying laboratories (>12-25%CV and SD(SDI) > 2.2 noted), indicating that additional technical training and/or manufacturer support was required. CONCLUSIONS: Participation in an AFREQAS with feedback and remedial action improves the quality of CD4 testing. African laboratory professionals can easily master CD4 counting technologies. However, the introduction of the simplest and most cost-effective methodologies is required to take ownership, and enable the delivery of quality CD4 counts in vast numbers necessary to support expansion of African ART programs.
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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 | 0.072 | 0.052 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".