Anesthesia and Hemodynamic Management for Lung Transplantation
Bibliographic record
Abstract
This chapter discusses the key preoperative considerations, intraoperative management strategies for lung transplantation as it pertains to induction of anesthesia, airway management, hemodynamic management, and postoperative analgesic strategies, with a review of the evidence. If a patient is deemed a candidate for lung transplantation, they are assigned a lung allocation score which determines their position on the waitlist. Patients undergo comprehensive imaging and laboratory testing prior to being listed. The cardiovascular status of the patient, particularly reduced cardiac index and increased pulmonary artery pressures, help define the urgency of transplantation and may predict hemodynamic instability and necessity for mechanical circulatory support. Maintaining hemodynamic stability on induction is the goal for all surgical procedures; however, this goal may be particularly challenging to achieve in the end-stage lung disease patient population. Maintenance of general anesthesia during lung transplantation can be achieved with inhaled volatile anesthetics or with total intravenous anesthesia, or a combination of both.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".