ArticleRespiratory care2024
The Ability of Critical Care Physicians to Identify Patient-Ventilator Asynchrony Using Waveform Analysis: A National Survey.
Article in Respiratory care, 2024. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 3 papers.
What it found
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The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.
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Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.
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Who cites it
3 citing papers in PubMed, 6 citations in OpenAlex.
- Ability to identify patient-ventilator asynchronies in intensive care unit professionals: A multicenter cross-sectional analytical study.Journal of critical care medicine (Universitatea de Medicina si Farmacie din Targu-Mures) · 2025Article
- Evaluation of health care providers' ability to identify patient-ventilator triggering asynchrony in intensive care unit: a translational observational study in China.BMC medical education · 2025Observational
- Closing the Gap in Patient-Ventilator Discordance Recognition.Respiratory care · 2024Article
Corrections and comments
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Authors and funding
8 authors at 2 institutions in 1 country.
Funding
No grant is acknowledged in the PubMed record.
Abstract
backgroundImproved 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.
methodsWe 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.
resultsAmong 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%],
conclusionsThe 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.
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