Investigation of myocardial contusion with sternal fracture in the emergency department: multicentre review.
Bibliographic record
Abstract
OBJECTIVE: To describe the use of initial electrocardiogram (ECG), follow-up ECG or equivalent monitoring, and troponin I in patients presenting with sternal fracture who are assessed in emergency departments or by front-line physicians. DESIGN: Multicentre descriptive retrospective study. SETTING: Two traumatology teaching centres in Quebec city, Que. PARTICIPANTS: Fifty-four trauma patients presenting with sternal fracture. INTERVENTIONS: Assessment of the use of initial ECG, ECG or equivalent monitoring 6 hours after trauma, and troponin administration. MAIN OUTCOME MEASURES: In terms of ECG use, quality comparison criteria were selected on the basis of expert opinions in 4 studies. An initial ECG and a follow-up ECG 6 hours after trauma or cardiac monitoring 6 hours after trauma were recommended by most authors for diagnosing myocardial contusion in cases of sternal fracture. Serum troponin I administered 4 to 8 hours after chest trauma was also recommended by some as an effective means of detecting substantial arrhythmia secondary to myocardial contusion. Descriptive univariate analyses and tests were performed. A P < .05 was considered significant. RESULTS: Thirty-nine patients (72%) were assessed initially with ECGs; after 6 hours in the emergency department, 18 of these patients (33%) had follow-up ECGs or equivalent cardiac monitoring. Sixteen patients (30%) were assessed by means of troponin I dosage. Two patients (4%) presented with ECG abnormalities and only 1 patient (2%) presented with an elevated troponin I level. CONCLUSION: Emergency physicians must increase their use of ECG in initial or follow-up diagnosis for trauma patients presenting with sternal fracture to detect myocardial contusion and arrhythmia. The use of troponin in conjunction with ECG is also suggested for this population in order to identify patients at risk of complications secondary to myocardial contusion.
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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 | 0.002 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.001 | 0.000 |
| 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".