A-003 Multisite Assessment of Commercial Quality Control Imprecision (testing from 2022 through to 2025) below the Limit of Quantification for a High-Sensitivity Cardiac Troponin I Assay
Bibliographic record
Abstract
Abstract Background The development of high-sensitivity cardiac troponin (hs-cTn) assays has enabled precise measurements below the 99th percentile upper reference limit, allowing serial measurements to detect subtle elevations of cTn at low concentrations. Therefore, analytical performance of the hs-cTn assay and the definition of “change” in cTn concentration in serial measurements are important factors for patient classification when using accelerated diagnostic pathways for patients with chest pain in the emergency setting. For the Abbott ARCHITECT hs-cTnI assay, the European Society of Cardiology (ESC) 0h/1h rapid ‘rule-out’ algorithm defines < 4 ng/L (limit of quantification (LoQ); 3.5 ng/L for Abbott ARCHITECT hs-cTnI assay in the United States) to rule-out at presentation and a delta of < 2 ng/L for values slightly exceeding the < 4 ng/L cutoff on serial measurements; emphasizing the need for robust analytical performance at these low concentrations. Unfortunately, in the United States, laboratories are not able to measure concentrations below the LoQ preventing assessment of analytical performance. In Canada, we can measure the Abbott ARCHITECT hs-cTnI assay at concentrations below the LoQ and accordingly we sought to assess imprecision using commercial quality control material below the LoQ ( < 4 ng/L) across seven different hospital sites. Methods The Thermo Scientific MAS Omni-CARDIO™ QC Ultra Low material (package insert value < 10 ng/L for the Abbott ARCHITECT hs-cTnI assay) was tested daily on seven different Abbott ARCHITECT analyzers (i1000 and i2000), generating 8685 measurements from 2022-2025 from different hospital sites: Hamilton General Hospital (i1000), St. Joseph’s Healthcare Hamilton (i1000), Milton District Hospital (i1000), Juravinski Hospital and Cancer Center (i2000), Georgetown Hospital (i1000), Oakville Trafalgar Memorial Hospital (i2000), and West Lincoln Memorial Hospital (i1000). Analytical performance at this level was evaluated against a standard deviation (SD) =1 ng/L as a precision goal, based on the recently published allowable performance limit (APL) of ±3 ng/L below 10 ng/L for hs-cTn assays (Clin Chem. 2025 Feb 3;71(2):332-334) Results The overall average concentration of the QC material was 3.1 ng/L with a SD of 0.9 ng/L, meeting the precision goal of SD =1 ng/L. Only 0.9% of QC results fell outside the APL (i.e. < 0.1 and > 6.1 ng/L), further supporting the validity of the proposed APL. Next, we further evaluated the impact of analytical performance at this level on the ESC ‘rule-out’ algorithm (i.e. < 4 ng/L for the initial hs-cTnI concentration). Assuming each QC result corresponds to an initial hs-cTnI test result (in whole number), 73.8% of all QC measurements would be < 4 ng/L. Conclusion This is the first study to evaluate daily QC performance below the LoQ of a hs-cTn assay. Daily QC measurements (mean = 3.1 ng/L for the Abbott ARCHITECT hs-cTnI assay) can be achieved with acceptable analytical precision (SD =1 ng/L) in small and large community and academic hospital settings. Despite robust analytical performance, nearly a quarter of results exceed 4 ng/L, potentially contributing to patient misclassification using a single low hs-cTnI cutoff as per the ESC pathway.
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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 | 0.055 | 0.059 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 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".