Retrospective analysis of intra-patient laboratory variation demonstrates that the BD Vacutainer® Barricor™ blood collection tube reduces troponin variation
Bibliographic record
Abstract
OBJECTIVE: The BD Vacutainer® Barricor™ plasma blood collection tube uses a mechanical separator during centrifugation to separate plasma from the cellular elements of blood. Compared to use of plasma separator tubes (PST™) with gel, Barricor™ produces a cleaner sample with less residual cellular content. We sought to determine if Barricor™ reduces pre-analytical error compared to PST™. DESIGN & METHODS: We used a model previously published that utilizes serial differences between intra-patient measurements transformed into a Taylor series of variation vs time with the y-intercept equal to the sum of short-term analytic variation, preanalytic variation and biologic variation. The intra-patient variation of chloride, sodium, potassium, and troponin-T (hs-TnT) obtained from the Emergency Department of a large tertiary care center sampled with PST™ (May 2015-April 2018, n = 59,762 specimens) or Barricor™ (May 2018-May 2021, n = 61,512 specimens) was evaluated. All specimens were analyzed on either Roche Modular or Cobas® instruments. For each analyte, pairs of intra-patient results were tabulated and separated by 1 h intervals. The average between-pair variations were then regressed against time. We also determined the number of intra-patient outliers using the reference change value for each analyte. RESULTS: The Barricor™ hs-TnT y-intercept (-0.0132) was significantly lower than the PST™ intercept (0.9109; p = 0.022). This was also true for chloride (y-intercept = 1.0067 in Barricor™ and 1.3431 in PST™, p = 0.037). The percentage of hs-TnT outliers was significantly lower in Barricor™ (8.32 %) vs PST™ (12.2 %; p < 0.001). CONCLUSION: The analytical and biological variations are assumed to be steady over the study periods; we ascribe the difference in the y-intercept to the preanalytical effect of the Barricor™ tube reducing platelets and other cellular debris.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.003 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 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".