High positive end-expiratory pressure levels promote bacterial translocation in experimental pneumonia
Bibliographic record
Abstract
OBJECTIVE: A previous study in piglets with experimental pneumonia showed that reducing atelectasis by means of open lung ventilation attenuated bacterial translocation compared to conventional ventilation settings. This study examined the effect of open lung ventilation with higher than necessary positive end-expiratory pressures (PEEP) on bacterial translocation. DESIGN AND SETTING: Prospective animal study in a university-affiliated research laboratory. SUBJECTS: Thirty piglets. INTERVENTIONS: Animals were surfactant-depleted by whole-lung lavage and infected with group B streptococci. Thereafter the animals were ventilated for 5 h according to either a conventional ventilation strategy, open lung strategy, or open lung/high-PEEP strategy. Blood samples for blood gas analysis and blood bacterial counts were taken every hour. After 5 h of ventilation surviving animals were killed, and lung colony forming units and lung mechanics parameters were determined. RESULTS: All animals in both open lung groups survived but only 30% of those in the conventional ventilation group. Open lung ventilation resulted in significantly less bacterial translocation than either conventional or high-PEEP ventilation. Lung function in the conventional ventilated group was significantly less than in the two open lung groups. CONCLUSIONS: The lowest level of bacterial translocation was observed during optimal ventilation (open lung) which was achieved by using individually tailored settings. Deviation to either side can be harmful, as shown by the increased bacterial translocation during conventional and high-PEEP ventilation.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.000 | 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".