Identifying D-positive donors using a second automated testing platform
Bibliographic record
Abstract
Because of the variability of D expression, one method may be inadequate to correctly classify donors with variant RHD alleles. We evaluated the use of a solid -phase automated platform (ImmucorGamma Galileo) to confirm D- test results obtained on first-time donors on the Beckman Coulter PK7300 automated microplate test system. Samples with discordant results were analyzed by serologic tube methods, RHD genotyping using the BLOODchip platform (Progenika) and, if necessary, sequencing. We estimated the number of cases of alloimmunization in women younger than 50 years likelyto be prevented by the addition of Galileo testing. From May 2011 to May 2012, 910,220 donor samples were tested; 15,441 were first-time donors with concordant D- results. Five donors tested D- on the PK7300 and weak D+ on the Galileo; one was found to be a false positive on further testing. On manual testing, the other four donors had positive indirect antiglobulin test results with one to three of the antisera used and were C+. On BLOODchip testing, two donors were classified as D+, and two were assigned a "no call". D variants included weak D type 67, weak D type 9, and two novel variants. Approximately 10 percent of D- units are transfused to women younger that 50 years. Assuming an alloimmunization rate of 30 percent, use of the Galileo would prevent approximately one alloimmunization every 5 to 6 years in this patient group. We conclude that the yield of preventing alloimmunization in this population by adding a second automated seologic testing platform is very low.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".