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Record W4220685846 · doi:10.1097/aln.0000000000004193

Pressure Support Ventilation and Atelectasis: Comment

2022· letter· en· W4220685846 on OpenAlexaff
Cédrick Zaouter, Alex Moore, François Martin Carrier, Julie Girard, Martin Girard

Bibliographic record

VenueAnesthesiology · 2022
Typeletter
Languageen
FieldMedicine
TopicUltrasound in Clinical Applications
Canadian institutionsUniversité de MontréalMcGill University Health Centre
Fundersnot available
KeywordsMedicineAtelectasisPressure support ventilationVentilation (architecture)AnesthesiaIntensive care medicineMechanical ventilationInternal medicineLungMechanical engineering

Abstract

fetched live from OpenAlex

We read with great interest the article by Jeong et al.1 titled “Pressure Support versus Spontaneous Ventilation during Anesthetic Emergence—Effect on Postoperative Atelectasis: A Randomized Controlled Trial.” Although many studies have looked at the potential effects of various intraoperative open lung ventilation strategies on postoperative pulmonary outcomes, recent evidence suggests that their potential benefits may be limited if no action is taken to minimize lung derecruitment during the emergence period.2 Considering that postoperative atelectasis plays a central role in the development of postoperative pulmonary complications, and that maintaining positive pressure during emergence may help preserve lung aeration,3 the research question of Jeong et al. is of paramount importance. However, we have some concerns regarding key aspects of the study’s methodology.First, we were especially worried about elements used to define and measure the incidence of atelectasis, the study’s primary outcome. The authors’ definition (more than three lung sections with a non-zero atelectasis score) is not standard4 and has not been previously validated. Can the authors specify whether their definition was selected before conducting the study to reassure readers on the absence of data-driven threshold selection? Performing sensitivity analyses looking at different thresholds for the number of atelectatic lung sections necessary to classify the outcome would better assess the robustness of their findings.Second, we were puzzled to read that Jeong et al. not only used a modified and unvalidated echographic pulmonary aeration loss score5 but also introduced their own modifications, potentially further weakening the validity of their primary outcome classification. In particular, loss of lung sliding with lung pulse is not a sign of atelectasis but rather a sign of a well-aerated lung without ventilation. This finding could have indicated the presence of a mucous plug which may have been resolved after a simple coughing fit without causing any atelectasis. Including this sign in their atelectasis score seems problematic. We encourage the authors to use the lung ultrasound score, a validated echographic loss of aeration score, to report their results.6Third, their study was underpowered for their anticipated effect size. Using the same assumptions (an incidence of 53% in the control group and 37% in the intervention group for an absolute estimated effect of 16%), we calculated that a sample size of 302 patients would have been necessary even before considering a 15% dropout rate. Their greater-than-anticipated observed effect explains why their results achieved statistical significance. However, underpowered studies are prone to inflated results with positive results that are more likely to be false positives.7Fourth, the authors’ definition of hypoxemia, a secondary outcome, may lead to missing important clinical effects resulting from their intervention. A punctual event of oxygen saturation measured by pulse oximetry greater than 92% may be not be clinically significant in comparison with a prolonged postoperative need for high fractional inspired oxygen tension. Can the authors provide data on this secondary outcome using a time-weighted need for organ support, such as oxygen-free days or cumulative postoperative oxygen administration?The imaging study by Jeong et al. is an essential first step in clarifying the role of assisted ventilatory modes during anesthesia emergence. However, there is still a lot of work to be done to answer the salient question: Are assisted ventilatory modes an important part of an open lung strategy at emergence that may lead to a decreased incidence of postoperative pulmonary complications?Dr. Girard is a paid consultant for the point-of-care ultrasonography group of GE Healthcare (Milwaukee, Wisconsin). The other authors declare no competing interests.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Commentary · Consensus signal: Commentary
Teacher disagreement score0.039
Threshold uncertainty score0.997

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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.

Opus teacher head0.037
GPT teacher head0.317
Teacher spread0.280 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreCommentary

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".

Quick stats

Citations2
Published2022
Admission routes1
Has abstractyes

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