Postoperative Management of Lung Transplant Recipients in the Intensive Care Unit
Bibliographic record
Abstract
The number of lung transplantations is progressively increasing worldwide, providing new challenges to interprofessional teams and the intensive care units. The outcome of lung transplantation recipients is critically affected by a complex interplay of particular pathophysiologic conditions and risk factors, knowledge of which is fundamental to appropriately manage these patients during the early postoperative course. As high-grade evidence-based guidelines are not available, the authors aimed to provide an updated review of the postoperative management of lung transplantation recipients in the intensive care unit, which addresses six main areas: (1) management of mechanical ventilation, (2) fluid and hemodynamic management, (3) immunosuppressive therapies, (4) prevention and management of neurologic complications, (5) antimicrobial therapy, and (6) management of nutritional support and abdominal complications. The integrated care provided by a dedicated multidisciplinary team is key to optimize the complex postoperative management of lung transplantation recipients in the intensive care unit.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".