Effects of two alveolar recruitment manoeuvres (sustained inflation and stepwise) followed by positive end-expiratory pressure on cardiac output (measured with lithium dilution), invasive blood pressure and arterial oxygen tension in isoflurane-anaesthetised goats
Bibliographic record
Abstract
Alveolar recruitment manoeuvres (ARM) performed during general anaesthesia improve oxygenation; however cardiovascular depression may be observed. The aim of the study was to compare the effects of sustained inflation (SI) and stepwise ARMs on cardiac output (CO), mean arterial blood pressure and arterial oxygen tension (PaO2) in ten mechanically ventilated goats anaesthetised with isoflurane. In the SI ARM, peak inspiratory presure (PIP) was increased to 30 cmH2O and sustained for 20 s. In the stepwise ARM, the PIP was increased by 5 cmH2O each minute for three minutes from 10 to 25 cmH2O. Both ARMs were followed by positive end-expiratory pressure of 5 cmH2O. Paired lithium dilution CO measurements and arterial blood samples were obtained before and after each ARM. The order of the ARM was randomised and each goat was subjected to both techniques. Data was reported as median and interquartile range (IQR). Significance was set at 0.05. The median change in CO (measured by subtracting values after and before ARM) was −0.15 L min−1 (IQR -0.51; 0.03) and − 0.90 L min−1 (IQR -1.69; −0.58) for SI and stepwise ARM respectively (p = 0.04). The median change in PaO2 was 3 kPa (IQR -2.7; 7.6) and 0.4 kPa (IQR -3.4; 5.5) for SI and stepwise ARM respectively (p = 0.03). In conclusion, SI ARM causes less impact on CO and provides a better improvement in PaO2 compared to stepwise ARM in goats.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 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".