Table 1_Computationally-directed mechanical ventilation in a porcine model of ARDS.docx
Background<p>Despite the implementation of protective mechanical ventilation, ventilator-induced lung injury remains a significant driver of ARDS-associated morbidity and mortality. Mechanical ventilation must be personalized and adaptive for the patient and evolving disease course to achieve...
Tallennettuna:
| Päätekijä: | |
|---|---|
| Muut tekijät: | , , , , , , , , , , , , |
| Julkaistu: |
2025
|
| Aiheet: | |
| Tagit: |
Lisää tagi
Ei tageja, Lisää ensimmäinen tagi!
|
| Yhteenveto: | Background<p>Despite the implementation of protective mechanical ventilation, ventilator-induced lung injury remains a significant driver of ARDS-associated morbidity and mortality. Mechanical ventilation must be personalized and adaptive for the patient and evolving disease course to achieve sustained improvements in patient outcomes. In this study, we modified a military-grade transport ventilator to deliver the airway pressure release ventilation (APRV) modality. We developed a computationally-directed (CD) method of adjusting the expiratory duration (T<sub>Low</sub>) during APRV using physiologic feedback to reduce alveolar derecruitment and tested this modality in a porcine model of moderate-to-severe ARDS.</p>Methods<p>Female Yorkshire-cross pigs (n = 27) were ventilated using a ZOLL EMV+® 731 Series ventilator during general anesthesia and subjected to a heterogeneous Tween lung injury followed by injurious mechanical ventilation. Animals were subsequently ventilated for 6 hours under general anesthesia after randomization to one of three groups: V<sub>T</sub>6 (n = 9) with a tidal volume (V<sub>T</sub>) of 6 mL/kg and stepwise adjustments in PEEP and FiO<sub>2</sub>; V<sub>T</sub>10 (n = 9) with V<sub>T</sub> of 10 mL/kg and PEEP of 5 cmH<sub>2</sub>O; CD-APRV group (n = 9) with computationally-directed adjustments in T<sub>Low</sub> based on a nonlinear equation of motion to describe respiratory mechanics. Results are reported as median [interquartile range].</p>Results<p>All groups developed moderate-to-severe ARDS and had similar recovery in lung injury, with all demonstrating final PaO<sub>2</sub>:FiO<sub>2</sub> > 300 mmHg (V<sub>T</sub>6: 415.5 [383.0–443.4], V<sub>T</sub>10: 353.3 [297.3–397.7], CD-APRV: 316.6 [269.8–362.4]; p = 0.12). PaCO<sub>2</sub> was significantly higher in the V<sub>T</sub>6 group compared with the CD-APRV group (59.3 [52.3–60.1] mmHg vs. 38.5 [32.7–52.2] mmHg, p = 0.04) but not significantly different from the V<sub>T</sub>10 group (47.5 [45.3–54.4] mmHg; p = 0.32 vs. V<sub>T</sub>6) despite having a significantly higher respiratory rate (30.0 [30.0–32.0] breaths/min) compared with V<sub>T</sub>10 (12.0 [12.0–15.0] breaths/min, p = 0.001) and CD-APRV (14.0 [14.0–14.0] breaths/min, p < 0.001) groups at the study end.</p>Conclusion<p>We successfully implemented a computationally directed APRV modality on a transport ventilator, adjusting T<sub>Low</sub> based on respiratory mechanics. This study demonstrated that CD-APRV can be safely used, with the advantage of guiding expiratory duration adjustments based on physiologic feedback from the lungs.</p> |
|---|