Pediatric reference interval verification for common biochemical assays on the Abbott Alinity system
Bibliographic record
Abstract
OBJECTIVES: The quality of clinical laboratory service depends on quality laboratory operations and accurate test result interpretation based on reference intervals (RIs). As new analytical systems continue to be developed and improved, previously established RIs must be verified. The Canadian Laboratory Initiative on Pediatric Reference Intervals (CALIPER) has established comprehensive RIs for many biomarkers on several analytical systems. Here, published CALIPER RIs for 28 chemistry assays on the Abbott ARCHITECT were assessed for verification on the newer Alinity system. METHODS: An analytical validation was first completed to assess assay performance. CALIPER serum samples (100) were analyzed for 28 chemistry assays on the Alinity system. The percentage of results falling within published pediatric ARCHITECT reference and confidence limits was determined for each analyte. Based on Clinical and Laboratory Standards Institute (CLSI) guidelines, if ≥90% of test results fell within confidence limits of ARCHITECT assay RIs, they were considered verified. RESULTS: Of the 28 assays assessed, 26 met the criteria for verification. Reference values for calcium and magnesium did not meet the criteria for verification with 87% and 35% falling within previously established ARCHITECT confidence limits, respectively. However, both assays could be verified using pediatric RIs provided in the Abbott Alinity package insert. CONCLUSIONS: In this study, CALIPER ARCHITECT RIs were verified on the Alinity system for several chemistry assays. These data demonstrate excellent concordance for most assays between the Abbott ARCHITECT and Alinity systems and will assist in the implementation of the Alinity system in pediatric healthcare institutions.
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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 | 0.028 | 0.045 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 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".