Performance evaluation of all analytes on the epoc® Blood Analysis System for use in hospital surgical and intensive care units
Bibliographic record
Abstract
OBJECTIVE: To evaluate the performance of the epoc hand-held analyzer against the RAPIDPoint 500 blood gas analyzer and laboratory analyzers where applicable. METHODS: Venous or arterial whole blood samples collected in balanced heparinized syringes were obtained from 69 patients (35 females, 34 males) predominantly (77%) from the surgical unit and intensive care unit (ICU). Method comparison was performed for all analytes on the epoc System against the RAPIDPoint 500 Blood gas analyzer or laboratory analyzers where applicable. Results: Mean bias was <5% for blood gases, electrolytes, lactate and glucose. Hematocrit showed a bias of -6.76% (95% CI = -8.91, - 4.61) compared to the HemataSTAT-II method, whereas calculated total hemoglobin showed a bias of 1.51% (95% CI = -1.04, 4.06) against the Sysmex XN-10 hematology analyzer. Creatinine showed the largest bias relative to laboratory analyzers, Abbott Architect c8000 Jaffe method (13.54%, 95% CI = 5.43, 21.65) and Roche Cobas c702 enzymatic method (30.01%, 95% CI = 12.64, 47.38). Conclusions: The epoc system is fit for use in the surgical and ICU setting for the measurement of all analytes except for creatinine.
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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 | 0.020 | 0.044 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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".