The Ability of Critical Care Physicians to Identify Patient-Ventilator Asynchrony Using Waveform Analysis: A National Survey

Rym Chelbi; Farah Thabet; Emna Ennouri; Khaoula Meddeb; Radhouane Toumi; Marwa Zghidi; Imen Ben Saida; Mohamed Boussarsar

doi:10.4187/respcare.11360

The Ability of Critical Care Physicians to Identify Patient-Ventilator Asynchrony Using Waveform Analysis: A National Survey

Respir Care. 2024 Jan 24;69(2):176-183. doi: 10.4187/respcare.11360.

Authors

Rym Chelbi¹, Farah Thabet², Emna Ennouri¹, Khaoula Meddeb¹, Radhouane Toumi¹, Marwa Zghidi¹, Imen Ben Saida¹, Mohamed Boussarsar³

Affiliations

¹ University of Sousse, Faculty of Medicine of Sousse, 4002, Sousse, Tunisia; and Farhat Hached University Hospital, Medical Intensive Care Unit, Research Laboratory "Heart Failure," LR12SP09, 4000, Sousse, Tunisia.
² University of Monastir, Faculty of Medicine of Monastir, Monastir, Tunisia; and Pediatric Department, Fattouma Bourguiba University Hospital, Monastir, Tunisia; University of Medicine of Monastir, Monastir, Tunisia.
³ University of Sousse, Faculty of Medicine of Sousse, 4002, Sousse, Tunisia; and Farhat Hached University Hospital, Medical Intensive Care Unit, Research Laboratory "Heart Failure," LR12SP09, 4000, Sousse, Tunisia. hamadi.boussarsar@gmail.com.

PMID: 38267232
PMCID: PMC10898468 (available on 2025-02-01)
DOI: 10.4187/respcare.11360

Abstract

Background: Improved patient-ventilator asynchrony (PVA) identification using waveform analysis by critical care physicians (CCPs) may improve patient outcomes. This study aimed to assess the ability of CCPs to identify different types of PVAs using waveform analysis as well as factors related to this ability.

Methods: We surveyed 12 university-affiliated medical ICUs (MICUs) in Tunisia. CCPs practicing in these MICUs were asked to visually identify 4 clinical cases, each corresponding to a different PVA. We collected the following characteristics regarding CCPs: scientific grade, years of experience, prior training in mechanical ventilation, prior exposure to waveform analysis, and the characteristics of the MICUs in which they practice. Respondents were categorized into 2 groups based on their ability to correctly identify PVAs (defined as the correct identification of at least 3 of the 4 PVA cases). Univariate analysis was performed to identify factors related to the correct identification of PVA.

Results: Among 136 included CCPs, 72 (52.9%) responded to the present survey. The respondents comprised 59 (81.9%) residents, and 13 (18.1%) senior physicians. Further, 50 (69.4%) respondents had attended prior training in mechanical ventilation. Moreover, 21 (29.2%) of the respondents could correctly identify PVAs. Double-triggering was the most frequently identified PVA type, 43 (59.7%), followed by auto-triggering, 36 (50%); premature cycling, 28 (38.9%); and ineffective efforts, 25 (34.7%). Univariate analysis indicated that senior physicians had a better ability to correctly identify PVAs than residents (7 [53.8%] vs 14 [23.7%], P = .044).

Conclusions: The present study revealed a significant deficiency in the accurate visual identification of PVAs among CCPs in the MICUs. When compared to residents, senior physicians exhibited a notably superior aptitude for correctly recognizing PVAs.

Keywords: critical care physicians; education and training; identification accuracy; mechanical ventilation; patient-ventilator asynchrony; respiratory support; waveform analysis.

MeSH terms

Critical Care
Female
Humans
Intensive Care Units
Patient-Ventilator Asynchrony
Physicians*
Premature Birth*