Suboptimal effect of a three‐factor prothrombin complex concentrate (Profilnine‐SD) in correcting supratherapeutic international normalized ratio due to warfarin overdose
Bibliographic record
Abstract
BACKGROUND: Plasma transfusion is standard therapy for urgent warfarin reversal in the United States. "Four-factor" prothrombin complex concentrate (PCC), available in Europe, has advantages over plasma therapy for warfarin reversal; however, only "three-factor" PCCs (containing relatively low Factor [F]VII) are available in the United States. STUDY DESIGN AND METHODS: The efficacy of a three-factor PCC for urgent warfarin reversal was evaluated in 40 patients presenting with supratherapeutic international normalized ratio (ST-INR > 5.0) with bleeding (n = 29) or at high risk for bleeding (n = 11). In 13 patients, pre- and posttherapy vitamin K-dependent factors were assayed. Historical controls (n = 42) treated with plasma alone were used for rate of ST-INR correction comparison. RESULTS: Treatment with plasma alone (mean, 3.6 units) lowered the INR to less than 3.0 in 63 percent of historical controls. Low-dose (25 U/kg) and high-dose (50 U/kg) PCC alone lowered INR to less than 3.0 in 50 and 43 percent of patients, respectively. Additional transfusion of a small amount of plasma (mean, 2.1 units) increased the rate of achieving an INR of less than 3.0 to 89 and 88 percent for low- and high-dose PCC therapy, respectively. FII, F IX, and FX increments were similar for PCC-treated patients with or without supplemental plasma; FVII was significantly higher in the PCC plus plasma group compared to the PCC-only group (p = 0.001). CONCLUSION: Three-factor PCC does not satisfactorily lower ST-INR due to low FVII content. Infusion of a small amount of plasma increases the likelihood of satisfactory INR lowering.
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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 | 0.000 | 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 | 0.000 | 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".