Resource type
Thesis type
(Thesis) Ph.D.
Date created
2022-04-09
Authors/Contributors
Author: Rohrs, Elizabeth
Abstract
Mechanical ventilation (MV) is an essential tool in the management of critical illness, however MV also induces lung injury that contributes to morbidity and mortality. This thesis investigates whether a new technology that uses temporary transvenous diaphragm neurostimulation (TTDN) to contract the diaphragm in synchrony with MV, can mitigate the risks of ventilator-induced lung injury (VILI). This thesis uses porcine ventilation models in two conditions to study the impact of TTDN on risk factors for VILI. The first study investigates the impact of a lung-protective ventilation protocol on VILI in a healthy-lung porcine model, mechanically ventilated for 50 hours, compared to an injured-lung porcine model, mechanically ventilated for 12 hours post-injury. Risk factors for VILI develop at a rate of 3-5 times faster in the presence of lung injury despite the use of a lung-protective ventilation protocol. The second study investigated the impact of the use of TTDN, combined with lung protective ventilation on every breath, or every second breath, for 50 hours in a healthy-lung porcine model. The third study investigated the impact of the use of TTDN, combined with lung protective ventilation on every breath, or every second breath, for 12 hours post-injury in an injured-lung porcine model. The findings were similar in these two studies. TTDN on every breath significantly reduced alveolar collapse that leads to alveolar heterogeneity in both ventilation models. TTDN on every breath also reduced driving pressure and mechanical power in both the healthy-lung and injured-lung models. TTDN on every breath combined with lung protective MV, called negative pressure assisted ventilation, provides a promising new method of reducing the risk of VILI in critically ill patients.
Document
Extent
200 pages.
Identifier
etd21849
Copyright statement
Copyright is held by the author(s).
Supervisor or Senior Supervisor
Thesis advisor: Reynolds, Steven
Language
English
Member of collection
Download file | Size |
---|---|
etd21849.pdf | 10.2 MB |