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Pressure support ventilation (PSV) is an assisted mechanical ventilation mode that provides synchronous inspiratory support for patients with spontaneous breathing. PSV divides the work involved in producing ventilation between the ventilator and the patients. The patient inspiratory effort needs close monitoring to avoid inappropriate assistance and maintain favorable patient-ventilator interaction during PSV. Esophageal pressure (Pes)-derived parameters are regarded as golden indicators of inspiratory effort. Based on this precondition, the fraction of PTP generated by the patient during PSV (PTP ratio) can evaluate the inspiratory contribution proportion of ventilated patients with spontaneous breathing. Inspiratory muscle pressure index (PMI) was confirmed to be associated with inspiratory effort and can effectively predict low/high effort. The study tries to explore the relationship between PMI and PTP ratio and find the optimal cut-off value of PMI to predict different PTP ratios. Second, investigators want to verify the safety and validity of PMI-guided PS settings for pressure-support ventilated patients.
Full description
Pressure support ventilation (PSV) is an assisted mechanical ventilation mode that provides synchronous inspiratory support for patients with spontaneous breathing. PSV divides the work involved in producing ventilation between the ventilator and the patients. The level of support should be adjusted to the patient's inspiratory effort for assisted ventilation to be successful. Despite PSV being commonly used in mechanical ventilation therapy, the PS setting is not precisely regulated. Clinicians and respiratory therapists typically use tidal volume/predicted body weight (VT/PBW, 6-8 ml/Kg) and respiratory rate (RR, 20-30 breaths/min) to modify ventilator settings. Because pressure support level is not dynamically modulated based on the inspiratory effort of ventilated patients in time, there is always the risk of excessive or insufficient assistance. Excessive assistance and low inspiratory effort may result in diaphragm disuse atrophy and ventilator-induced lung injury (VILI). Inadequate assistance and high inspiratory effort may result in diagram stretched injury and patient-inflicted lung injury (PSILI). Both situations cause strain and stress on the lung and diaphragm, which may influence the ICU clinical outcomes.
The patient inspiratory effort needs close monitoring to avoid inappropriate assistance and maintain favorable patient-ventilator interaction during PSV. Esophageal pressure (Pes)-derived parameters are regarded as golden indicators of inspiratory effort, including respiratory muscle pressure (Pmus), esophageal pressure-time product (PTPes), etc. Based on this precondition, the fraction of PTP generated by the patient during PSV (PTP ratio) can evaluate the inspiratory contribution proportion of ventilated patients with spontaneous breathing. Pmus index (PMI) is defined as the change in airway pressure (Paw) during the end-inspiratory occlusion and represents the patient's current elastic workload. This variable was confirmed to be associated with inspiratory effort and can effectively predict low/high effort. More importantly, it is non-invasive and available at the bedside because respiratory hold operations are integrated into most ventilators. However, the relationship between PMI and the inspiratory contribution proportion of ventilated patients is not clear, and how to guide PS settings through PMI needs more research.
Our study aims to explore the inspiratory contribution of pressure-support ventilated patients in different PMI conditions. In other words, investigators try to explore the relationship between PMI and PTP ratio and find the optimal cut-off value of PMI to predict different PTP ratios. Second, investigators want to verify the safety and validity of PMI-guided PS settings for pressure-support ventilated patients.
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Adult acute respiratory failure patients undergoing mechanical ventilation were screened daily and enrolled 24 hours after switching to PSV mode.
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22 participants in 1 patient group
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Jian-Xin Zhou, MD; Ran Gao, MD
Data sourced from clinicaltrials.gov
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