Evaluation of argatroban and DUP 714 as anticoagulants for blood gas, electrolyte and ionized calcium analyses
Bibliographic record
Abstract
The objective of this study was to determine if the thrombin inhibitors Argatroban and DUP 714 could anticoagulate whole blood without influencing the analyses of blood gases, electrolytes, ionized calcium or CO-oximetry. The anticoagulant potency of DUP 714 (0.5-68 micromol/l) and Argatroban (1.5-390 micromol/l) was evaluated using the activated partial thromboplastin time (APTT), prothrombin time (PT) and whole blood clot time (WBCT). APTT and the PT were measured using a Behring Fibrintimer. APTT was found to be more sensitive to prolongation by both of the thrombin inhibitors than were the PT or WBCT assays. DUP 714 was found to a more potent anticoagulant than Argatroban. DUP 714 anticoagulated specimens (>2.2 micromol/l) did not clot for at least 2 days, whereas Argatroban preserved specimens (390 micromol/l) clotted within 5.5 h of collection. No statistically significant changes in the measurement of pH, PCO2, PO2, Na, K, ionized calcium, oxyhaemoglobin, deoxyhaemoglobin, methaemoglobin or carboxyhaemoglobin (measured using a Corning 288 Blood Gas/Electrolyte Analyzer and a Coming 270 CO-oximeter) were detected in DUP 714 (34 micromol/l) or Argatroban (390 micromol/l) anticoagulated whole blood specimens. In conclusion, DUP 714 and Argatroban are suitable anticoagulants for preserving blood prior to blood gas and electrolyte analyses.
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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".