Pulmonary hemodynamics and lung surgery: a narrative review
Bibliographic record
Abstract
Background and Objective: Lung cancer represents the leading cause of death from cancer. In suitable patients, lung resection surgery provides the highest chance of cure and thus it is one of the most commonly performed thoracic surgeries. Lung resection surgeries, including lobectomy and pneumonectomy are associated with high rates of cardiopulmonary complications. These complications may cause long-term morbidity which can be unrelated to the degree of lung function reduction. In particular, these sequelae could be due to cardiac impairment. These complications must be taken into consideration in the management of patients. The aim of the presented narrative review is to revisit the anatomy, the physiologic considerations of the right ventricle and pulmonary artery unit as well as the pre-operative hemodynamic and functional evaluation to understand the impact of one-lung ventilation and lung resection on pulmonary hemodynamics.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.006 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".