Recombinant factor VIIa for intractable blood loss after cardiac surgery: a propensity score–matched case‐control analysis
Why this work is in the frame
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Bibliographic record
Abstract
BACKGROUND: Cardiac surgery is occasionally complicated by massive blood loss that is refractory to standard hemostatic interventions. Recombinant factor VIIa (rF-VIIa) is being increasingly used as rescue therapy in such cases, but little information is available on its safety and efficacy for this indication. STUDY DESIGN AND METHODS: The outcomes of the first 51 cardiac surgery patients who received rF-VIIa for intractable blood loss (from November 2002 to February 2004) at a single institution according to a standardized clinical guideline were compared to 51 matched control patients, with the control patients identified from a large database and matched based on the propensity for massive blood loss. RESULTS: Blood loss and blood product usage were significantly decreased after 2.4 to 4.8 mg of rF-VIIa. In those treated after sternal closure (n = 32), there was a significant reduction in blood loss from the hour before to the hour after treatment: 100 (70, 285) mL (median [25th, 75th percentiles]; p < 0.0001). Except for a slower postoperative recovery and higher incidence of acute renal dysfunction, the adverse event rates were similar between the rF-VIIa-treated patients and their matched controls. CONCLUSIONS: These results suggest that rF-VIIa may be an effective rescue therapy for patients with intractable hemorrhage after cardiac surgery. A clinically important risk of stroke or other major thrombotic complications could not be ruled out by our study. Controlled clinical trials with adequate power to detect the impact of rF-VIIa therapy on morbidity and mortality therefore are necessary before one can recommend its routine use in patients undergoing cardiac surgery who have excessive bleeding.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.000 | 0.001 |
| 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) | 0.000 | 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 it