Whole Blood Cardiac Troponin “Triaging” to Improve Early Detection of Myocardial Injury at a Pediatric Hospital
Bibliographic record
Abstract
BACKGROUND: The importance of offering on-site cardiac troponin (cTn) testing at pediatric hospitals may be underappreciated. We developed a rapid rule-in process for myocardial injury at a pediatric hospital experiencing delays in off-site high-sensitivity cardiac troponin T (hs-cTnT) testing. METHODS: Collect-to-verify turnaround times (TATs) for off-site testing were reviewed. Pre-analytic changes to improve TATs were devised, implemented and evaluated, after which a new analyzer was selected and evaluated for on-site cTn testing. Performance of the new analyzer's assay was compared to the off-site hs-cTnT assay, and post go-live TATs for on-site testing were assessed. RESULTS: Median collect-to-verify TAT for short turnaround-time (STAT) priority off-site plasma hs-cTnT testing was 104 min, with 35% of orders having a TAT >120 min. Eliminating serum separator tubes and requiring a separate plasma separator tube did not significantly reduce TATs. A QuidelOrtho Triage® MeterPro whole blood cardiac troponin I (cTnI) assay was implemented to "triage" time-critical and STAT priority specimens collected for off-site hs-cTnT testing. Elevated cTnI (≥0.02 µg/L) had a sensitivity of 91% for clear elevations in hs-cTnT (≥53 ng/L) but a 0% sensitivity for modest elevations (5 to 13 ng/L, 14 to 52 ng/L). An interpretive comment was auto-appended to cTnI results indicating that clinicians should wait for the hs-cTnT result if cTnI was normal. Median collect-to-verify TAT for on-site cTnI testing was <50% the TAT for off-site hs-cTnT testing. CONCLUSIONS: On-site point-of-care whole blood cTn testing can rapidly confirm significant or late-presenting myocardial injury. Combined with simultaneous off-site high-sensitivity cardiac troponin (hs-cTn) testing, this workflow is a viable interim solution for pediatric hospitals without on-site hs-cTn testing.
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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 | 0.003 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".