Individualizing Intraoperative Ventilation: Comment
Bibliographic record
Abstract
We read with great interest the article by Pereira et al.1 in a recent issue of Anesthesiology. The authors explore electrical impedance tomography–based determination of an individualized positive end-expiratory pressure level to simultaneously limit both atelectasis and overdistension in mechanically ventilated patients during general anesthesia. While atelectasis is a well-recognized consequence of mechanical ventilation during general anesthesia, some authors previously considered overdistension as a non–clinically significant problem in the operating room.2 We congratulate the authors for presenting data that challenge this assumption.However, we feel that the authors omitted proper discussion of the discrepancy between their study and two other recent studies that failed to show a difference in postoperative atelectasis when assessed shortly after extubation.3,4 While Pereira et al. are to be commended for using computed tomography, the reference imaging technique, to assess the amount of atelectasis postextubation, we wonder why the authors have chosen a −200 to +100 Hounsfield units interval to define nonaerated lung. In the reference quoted to explain their methodology,5 atelectasis was defined as −100 to +100 Hounsfield units, as in numerous other publications.6–8 To rule out the possibility of a classification bias, the authors should have analyzed their results using the generally accepted reference values for both poorly aerated (−500 to −100 Hounsfield units) and nonaerated (–100 to +100 Hounsfield units) lung. Moreover, they should have reported the degree of atelectasis in square centimeters, as used in their sample size calculation, to eliminate the presumption of a reporting bias. We write to request that the authors report results both in square centimeters, as well as according to the generally accepted Hounsfield units reference values to address these potential biases.Finally, provided the aforementioned concerns are properly addressed, Pereira et al.’s work is a crucial piece of information, as the primary mechanism by which lung protective ventilation is thought to decrease postoperative pulmonary complication is through the successful decrease in postoperative atelectasis.9 The authors weaned their patients using the pressure-support mode maintaining the same intraoperative positive end-expiratory pressure level contrary to the other studies. Interestingly, weaning using assisted ventilatory modes is seldomly performed in the operating room while it is a commonly performed procedure in the intensive care unit. This cointervention might explain this trial’s observed difference in postoperative atelectasis. We would also welcome comments from the authors about their choice of weaning method.The authors declare no competing interests.
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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 | 0.024 | 0.154 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.003 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.009 |
| Open science | 0.008 | 0.003 |
| Research integrity | 0.035 | 0.056 |
| Insufficient payload (model declined to judge) | 0.008 | 0.008 |
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".