Anaphylaxis and cardiac surgery for hypertrophic obstructive cardiomyopathy: a case report and review of anaesthetic management
Bibliographic record
Abstract
BACKGROUND: The aim of this paper is to describe clinical management in a situation where patient has experienced anaphylaxis while undergoing surgical septal myectomy for hypertrophic obstructive cardiomyopathy (HOCM). CASE REPORT: A 40-yr-old female was scheduled to undergo surgical septal myectomy for the treatment of HOCM. After induction, the patient developed refractory hypotension that did not respond to escalating doses of vasopressors and volume therapy. Although a clinical examination led to the diagnosis of anaphylaxis, epinephrine, which is the usual treatment of choice, failed to improve the patient's haemodynamics. A transesophageal echocardiography revealed a worsening of left ventricular outflow tract obstruction (LVOTO) after epinephrine administration. In the end, the rapid institution of a cardiopulmonary bypass was required as a rescue therapy instead of to save a patient. CONCLUSION: The anaesthetic goals in a patient in HOCM are to maintain preload and afterload and to avoid stimulation of inotropy and chronotropy to leading to left ventricular outflow obstruction. In a patient with anaphylaxis, maintaining these haemodynamic goals becomes much more difficult since the pathophysiology and usual treatment of choice will worsen LVOTO. Special consideration for the need to have extracorporeal life support to treat refractory hypotension in surgical patients with HOCM may be warranted.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.002 |
| 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".