A-121 Analytical performance evaluation of the next generation Abbott enzyme assays on the Alinity c system
Bibliographic record
Abstract
Abstract Background Liver enzyme assays, including alanine aminotransferase (ALT), aspartate aminotransferase (AST), gamma-glutamyltransferase (GGT), and alkaline phosphatase (ALP), are essential in clinical laboratories for assessing liver function, diagnosing liver diseases, and monitoring treatment efficacy. Thus, accurate measurement of these enzyme activities is crucial for clinical diagnostics. Recently, Abbott introduced a next generation of Alinity and Architect enzyme assays, incorporating a multianalyte calibrator (Consolidated Chemistry Calibrator, ConCC) with extended stability. For these new formulation assays, both ConCC and calibration factors are offered for all the assays except GGT, which had better performance with the ConCC calibrator. These assays achieve high Sigma metrics on the Alinity c system, minimizing variability and errors. This study evaluated the analytical performance of these newly developed next generation assays on the Abbott Alinity c platform. Methods Using 2 levels of quality control (QC) material (Bio-Rad Chemistry UA) and 3 pooled patient samples, we assessed imprecision by measuring these 5 samples twice per day (morning and afternoon), for five days. Acceptable imprecision and bias were determined based on the Accreditation Canada Diagnostics (ACDx) recommendations. Linearity testing consisted of 6 levels of commercially available linearity materials, with 3 replicates per level. Method comparison between the next generation assays and on-market conventional assays were evaluated in duplicates using patient specimens (n= 145 – 155) on the Abbott Alinity c platform. Passing-Bablok and Bland-Altman plots were used for the method comparison analyses. The precision and bias (external standard) studies were used to calculate the Sigma-metric using the formula, Sigma-metric=(%TEa-|%bias|)/%CV. TEa was defined based on ACDx and Clinical Laboratory Improvement Amendments (CLIA) recommendations. Results The Alinity next generation assays demonstrated acceptable imprecision, meeting the ACDx goals of ±2 U/L for concentrations =40 U/L and ±4% for concentrations >40 U/L for AST, ALT and GGT, and for ALP at ±4 U/L for concentrations =100 U/L and ±4% for concentrations >100 U/L. Furthermore, these assays exhibited linearity across the six concentration levels tested. All next generation Alinity clinical chemistry enzyme assays showed a Pearson*s R value of 1.0, indicating a strong linear correlation. The linearity slope ranged from 0.76 (ALP2) to 1.04 (AST2) whereas the y-intercept ranged from –59.40 (GGT2) to 8.78 (AST2). The majority of next generation assays performed at or above 6 Sigma. Good agreements were observed between the on-market assay and the next generation (ConCC and factor calibrated) assays. Conclusion The Alinity next generation assays (ALT2, AST2, GGT2 and ALP2) demonstrated acceptable performance for precision and linearity, with good agreement with the conventional factor-based assays on the Alinity c system. These next generation assays had a high sigma value; hence laboratories can expect excellent performance. The precision and method comparison agreement with the conventional assays were satisfactory.
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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 | 0.008 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 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) | 0.003 | 0.002 |
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".