Patient-ventilator asynchrony

The Effect of Switching from Volume-Controlled to Pressure-Controlled Ventilation on Respiratory Distress and Asynchrony Index Improvement among Mechanically Ventilated Adults

Background

It is important to synchrony the time, intensity, and respiratory signal of the phrenic nerve between the patient and the ventilator. This study aimed to evaluate the effect of switching from volume-controlled to pressure-controlled ventilation on respiratory distress and asynchrony index improvement.

Materials and Methods

In this randomized controlled clinical trial, 70 patients admitted to the intensive care unit under mechanical ventilation were included. Asynchronous evaluation was performed by examining the patient and evaluating and analyzing the graphic flow curve and ventilator pressure, which included trigger and flow asynchronous and asynchronous cycling. In the intervention group, the mode of ventilation was switched to PSIMV such that peak inspiratory pressures would be equivalent to positive end-expiratory pressure (PEEP) in the volume-controlled mode. Finally, again at 60, 75, and 90 min, information about the ventilator and the patient's symptoms, and arterial carbon dioxide levels were sent by arterial gas sample. The asynchronous index was also recorded in both groups.

Results

This study showed that the mean of variables such as height, ideal body weight, tidal volume, set rate; Sense, FiO₂, PEEP did not differ significantly between the two groups. The mean of asynchrony was significantly reduced in both control group (16.51 ± 3.35-14.51 ± 2.90; P < 0.001) and intervention group (18.26 ± 6.13-13.32 ± 5.53; P < 0.001).

Conclusion

Regardless of the type and severity of the disease, switching the ventilation mode from volume-controlled to pressure-controlled can improve patient adaptation to the ventilator, especially in cases with frequent asynchrony.

The Impact of a Training Intervention on Detection of Patient-Ventilator Asynchronies in Nursing Students

BACKGROUND AND AIM

Patient-ventilator asynchronies (PVA) are associated to negative outcomes for patients: increased respiratory work, mechanical ventilation time and ICU length of stay, and mortality. Some studies described the positive impact of a training intervention on the knowledge and attitudes of nurses in detecting PVA. The aim of this study was to evaluate the efficacy of a training intervention focused on detection of PVA.

METHODS

A before-after design on a single group of nursing students was used. The training intervention about detection of the correct respiratory waveform through graphic monitoring was conducted in a single edition course of 2 hours, for 25 participants. Measurements of correct detection of PVA through specific competency assessment tool were performed before (T0), immediately after (T1) and at 1 month (T2) from the training intervention between January and February 2020.

RESULTS

19 Nurse students completed the training. A total of 50 questionnaires were distributed (T0; n=19; T1; n=19; T2; n=12). PVA were correctly detected in 67.5% (77) of cases. Statistically significant difference There were differences in trainees performance between T0 and T1 [77,2% (CI95%: 68,7% - 85,8%; p=0.001)] and between T0 and T2 [75% (CI95%: 65,3% - 84,7%; p=0.001]. No significant difference was recorded between T1 and T2 (p=0.83) Conclusions: Nursing students increased their performance on analysis of the graphic monitoring of the respiratory waveforms and detection of asynchronies after a basic training intervention. These skills were retained after 1 month. Nurse student trained about PVA increased their competence potentially employed in critical care settings.

A Taxonomy for Patient-Ventilator Interactions and a Method to Read Ventilator Waveforms

Mechanical ventilators display detailed waveforms which contain a wealth of clinically relevant information. Although much has been written about interpretation of waveforms and patient-ventilator interactions, variability remains on the nomenclature (multiple and ambiguous terms) and waveform interpretation. There are multiple reasons for this variability (legacy terms, language, multiple definitions). In addition, there is no widely accepted systematic method to read ventilator waveforms. We propose a standardized nomenclature and taxonomy along with a method to interpret mechanical ventilator displayed waveforms.