2014 Consensus conference on viscoelastic test–based transfusion guidelines for early trauma resuscitation
Bibliographic record
Abstract
There has been an increased interest in the use of viscoelastic testing to guide blood product replacement during the acute resuscitation of the injured patient. Currently, no uniformly accepted guidelines exist for how this technology should be integrated into clinical care. In September 2014, an international multidisciplinary group of leaders in the field of trauma coagulopathy and resuscitation was assembled for a 2-day consensus conference in Philadelphia, Pennsylvania. This panel included trauma surgeons, hematologists, blood bank specialists, anesthesiologists, and the lay public.Nine questions regarding the impact of viscoelastic testing in the early resuscitation of trauma patients were developed before the conference by panel consensus. Early use was defined as baseline viscoelastic test result thresholds obtained within the first minutes of hospital arrival-when conventional laboratory results are not available. The available data for each question were then reviewed in person using standardized presentations by the expert panel. A consensus summary document was then developed and reviewed by the panel in an open forum. Finally, a two-round Delphi poll was administered to the panel of experts regarding viscoelastic thresholds for triggering the initiation of specific treatments including fibrinogen, platelets, plasma, and prothrombin complex concentrates. This report summarizes the findings and recommendations of this consensus conference.
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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 | 0.097 | 0.114 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.006 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.005 | 0.004 |
| Open science | 0.009 | 0.007 |
| Research integrity | 0.012 | 0.016 |
| Insufficient payload (model declined to judge) | 0.008 | 0.006 |
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".