Recombinant activated factor VII in the treatment of non‐haemophilia patients: physician under‐reporting of thromboembolic adverse events
Bibliographic record
Abstract
The objective of this study was to determine if clinically important thromboembolic adverse events (TAEs) because of recombinant activated factor VII (rFVIIa) administration are being under-reported. rFVIIa is a potent haemostatic agent with a short half-life of 2.6 h that is increasingly used in 'off-label' situations. Retrospective review of 94 patients who received rFVIIa during 1 January 2003 to 30 June 2007 was carried out at a tertiary care centre. Sixty-nine patients, 32 females and 37 males, mean age 55 years (18-84 years), satisfied study criteria of off-label usage. This was a high-risk population with 33 (48%) deaths. A mean dose of 8.2 mg (2.4-19.2 mg) was administered in two average divided doses. Thirty-six potential TAEs were identified in 29 patients, and of these, 12 patients had TAEs deemed to be rFVIIa related and were identified on average 8.8 days after exposure to rFVIIa. Forty-eight (70%) physician questionnaires were completed; however, no TAEs were reported in these questionnaires or on chart review. Potential clinically significant TAEs are being under-reported by treating physicians. Until further evidence, we suggest the urgent need to develop consensus recommendations for utilization and required follow up to monitor the safety of rFVIIa and that at a minimum, all use of rFVIIa should be regulated through a gate-keeping mechanism that ensures adherence to these policies. Furthermore, prospective registries and trials are necessary to evaluate the efficacy and safety of rFVIIa in off-label settings.
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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 | 0.004 | 0.024 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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".