Body Habitus and Dynamic Surgical Conditions Independently Impair Pulmonary Mechanics during Robotic-assisted Laparoscopic Surgery
Bibliographic record
Abstract
BACKGROUND: Body habitus, pneumoperitoneum, and Trendelenburg positioning may each independently impair lung mechanics during robotic laparoscopic surgery. This study hypothesized that increasing body mass index is associated with more mechanical strain and alveolar collapse, and these impairments are exacerbated by pneumoperitoneum and Trendelenburg positioning. METHODS: This cross-sectional study measured respiratory flow, airway pressures, and esophageal pressures in 91 subjects with body mass index ranging from 18.3 to 60.6 kg/m2. Pulmonary mechanics were quantified at four stages: (1) supine and level after intubation, (2) with pneumoperitoneum, (3) in Trendelenburg docked with the surgical robot, and (4) level without pneumoperitoneum. Subjects were stratified into five body mass index categories (less than 25, 25 to 29.9, 30 to 34.9, 35 to 39.9, and 40 or higher), and respiratory mechanics were compared over surgical stages using generalized estimating equations. The optimal positive end-expiratory pressure settings needed to achieve positive end-expiratory transpulmonary pressures were calculated. RESULTS: At baseline, transpulmonary driving pressures increased in each body mass index category (1.9 ± 0.5 cm H2O; mean difference ± SD; P < 0.006), and subjects with a body mass index of 40 or higher had decreased mean end-expiratory transpulmonary pressures compared with those with body mass index of less than 25 (-7.5 ± 6.3 vs. -1.3 ± 3.4 cm H2O; P < 0.001). Pneumoperitoneum and Trendelenburg each further elevated transpulmonary driving pressures (2.8 ± 0.7 and 4.7 ± 1.0 cm H2O, respectively; P < 0.001) and depressed end-expiratory transpulmonary pressures (-3.4 ± 1.3 and -4.5 ± 1.5 cm H2O, respectively; P < 0.001) compared with baseline. Optimal positive end-expiratory pressure was greater than set positive end-expiratory pressure in 79% of subjects at baseline, 88% with pneumoperitoneum, 95% in Trendelenburg, and ranged from 0 to 36.6 cm H2O depending on body mass index and surgical stage. CONCLUSIONS: Increasing body mass index induces significant alterations in lung mechanics during robotic laparoscopic surgery, but there is a wide range in the degree of impairment. Positive end-expiratory pressure settings may need individualization based on body mass index and surgical conditions.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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".