Identifying and managing patient–ventilator asynchrony: An international survey

Abstract

International study conducted in 20 countries through an online survey. Participants: Physicians, respiratory therapists, nurses and physiotherapists that are currently working at the Intensive Care Unit (ICU). Main variables of interest: Univariate and multivariate logistic regression models were used to establish associations between all variables (profession, training in mechanical ventilation, type of training program, years of experience and ICU characteristics) with the ability of HCPs to correctly identify and manage 6 PVA. Results: A total of 431 HCPs answered a validated survey. The main factors associated with the proper recognition of PVA were: specific training program in mechanicalventilation (MV) (OR 2.27; 95% CI 1.14-4.52; p = 0.019), courses with more than 100 hours completed (OR 2.28; 95% CI 1.29-4.03; p = 0.005) and the number of intensive care unit (ICU) beds (OR 1.037; 95% CI 1.01-1.06; p = 0.005). The main factor that influenced PVA management was recognizing 6 PVA correctly (OR 118.98;; p < 0.001). Conclusion:Identifying and managing PVA using ventilator waveform analysis is influenced by many factors including specific training programs in MV, number of ICU beds and the recognized number of PVA.

Critical care nurses' knowledge and attitudes toward using ventilator waveform monitoring to detect patient-ventilator asynchrony: A cross-sectional online survey

“…The current study's ndings agree with Smith et al (17) , who found that the knowledge level of either nurses or respiratory therapists was signi cantly affected by receiving education on the patient-ventilator synchrony and asynchrony. Recently, Ramírez et al (32) found that a speci c training program in mechanical ventilation was among the main factors associated with proper recognition of PVA.…”

“…Recently, a universal study was conducted by Ramirez et al (32) through an online survey to investigate the main factors associated with proper recognition and management of PVA. The results revealed that proper recognition and management of PVA were associated signi cantly with speci c training programs in MV, the number of ICU beds, and the number of recognized PVAs.…”

The authors respond

“…Different studies measuring the accuracy of waveforms to detect asynchrony have shown a wide range of results. 3,4 Colombo et al 5 reported low sensitivity and positive predictive value for detecting asynchrony with waveforms (22% and 32%, respectively), results that improved to some extent (55% and 44%, respectively) in cases in which asynchrony were frequent (asynchrony index > 10%). However, in the study cited by Drs Bonorino and Cani, Chaco ´n et al 6 reported that trained nurses could detect asynchrony based on waveforms with high accuracy (ie, 92.5% sensitivity and 95.4% positive predictive value, not 22% and 32%, respectively, as stated in the letter).…”