A practical approach for the validation and clinical implementation of a high-sensitivity cardiac troponin I assay across a North American city
Bibliographic record
Abstract
Despite several publications on the analytical performance of high-sensitivity cardiac troponin (hs-cTn) assays, there has been little information on how laboratories should validate and implement these assays into clinical service. Our study provides a practical approach for the validation and implementation of a hs-cTn assay across a large North American City. Validation for the Abbott ARCHITECT hs-cTnI assay (across 5 analyzers) consisted of verification of limit of blank (LoB), precision (i.e., coefficient of variation; CV) testing at the reported limit of detection (LoD) and within and outside the 99th percentile, linearity testing, cTnI versus hs-cTnI patient comparison within and between analyzers (Passing and Bablok and non-parametric analyses). Education, clinical communications, and memorandums were issued in advance to inform all staff across the city as well as a selected reminder the day before live-date to important users. All hospitals switched to the hs-cTnI assay concurrently (the contemporary cTnI assay removed) with laboratory staff instructed to repeat samples previously measured with the contemporary cTnI assay with the hs-cTnI assay only by physician request. Across the 5 analyzers and 6 reagent packs the overall LoB was 0.6 ng/L (n=60) with a CV of 33% at an overall mean of 1.2 ng/L (n=60; reported LoD=1.0 ng/L), with linearity demonstrated from 45,005 ng/L to 1.1 ng/L. Precision testing with a normal patient-pool QC material (mean range across 5 analyzers was 3.9–4.4 ng/L) yielded a range of CVs from 7% to 10% (within-run) and CVs from 7% to 18% (between-run) with the high patient-pool QC material (mean range across 5 analyzers was 29.6–36.3 ng/L) yielding a range of CVs from 2% to 5% (within-run) and CVs from 4% to 8% (between-run). There was agreement between hs-cTnI versus cTnI with the patient samples (slope ranges: 0.89–1.03; intercept ranges: 1.9–3.8 ng/L), however, the median CV on patient samples <100 ng/L across the analyzers was 5.6% for hs-cTnI versus 18.7% for the contemporary assay (p<0.001). Following the switch to hs-cTnI testing, no requests for repeat measurements were received. Validation and implementation of hs-cTnI testing across multiple sites requires collaboration within the laboratories and between hospital laboratories and clinical staff.
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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 | 0.075 | 0.075 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.007 | 0.003 |
| Scholarly communication | 0.006 | 0.004 |
| Open science | 0.006 | 0.010 |
| Research integrity | 0.005 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 0.007 |
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".