Comparison of Becton Dickinson Vacutainer rapid serum tube with the serum separator tube for routine chemistry and immunoassay tests
Bibliographic record
Abstract
AIMS: To shorten the clotting time and resolve the delayed clotting or no clotting on specimens from patients on anticoagulant therapy, Becton Dickinson (BD) recently developed the Vacutainer rapid serum tube (RST). The aim of this study was to systematically compare the new RST tube with the widely used serum separator tube (SST) for routine chemistry and immunoassay tests on 3 common analyser platforms. METHODS: Blood from 45 people (24 women and 21 men, age 21-77 years) was collected using the SST and RST tubes in sequence. Sera from both tubes were separated and analysed simultaneously for 54, 50, and 10 chemistry and/or immunoassay tests on the Roche Modular, Abbott Architect, and Siemens Centaur analysers, respectively. RESULTS: The results from the RST tube were comparable with those from the SST tube on most analytes. Although the results for a few analytes showed statistically significant differences between the two tubes (p<0.05), the differences had no clinical significance for most assays. Only for parathyroid hormone on the Abbott Architect, the RST tube demonstrated clinical significant bias versus the SST tube (-15.3%, p<0.01). CONCLUSIONS: The RST tube provides acceptable performance for routine chemistry and immunoassay tests.
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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 | 0.012 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| 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 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".