Outcome of major cardiac injuries at a Canadian trauma center
Bibliographic record
Abstract
BACKGROUND: Canadian trauma units have relatively little experience with major cardiac trauma (disruption of a cardiac chamber) so injury outcome may not be comparable to that reported from other countries. We compared our outcomes to those of other centers. METHODS: Records of patients suffering major cardiac trauma over a nine-year period were reviewed. Factors predictive of outcome were analyzed. RESULTS: Twenty-seven patients (11 blunt and 16 penetrating) with major cardiac trauma were evaluated. Injury severity scores (ISS) were similar for blunt (49.6 +/- 16.6) and penetrating (39.5 +/- 21.6, p = 0.20) injuries. Five of 11 blunt trauma patients, and 9 of 16 penetrating trauma patients, had detectable vital signs on hospital arrival (p = 0.43). Ten patients underwent emergency department thoracotomy and 11 patients had cardiac repair in the operating theatre. Eleven patients survived and 16 died. Survivors had a lower ISS (33.7 +/-15.4) than non-survivors (50.4 +/- 20.4; p = 0.03). Two of 11 blunt trauma patients and 9 of 16 penetrating trauma patients survived (p = 0.06). Eleven of 14 patients with detectable vital signs survived; all 13 without detectable vital signs died (p = 0.00003). Ten of eleven patients treated in the operating theatre survived, while only one of the other 16 patients survived (p = 0.00002). CONCLUSIONS: Patients with major cardiac injuries and detectable vital signs on hospital arrival can be salvaged by prompt surgical intervention in the operating theatre. Major cardiac injuries are infrequently encountered at our center but patient survival is comparable to that reported from trauma units in other countries.
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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 | 0.000 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".