OC 31.3 Phase 1 Study of the Safety, Tolerability, Pharmacokinetics, and Pharmacodynamics of VMX-C001 in Healthy Subjects
Bibliographic record
Abstract
the induction of anesthesia in the operating room.Our newly developed cartridges were used to measure DBCM-CT.Plasma was isolated, and they are used in evaluation of thrombin generation using calibrated automated thrombogram, and in vitro quantitative determination of direct Factor Xa inhibitors.Spearman's correlation was tested to analyze correlation between DBCM-CT and plasma concentration of DOACs or peak thrombin generation.Receiver operating characteristic curve analyses were performed to evaluate diagnostic performance of this system to detect <50 ng/mL of DOACs.Statistical significance was defined as P < 0.05.Results: DBCM-CT correlated with plasma concentration of DOACs (Rs = 0.87, for apixaban [n = 55, P < 0.001]; Rs = 0.91 for rivaroxaban [n = 46, P < 0.001], Fig 1).Peak thrombin levels showed significant correlation with DBCM CT Rs = -0.82for apixaban [n = 55, P < 0.001]; Rs = -0.84 for rivaroxaban [n = 46, P < 0.001], Fig 2).ROC analysis for detection of samples <50 ng/mL of DOACs showed area under the curve of 0.97 (95% confidence interval (CI) 0.94-1.0)for apixaban and 0.99 (95%CI 0.98-1.0)for rivaroxaban.Conclusion(s): These results suggest clinical usefulness of DBCM as a point of care test to evaluate anticoagulation induced by DOACs.
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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) | 0.002 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".