Improved Arterial Oxygenation with Biologically Variable or Fractal Ventilation Using Low Tidal Volumes in a Porcine Model of Acute Respiratory Distress Syndrome
Bibliographic record
Abstract
We compared biologically variable ventilation (V (bv); n = 9) with control mode ventilation (V (c); n = 8) at low tidal volume (VT)--initial 6 ml/kg--in a porcine model of acute respiratory distress syndrome (ARDS). Hemodynamics, respiratory gases, airway pressures, and VT data were measured. Static P-V curves were generated at 5 h. Interleukin (IL)-8 and IL-10 were measured in serum and tracheal aspirate. By 5 h, higher Pa(O(2)) (173 +/- 30 mm Hg versus 119 +/- 23 mm Hg; mean +/- SD; p < 0.0001 group x time interaction [G x T]), lower shunt fraction (6 +/- 1% versus 9 +/- 3%; p = 0.0026, G x T) at lower peak airway pressure (21 +/- 2 versus 24 +/- 1 cm H(2)O; p = 0.0342; G x T) occurred with V (bv). IL-8 concentrations in tracheal aspirate and wet:dry weight ratios were inversely related; p = 0.011. With V (c), IL-8 concentrations were 3.75-fold greater at wet:dry weight ratio of 10. IL-10 concentrations did not differ between groups. In both groups, ventilation was on the linear portion of the P-V curve. With V (bv), VT variability demonstrated an inverse power law indicating fractal behavior. In this model of ARDS, V (bv) improved Pa(O(2)) at lower peak airway pressure and IL-8 levels compared with V (c).
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 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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| 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".