Interchangeability of Electrolyte and Metabolite Testing on Blood Gas and Core Laboratory Analyzers
Bibliographic record
Abstract
BACKGROUND: Using blood gas (BG) analyzers as backups for core laboratory analyzers has the potential to greatly reduce turnaround times and costs. METHODS: One venous blood gas syringe, one plasma separator tube (PST), and one serum separator tube (SST) were drawn from 42 healthy individuals. All samples were run on the GEM4000 BG analyzer whereas the PST and SST samples were also run on the Roche Modular chemistry analyzer. Blood electrolyte and metabolite parameters were compared for paired measurements, and their differences were assessed for statistical and clinical significance. RESULTS: Whole blood on GEM4000 and plasma/serum on Roche Modular produced incomparable results for Na+ in plasma and serum (2.5 percentile difference, GEM4000 - Modular: -4.975 and -4.95 mmol/L, respectively) and K+ in serum (2.5 percentile difference, GEM4000 - Modular: -0.7975 mmol/L). When comparing whole blood to plasma/serum samples, all from the GEM4000, incomparable parameters were also found for Cl- in plasma and serum (97.5 percentile difference, plasma or serum - whole blood: 6 and 5 mmol/L, respectively), and K+ in serum (97.5 percentile difference, serum - whole blood: 0.7 mmol/L). None of the parameter differences when comparing plasma/serum results on the GEM4000 to those on the Roche Modular were found to be clinically significant. CONCLUSIONS: The off-label use of plasma/serum on a BG analyzer produced electrolyte and metabolite measurements that were more interchangeable with standard core laboratory analyzer results than with its designated whole blood samples. The interchangeability of results, therefore, seems to be affected more by different sample types than by different measurement methods.
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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 | 0.019 | 0.051 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".