Diagnostic discrimination of a novel high-sensitivity cardiac troponin I assay and derivation/validation of an assay-specific 0/1h-algorithm
Bibliographic record
Abstract
BACKGROUND: We aimed to assess the diagnostic utility of the Dimension EXL LOCI High-Sensitivity Troponin I (hs-cTnI-EXL) assay. METHODS: This multicenter study included patients with chest discomfort presenting to the emergency department. Diagnoses were centrally and independently adjudicated by two cardiologists using all available clinical information. Adjudication was performed twice including serial measurements of high-sensitivity cardiac troponin (hs-cTn) I-Architect (primary analysis) and serial measurements of hs-cTnT-Elecsys (secondary analysis) in addition to the clinically used (hs)-cTn. The primary objective was to assess and compare the discriminatory performance of hs-cTnI-EXL, hs-cTnI-Architect and hs-cTnT-Elecsys for acute myocardial infarction (MI). Furthermore, we derived and validated a hs-cTnI-EXL-specific 0/1h-algorithm. RESULTS: Adjudicated MI was the diagnosis in 204/1454 (14%) patients. The area under the receiver operating characteristics curve for hs-cTnI-EXL was 0.94 (95%CI, 0.93-0.96), and comparable to hs-cTnI-Architect (0.95; 95%CI, 0.93-0.96) and hs-cTnT-Elecsys (0.93; 95%CI, 0.91-0.95). In the derivation cohort (n = 813), optimal criteria for rule-out of MI were <9ng/L at presentation (if chest pain onset >3h) or <9ng/L and 0h-1h-change <5ng/L, and for rule-in ≥160ng/L at presentation or 0h-1h-change ≥100ng/L. In the validation cohort (n = 345), these cut-offs ruled-out 56% of patients (negative predictive value 99.5% (95%CI, 97.1-99.9), sensitivity 97.8% (95%CI, 88.7-99.6)), and ruled-in 9% (positive predictive value 83.3% (95%CI, 66.4-92.7), specificity 98.3% (95%CI, 96.1-99.3)). Secondary analyses using adjudication based on hs-cTnT measurements confirmed the findings. CONCLUSIONS: The overall performance of the hs-cTnI-EXL was comparable to best-validated hs-cTnT/I assays and an assay-specific 0/1h-algorithm safely rules out and accurately rules in acute MI. CLINICAL TRIAL REGISTRATION: ClinicalTrials.gov number, NCT00470587.
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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 | 0.010 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| 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 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".