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Obesity Modifies the Effect of Peep on Mechanics of Breathing in Acute Hypoxemic Respiratory Failure

2025· article· en· W4410276560 on OpenAlexaff
Bryan Kozdas, Ewan C. Goligher, José Dianti

Bibliographic record

VenueAmerican Journal of Respiratory and Critical Care Medicine · 2025
Typearticle
Languageen
FieldMedicine
TopicRespiratory Support and Mechanisms
Canadian institutionsToronto General HospitalUniversity of Toronto
Fundersnot available
KeywordsMedicineAcute respiratory failureRespiratory physiologyCardiologyRespiratory systemBreathingIntensive care medicineInternal medicineAnesthesiaMechanical ventilation

Abstract

fetched live from OpenAlex

Abstract Rationale: Obesity has detrimental effects on the respiratory system—including decreased tidal volume and lung compliance, and increased atelectasis and work of breathing. These effects are especially pronounced in patients who are sedated and mechanically ventilated. The effect of obesity on spontaneous breathing effort and lung-distending pressure in acute hypoxemic respiratory failure (AHRF) is unknown. This study aims to establish the effects of obesity on respiratory mechanics during spontaneous breathing and the success of a lung- and diaphragm-protective ventilation strategy in patients with AHRF. Methods: This is a secondary analysis of a randomized cross-over trial that tested various interventions on lung-distending pressure and respiratory effort in an attempt to achieve lung- and diaphragm-protective (LDP) targets to treat invasively mechanically ventilated patients with AHRF. Ventilation and sedation were titrated to achieve moderate respiratory effort and safe lung-distending pressures at lower and higher PEEP levels (applied in random order). High PEEP was defined as end-expiratory transpulmonary pressure of 0-2 cm H2O. Low PEEP was defined as the lowest tolerable level (FiO2 ≤0.9). Bayesian statistical methods were used to assess the influence of BMI on the selected PEEP, the proportion of success in achieving LDP targets, esophageal pressure swings, and dynamic transpulmonary pressure. Results: BMI modified the effect of increasing PEEP on the probability of achieving LDP targets (posterior probability of interaction: 99%; see figure). In patients with a BMI≥30, the probability of achieving LDP targets was greater when applying higher PEEP compared to lower PEEP (median posterior probability 100% vs 21%). In patients with a BMI<30, the probability of achieving LDP targets was lower at higher PEEP compared to lower PEEP (median posterior probability 40% vs. 87%). In patients with BMI ≥30, esophageal pressure swing was lower under high PEEP conditions (median -9 cm H2O, IQR -10 − -7) compared with low PEEP conditions (median -10 cm H2O, IQR -14 − -7); transpulmonary pressure swing was also lower under high PEEP conditions (median 15 cm H2O, IQR 14−17) compared with low PEEP conditions (median 19 cm H2O, IQR 13−21). Patients with BMI≥30 required more PEEP to achieve the high PEEP target: in patients with BMI≥30, PEEP was a median of 16 cm H2O (IQR 14−17); in patients with BMI<30, PEEP was a median of 14 cm H2O (IQR 12−14). Conclusion: Patients with higher body mass index may require high PEEP to achieve lung- and diaphragm-protective targets for spontaneous breathing in AHRF.

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 machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.005
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.029

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.000
Science and technology studies0.0000.001
Scholarly communication0.0010.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.012
GPT teacher head0.309
Teacher spread0.297 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

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

Citations0
Published2025
Admission routes1
Has abstractyes

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