Ability of ICU health-care professionals to identify patient-ventilator asynchrony using waveform analysis

Ivan I. Ramirez, Daniel H. Arellano, Rodrigo S. Adasme, Jose M. Landeros, Francisco A. Salinas, Alvaro G. Vargas, Francisco J. Vasquez, Ignacio A. Lobos, Magdalena L. Oyarzun, Ruben D. Restrepo

Research output: Contribution to journalArticlepeer-review

28 Scopus citations


BACKGROUND: Waveform analysis by visual inspection can be a reliable, noninvasive, and useful tool for detecting patient-ventilator asynchrony. However, it is a skill that requires a properly trained professional. METHODS: This observational study was conducted in 17 urban ICUs. Health-care professionals (HCPs) working in these ICUs were asked to recognize different types of asynchrony shown in 3 evaluation videos. The health-care professionals were categorized according to years of experience, prior training in mechanical ventilation, profession, and number of asynchronies identified correctly. RESULTS: A total of 366 HCPs were evaluated. Statistically significant differences were found when HCPs with and without prior training in mechanical ventilation (trained vs non-trained HCPs) were compared according to the number of asynchronies detected correctly (of the HCPs who identified 3 asynchronies, 63 [81%] trained vs 15 [19%] non-trained, P <.001; 2 asynchronies, 72 [65%] trained vs 39 [35%] non-trained, P =.034; 1 asynchrony, 55 [47%] trained vs 61 [53%] non-trained, P =.02; 0 asynchronies, 17 [28%] trained vs 44 [72%] non-trained, P <.001). HCPs who had prior training in mechanical ventilation also increased, nearly 4-fold, their odds of identifying ≥2 asynchronies correctly (odds ratio 3.67, 95% CI 1.93–6.96, P <.001). However, neither years of experience nor profession were associated with the ability of HCPs to identify asynchrony. CONCLUSIONS: HCPs who have specific training in mechanical ventilation increase their ability to identify asynchrony using waveform analysis. Neither experience nor profession proved to be a relevant factor to identify asynchrony correctly using waveform analysis.

Original languageEnglish (US)
Pages (from-to)144-149
Number of pages6
JournalRespiratory care
Issue number2
StatePublished - Feb 1 2017


  • Critical care
  • Intensive care unit
  • Mechanical ventilation
  • Patient-ventilator asynchrony
  • Ventilator graphics
  • Waveforms

ASJC Scopus subject areas

  • Pulmonary and Respiratory Medicine
  • Critical Care and Intensive Care Medicine


Dive into the research topics of 'Ability of ICU health-care professionals to identify patient-ventilator asynchrony using waveform analysis'. Together they form a unique fingerprint.

Cite this