Bibliographic record
Abstract
During cardiopulmonary resuscitation (CPR), chest compressions are critical for augmenting cardiac output, primarily through left ventricular (LV) compression. However, achieving optimal compression without direct visualization can be challenging. Point of care transesophageal echocardiography (TEE) serves as an invaluable tool for real-time guidance, ensuring accurate chest compression positioning over the LV apex. In this case, initial compressions were misaligned over the left ventricular outflow tract (LVOT) and aortic valve (AV). TEE assessment enabled real-time identification and precise repositioning of compressions to the LV apex, resulting in marked improvements in arterial pressure waveforms and end-tidal CO2 (ETCO2)—both reliable indicators of CPR quality. This case highlights the critical role of TEE in cardiac arrest management, offering real-time diagnostic insights and optimizing compression mechanics. Integrating TEE into resuscitation protocols enhances the quality of chest compressions, supports hemodynamic stability, and may ultimately improve patient outcomes.
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.
How this classification was reachedexpand
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) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".