Utilization of FAST (Focused Assessment with Sonography for Trauma) in 1999: Results of a Survey of North American Trauma Centers
Bibliographic record
Abstract
Although much has been written about FAST (Focused Assessment with Sonography for Trauma) in the last decade little is known about its present clinical utilization. The purpose of this study was to evaluate and characterize the contemporary utilization of FAST at trauma centers in the United States and Canada. In 1999 trauma directors or their delegates at Level I regional trauma centers in the United States and Canada were surveyed either by fax or phone regarding the present utilization and the future of FAST at their center. The overall survey response rate was 91 per cent with 96 of 105 centers completing the survey. Of the 96 centers surveyed 78 were in the United States and 18 were in Canada. Of the 78 U.S. centers surveyed 62 (79%) routinely use FAST, and it is done by surgeons in 39 per cent, surgeons and emergency departments in 21 per cent, emergency departments in 5 per cent, and radiologists in 35 per cent. Most centers (79%) thought that it sped up their workups, and 89 per cent said it was an advance in patient care. FAST is used in penetrating injury at 58 per cent of centers, and some centers use FAST to assess organ injury. The utilization of diagnostic peritoneal lavage and CT has markedly decreased at many centers. Almost all respondents thought that FAST should be a component of surgery resident training. The utilization of FAST is significantly less in Canada than in the United States (P < 0.05). Our conclusions are the following. FAST has become routinely used at the majority of the U.S. centers surveyed. FAST is performed by clinicians at 65 per cent of the trauma centers surveyed. The utilization of CT and diagnostic peritoneal lavage has changed. Many centers have broadened the scope of FAST to include the assessment of organ, pediatric, and penetrating injury.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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".