Effect of Different Levels of Pressure Support and Proportional Assist Ventilation on Breathing Pattern, Work of Breathing and Gas Exchange in Mechanically Ventilated Hypercapnic COPD Patients with Acute Respiratory Failure
Bibliographic record
Abstract
BACKGROUND: Proportional assist ventilation (PAV) has been shown to maintain better patient-ventilator synchrony than pressure support ventilation (PSV); however, its clinical advantage regarding invasive ventilation of COPD patients has not been clarified. OBJECTIVES: To compare the effect of PAV and PSV on respiratory parameters of hypercapnic COPD patients with acute respiratory failure (ARF). METHODS: Nine intubated hypercapnic COPD patients were placed on the PAV or PSV mode in random sequence. For each mode, four levels (L1-L4) of support were applied. At each level, blood gases, flow, tidal volume (VT), airway pressure (Paw), esophageal pressure (Pes) (n = 7), patient respiratory rate (fp), ventilator rate (fv), missing efforts (ME = fp - fv) were measured. RESULTS: We found increases in ME with increasing levels of PSV but not with PAV. PO2 and VT increased whereas PCO2 decreased significantly with increasing levels of PSV (p < 0.05). With PAV, PCO2 decreased and VT increased significantly only at L4 whereas PO2 increased from L1 to L4. Runaways were observed at L3 and L4 of PAV. The pressure-time product (PTP) was determined for effective and missing breaths. The mean total PTP per minute (of effective plus missing breaths) was 160 +/- 57 cm H2O/s.min in PSV and 194 +/- 60 cm H2O/s.min in PAV. CONCLUSION: We conclude that in COPD patients with hypercapnic ARF, with increasing support, PSV causes the appearance of ME whereas PAV develops runaway phenomena, due to the different patient-ventilator interaction; however, these do not limit the improvement of blood gases with the application of both methods.
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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 | 0.001 | 0.002 |
| 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".