Dose Modulation, Body Mass Index, and Computed Tomography Air Trapping
Bibliographic record
Abstract
Considering these findings, diaphragm activity during expiration, measured with the Pdi at the quartiles of expiration and the pressure-time product during expiration, would have been slightly higher, on average, if expiratory cycling had been perfectly matched.Thus, we likely underestimated the "neural" expiratory diaphragm recruitment by defining expiration on the basis of flow in our patients.The extent of underestimation is difficult to estimate and would have been balanced to some degree by the patients in which neural diaphragm activation was overestimated.Nevertheless, our data reflect the degree of diaphragm activity during expiration in a real-world scenario, where expiratory cycling asynchronies are common.Moreover, the imperfect neuromechanical coupling likely contributed to the higher magnitude of negative work and active lengthening found in the critically ill patients, especially in the breaths with premature cycling.The current hypothesis is that diaphragm injury is caused by the mechanical effects of imperfect cycling and expiratory diaphragm recruitment (i.e., by active lengthening/eccentric contractions) and not by the neuromechanical uncoupling per se (4, 5).Our retrospective study was thus better suited to study the mechanical impact of expiratory diaphragm recruitment and not the neural basis for its occurrence.Future studies are required to assess the neuromechanical coupling of expiration in critically ill patients and especially to further evaluate the hypothesis that the diaphragm is recruited during expiration to prevent lung collapse (6).These studies should consider several factors.First, studies should use the electrical activity of the diaphragm (Edi) to assess the duration of neural inspiration and expiration, because Edi is a much more direct measurement of the respiratory center output than Pdi (7).Alas, Edi was available only in a subset of patients in our cohort, in whom the catheter was already in situ.Second, studies should standardize the cycling criteria and systematically adjust positive end-expiratory pressure and FI O 2 settings, which was not the goal of our original study (8).Third, a better definition of the end of neural inspiration and the start of neural expiration is required.The "start of the rapid decline" in either Edi or Pdi is rather subjective (7) and is not based on the actual activity in the respiratory centers as far as we know.Choosing peak Edi as the end of inspiration will mean that there is always diaphragm activity during expiration (6).This discussion underlines that we should further investigate the physiology of breathing in ventilated patients, especially the impact of ventilator settings on neuromechanical coupling and lengthening activations of the diaphragm.We thank Akoumianaki and colleagues for starting this discussion.
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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 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.014 | 0.011 |
| Insufficient payload (model declined to judge) | 0.003 | 0.002 |
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".