An evaluation of echo in life support (ELS): is it feasible? What does it add?
Bibliographic record
Abstract
BACKGROUND: Emergency physicians were trained to perform echo in life support (ELS)--that is, limited transthoracic echocardiography during advanced life support (ALS) management of cardiac arrest. METHODS: Data were collected on the adequacy of views obtained and timing of the scan, as well as the clinical findings of pericardial effusion and ventricular wall motion. Any intervention performed as a result of the scan was also noted. ELS was performed on 50 patients during cardiac arrest. RESULTS: Adequate views were obtained in 47 (94%) scans, and 45 (90%) were obtained within the 10 s rhythm check. Twenty patients (40%) had ventricular wall motion (VWM), three (6%) had pericardial effusions and six patients (12%) had an intervention performed as a direct result of the scan. These included pericardiocentesis, thrombolysis and insertion of a chest drain. The presence of VWM had a positive predictive value of 55%. The absence of VWM resulted in a negative predictive value of 97% for predicting return of spontaneous circulation (ROSC). CONCLUSION: It is concluded that ELS is feasible and that the scan findings may guide further interventions.
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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 | 0.009 | 0.066 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.002 | 0.007 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.002 |
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".