Tidal lung hysteresis to interpret PEEP-induced changes in compliance in ARDS patients
Bibliographic record
Abstract
Abstract Background In ARDS, the PEEP level associated with the best respiratory system compliance is often selected; however, intra-tidal recruitment can increase compliance, falsely suggesting improvement in baseline mechanics. Tidal lung hysteresis increases with intra-tidal recruitment and can help interpreting changes in compliance. This study aims to assess tidal recruitment in ARDS patients and to test a combined approach, based on tidal hysteresis and compliance, to interpret decremental PEEP trials. Methods A decremental PEEP trial was performed in 38 COVID-19 moderate to severe ARDS patients. At each step, we performed a low-flow inflation-deflation manoeuvre between PEEP and a constant plateau pressure, to measure tidal hysteresis and compliance. Results According to changes of tidal hysteresis, three typical patterns were observed: 10 (26%) patients showed consistently high tidal-recruitment, 12 (32%) consistently low tidal-recruitment and 16 (42%) displayed a biphasic pattern moving from low to high tidal-recruitment below a certain PEEP. Compliance increased after 82% of PEEP step decreases and this was associated to a large increase of tidal hysteresis in 44% of cases. Agreement between best compliance and combined approaches was accordingly poor (K = 0.024). The combined approach suggested to increase PEEP in high tidal-recruiters, mainly to keep PEEP constant in biphasic pattern and to decrease PEEP in low tidal-recruiters. PEEP based on the combined approach was associated with lower tidal hysteresis (92.7 ± 20.9 vs. 204.7 ± 110.0 mL; p < 0.001) and lower dissipated energy per breath (0.1 ± 0.1 vs. 0.4 ± 0.2 J; p < 0.001) compared to the best compliance approach. Tidal hysteresis ≥ 100 mL was highly predictive of tidal recruitment at next PEEP step reduction (AUC 0.97; p < 0.001). Conclusions Assessment of tidal hysteresis improves the interpretation of decremental PEEP trials and may help limiting tidal recruitment and energy dissipated into the respiratory system during mechanical ventilation of ARDS patients.
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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 | 0.002 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 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".