The Use of High Frequency Percussive Ventilation (HFPV) in Postoperative Cardiac Surgery Patients Significantly Improves Gas Exchange without Impairment of Hemodynamics
Bibliographic record
Abstract
OBJECTIVE: Respiratory failure represents a significant source of morbidity and mortality for surgical patients. High-frequency percussive ventilation (HFPV) is emerging as a potentially effective rescue therapy in patients failing conventional mechanical ventilation (CMV). Use of HFPV is often limited by concerns for potential effects on hemodynamics, which is particularly tenuous in patients immediately after cardiac surgery. In this manuscript we evaluated the effects of HFPV on gas exchange and cardiac hemodynamics in the immediate postoperative period after cardiac surgery, in comparison with CMV. METHODS: Twenty-four consecutive cardiac surgery patients were ventilated in immediate postoperative period with HFPV for two to four hours, then they switched to a CMV using the adaptive support ventilation mode for weaning. Arterial blood gases were performed during the first and second hour on HFPV, and at 45 minutes after initiation of CMV. Respiratory settings and invasive hemodynamic data (mixed venous oxygen saturation, central venous pressure, systemic and pulmonary blood pressure, cardiac output and index) were collected utilizing right heart pulmonary catheter and arterial lines during HFPV and CMV. Primary outcome was improvement in the ratio between partial pressure of oxygen to fraction of inspired oxygen (P/F ratio) and changes in hemodynamics. RESULTS: < 0.05), suggesting much better gas exchange on HFPV than on CMV. Hemodynamics were not affected by the mode of the ventilation. CONCLUSIONS: Improvement in gas exchange, reflected in a significantly improved P/F ratio, wasn't accompanied by worsening in hemodynamic parameters. The significant gains in the P/F ratio were lost when patients were switched to conventional ventilation. This data suggest that HFPV provides significantly better gas exchange compared with CMV and can be safely utilized in postoperative cardiac patients without any significant effect on hemodynamics.
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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 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 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".