Abstract
Background:
Patient-ventilator asynchrony (PVA) has detrimental effects that include increased WOB, patient discomfort, increased need for sedation, prolonged mechanical ventilation, and decreased survival. Ventilator waveforms could assist identifying and correcting PVA by matching ventilator parameters to patient respiratory needs. The goal of this study was to assess the ability of HCPs working in ICUs to interpret common types of PVA.
Methods:
Descriptive observational study at a 496-bed university-affiliated institution in San Antonio, TX. Study was approved by the IRB. Four waveforms showing examples of PVA (ineffective effort, flow asynchrony, double-triggering, and auto-triggering) were presented, one at a time, to each HCP in the same order and asked to select the best answer from a multiple-choice questionnaire. HCPs with previous training on waveforms were compared to non-trained.
Results:
A total of 47 HPCs, including 19 RRTs (40.4%), 2 CRTs (4.3%), 6 resident physicians (12.8%), 7 fellows, (14.9%), 1 attending physician (2.1%), 1 physician assistant (2.1%), and 11 RNs (23.4%), completed the evaluation. Only 9 (19.1%) HCPs recognized the 4 types of asynchrony correctly, whereas 9 (19.1%) detected 2 types correctly, and 16 (34.0%) detected 1 type correctly. Thirteen participants (27.7%) did not identify any asynchrony correctly. Flow asynchrony was identified by 12 HCPs (25.5%), double-triggering by 18 (38.3%), while autotriggering and missed trigger was identified by the same number of HCPs, 20 (42.5%). There was not a significant difference between trained and non-trained HCPs who identified 4 asynchronies. Only 2 (10.5%) of the 19 RRTs identified all PVAs, while both CRTs (100%), one attending (100%), 2 CRTs (100%), 1 resident (16.7%), and 2 RNs (18.2%) identified all PVAs. The great majority of RRTs (57.9%) recognized only one type of PVA. The percentage of trained HCPs who identified 2 asynchronies (77.7%) was significantly higher than non-trained HCPs (22.2%; P = 0.023). Lack of recognition of any asynchrony was significantly higher in the non-trained group (76.9%) than in the trained group (23. 1%; P = 0.005).
Conclusions:
A small number of HCPs in the ICU are able to recognize common types of patient-ventilator asynchronies. Previous training on ventilator waveform analysis may significantly impact the ability of professionals to identify ventilator asynchrony.
Number of PVAs detected correctly
Trained
Non-trained
P
4
5
4
1.0
3
7
2
0.005
2
12
4
0.001
1
3
10
0.001
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