Case Report: Posterior Thoracic Window in the Presence of Pleural Effusion in Critical Care Medicine: One More Chance to Image the Aortic Valve
Bibliographic record
Abstract
Good quality echocardiographic images in the setting of critical care medicine may be difficult to obtain for many reasons. We present a case of an 85-year-old woman with acute pulmonary edema and pleural effusion, where transthoracic bedside echocardiographic examination raised a suspicion for significant aortic valve disease. However, given the orthopneic decubitus of the patients, the quality of images was poor. To increase the accuracy of diagnosis, a posterior thoracic view through the pleural effusion in the sitting position was used. This view allowed the diagnosis of mixed aortic valve disease (aortic stenosis and regurgitation) and the quantification of valve disease through multiparametric criteria as recommended by current guidelines. The posterior thoracic view, when feasible, may provide a useful option in the assessment of cardiac structures and further diagnostic information in technically difficult echocardiographic examinations.
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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 | 0.001 | 0.007 |
| Meta-epidemiology (narrow) | 0.003 | 0.002 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.015 | 0.008 |
| Insufficient payload (model declined to judge) | 0.004 | 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".