Efficacy of Prothrombin Complex Concentrate (PCC) for Reversal of Warfarin Effect.
Bibliographic record
Abstract
Abstract In the United States supratherapeutic INRs are typically reversed with fresh frozen plasma (FFP). This requires transfusion of large volumes (10–15 ml/kg) with therapeutic delay, volume overload, risk for TRALI (transfusion related acute lung injury) and multiple donor exposures. Our Blood Utilization Review Committee recommends PCC as the preferred product for warfarin reversal. Profilnine (Alpha Therapeutic Corp, Los Angeles, CA) is PCC containing vitamin-K dependent clotting factors and dosed by FIX content. FII, VII and X content is no more than 150%, 35% and 100% of the FIX amount, respectively. The manufacturer’s suggested dose for warfarin reversal is 15–50 U/kg. The dose of PCC and need for vitamin K or FFP is determined by the clinician after consultation with the transfusion service. Sixty-five patients received PCC; 25 for reduction of INR prior to surgery or other interventions and 40 for treatment of a supratherapeutic INR (>5.0) with bleeding or risk of bleeding. Twenty-three patients with supratherapeutic INRs received low dose PCC (mean 25 U/kg) and 17 received high dose (mean 50 U/kg). The average admission INR was 9.0 (5.2–15.0) for the low-dose group and 8.6 (5.3–15) for the high-dose group. Repeat INR measurements occurred after PCC and again if FFP was transfused. Twenty patients had samples frozen for analysis of FII, VII, IX and X with a mean time between PCC infusion and sample draw of 2 hours (0.5–8.1). Ten of these were stable at the time of PCC infusion and were used to calculate relative factor recovery. The INR corrected (decreased to ≤3) in 55%(6/11) of cases following treatment with low-dose PCC, while high-dose PCC corrected the INR in 43%(3/7). Combination of PCC and FFP (mean 2 units, ~5–7 mL/kg) corrected the INR in 89% (16/18) and 87%(13/15) of cases for low and high-dose PCC, respectively. PCC dose, with or without FFP, had no effect on the likelihood of INR correction (Chi-square, p> 0.05). The addition of low dose FFP, however, significantly increased the response rate (Chi-square, p<0.05) for both doses. The average factor increment is summarized in Table 1. Differences in factor levels between the PCC and PCC plus FFP groups were not significant(ANOVA, p>0.05). Based on PCC dose the median recovery of factor IX was 100% with a median recovery for FII, VII and X of 168%, 32%, and 100% of the factor IX increment. When FFP was added to the treatment regimen the recovery of factor IX was 106% of the PCC dose. FII, VII, and X were 182%, 46%, and 119% of the FIX increment. Only FVII recovery was significantly higher in the PCC plus FFP group (Mann-Whitney, p< 0.05). In conclusion, treatment with Profilnine increases factor levels compatible with the manufacturer’s insert, but PCC plus FFP causes a larger FVII increment. Treatment with low or high dose PCC results in similar rates of INR correction. However, addition of FFP increases the rate of INR correction for both doses. Profilnine alone is, therefore, unable to reliably correct a supratherapeutic INR, and supplementation with small amounts of FFP is necessary to provide additional FVII. A PCC product with a higher content of FVII is a better therapeutic option but is not readily available in the United States. Factor increments following PCC infusion INR F II(%) F VII(%) F IX(%) F X(%) mean±SD PCC only Pre 8.3±4.5 11±10 7±7 10±10 6±3 Post 2.6±1.4 53±21 14±10 28±19 31±12 PCC plus FFP Pre 12.2±5.0 5±1 1±1 12±19 12±19 Post 1.9±0.8 76±28 20±12 45±22 53±19
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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 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".