Air versus ground transport of major trauma patients to a tertiary trauma centre: a province-wide comparison using TRISS analysis.
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
OBJECTIVE: The purpose of this study was to compare the outcomes of adult (aged > 15 yr) blunt trauma patients with an Injury Severity Score (ISS) = 12 who were transported to a single tertiary trauma centre (TTC) by helicopter emergency medical service (HEMS) versus those transported by ground ambulance. METHODS: We retrospectively analyzed all adult (aged > 15 yr) trauma patients between March 27, 1998 and March 28, 2002 with an ISS score = 12, as identified through the provincial trauma registry. We used the Trauma and Injury Severity Score (TRISS) methodology to determine a difference in outcomes between the 2 groups. RESULTS: We identified 823 patients; of these, we excluded 32 (3.9%) penetrating trauma patients. Of the blunt trauma cases (n = 791) 237 (30%) patients were transported by air and 554 were transported by ground (70%). A total of 770 (97.3%) patients were eligible for TRISS analysis. Using the TRISS methodology, the air group had a Z statistic of 2.77, yielding a W score of 6.40. This compared with the ground transport group, whose Z statistic was 1.97 and W score was 2.39. CONCLUSION: The transport of trauma patients with an ISS = 12 by a provincially dedicated rotor wing air medical service was associated with statistically significantly better outcomes than those transported by standard ground ambulance. This is the first large Canadian study to specifically compare the outcome of patients transported by ground with those transported by air.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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