Preintervention imaging and intraoperative management care of the hypertrophic obstructive cardiomyopathy patient
Bibliographic record
Abstract
With an estimated overall mortality of less than 1 percent per year, hypertrophic cardiomyopathy, is the most common genetic cardiomyopathy. Intraoperative transesophageal echocardiography is the standard of care for assessing patients with hypertrophic obstructive cardiomyopathy undergoing surgical septal myectomy, allowing surgical planning, intraoperative hemodynamic monitoring, and postprocedural assessment of the repair, including detection of immediate complications. At various phases during surgical septal myectomy, the changing hemodynamic conditions may lead to worsening or improvement in left ventricle outflow tract obstruction by change in preload or afterload, systolic anterior motion of the mitral valve, or sympathetic stimulation. These characteristics represent unique challenges in the management of these patients, requiring a comprehensive understanding of the management of all the conditions required to decrease the left ventricle outflow tract gradient avoiding obstruction, which include the maintenance of sinus rhythm, adequate rate avoiding tachycardia and bradycardia, and avoidance of systemic hypotension preserving preload and afterload, with adequate vasoactive agents. The aim of this review is to summarize the perioperative assessment and management of patients undergoing hypertrophic obstructive myopathy surgery.
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 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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 0.001 |
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".