Minimizing high sensitivity troponin T delta variation at low concentration using BD Barricor blood collection tube
Bibliographic record
Abstract
OBJECTIVE: Reproducible low troponin concentrations from high-sensitivity troponin (hs-cTn) assays are paramount to accurate risk determination in the accelerated diagnostic pathway. Total variation consists of pre-analytical, analytical and biological components. While analytical and biological variations cannot be readily modifiable, minimizing pre-analytical variation is desirable and potentially attainable. The BD Barricor collection tube has previously been demonstrated to reduce pre-analytical variation in test results. The goal of the study is to determine whether BD Barricor tubes provide more reproducible hs-cTnT results compared to plasma separator tubes (PST) at concentrations ≤ 20 ng/L. METHODS: Paired intra-patient hs-cTnT results collected less than 1 h apart in the emergency department were retrospectively analyzed from nine urban hospitals which primarily use either PST (n = 336 pairs) or Barricor (n = 327 pairs) collection tubes for troponin. Total variation of the replicated measurements was calculated for hs-cTnT ≤ 20 ng/L. The numbers of paired intra-patient samples were grouped based on decisive absolute delta thresholds as indicated by the European Society of Cardiology 0/1 h algorithm; delta < 3 ng/L, 3-4 ng/L, ≥5 ng/L. RESULTS: The total testing variation for hs-cTnT collected in PST is 14.8 % while Barricor is 8.6 % for hs-cTnT ≤ 20 ng/L. The proportion of delta values < 3 ng/L between the intra-patient replicates is 80.4 % (95 % CI: 75.7-84.5 %) in PST compared to 95.4 % (95 % CI: 92.5-97.4 %) in Barricor (p < 0.001). Median time for serial sampling in PST is 41 min (IQR:18-53) and Barricor is 45 min (IQR 23-54). CONCLUSION: The use of Barricor tubes demonstrated reproducible and less variable hs-cTnT replicates at concentration ≤ 20 ng/L when compared to a hospital that does not use Barricor tubes.
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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 | 0.005 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 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".