B-053 Investigation of Discrepant Alkaline Phosphatase Results on the Roche Cobas Pro Instrument
Bibliographic record
Abstract
Abstract Background A high frequency of Roche Cobas delta check instrument errors for alkaline phosphatase (ALP) led to the discovery of non-reproducible and spurious ALP results in a tertiary care hospital. A series of studies were subsequently performed on different Roche instruments at multiple hospital laboratories across Alberta, Canada, to determine the root cause and develop workflow mitigation strategies. Methods Three studies were implemented across different hospital laboratories to quantify frequency and identify cause of ALP fliers. ALP was measured on the Roche Cobas Pro c503 at 12 sites and on Roche Cobas 8000 c702 at 1 site. Replicates that exceeded the total allowable error (TAE) of =150 U/L ± 15 U/L or >150 U/L ± 10% were considered discrepant. Firstly, ALP samples run in duplicate and those exceeding the TAE were aliquoted, respun and reanalyzed in for 1-9 months. In the second study, ALP collections in BD Vacutainer plasma separator tubes (PST) were switched to BD Vacutainer Barricor tubes, which produce cleaner plasma, and run in duplicate for 1 month. Lastly, ALP was diluted (5x) and analyzed in duplicate. If TAE was exceeded then neat samples were aliquoted, respun and rerun. Results The first phase identified 563 ALP repeats outside the TAE across the Pro sites but none on the 8000. Frequency of spurious results varied at sites and ranged from 0.3-12/week and 0.04-1.5% of total ALP testing volumes. Initial duplicate comparisons had an overall mean difference (standard deviation, SD) of 15.1% (38.2%), and difference range of -85 to 270% across sites. Respinning significantly improved comparison results, with the percent mean (SD) decreasing to 0.3% (3.2%) and a narrower difference range of -13.5 to 41%. Barricor tubes reduced overall ALP flier rate by 72% and 5x dilutions reduced them by 89%. Conclusion Clinically significant ALP discrepancies were identified on multiple Roche Cobas Pro instrument across a large provincial laboratory network. These fliers were not observed on the Roche Cobas 8000, and were largely eliminated after respinning, dilution, and use of Barricor tubes, suggesting a preanalytical cause. This also suggests that the Pros may be more prone to interference from plasma contaminants. An automated workflow protocol involving a combination of onboard dilution of all ALP samples with respin only if TAE is exceeded was developed as a cost-effective and streamlined approach to minimize these errors.
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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 | 0.020 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 0.005 |
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".