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Factors associated with intensive care professionals' ability to identify patient-ventilator asynchronies: A
Andrés Mauricio Enriquez-Popayan1, Henry Mauricio Parada-Gereda2, José Julian Bernal-Sanchez3
1Departamento de Fisioterapia en Cuidados Intensivos, SES Hospital Universitario de Caldas, Manizales, Colombia; Grupo de Investigación GIHORO, Hospital Regional de la Orinoquia, Yopal, Colombia.
Background:
Patient-ventilator asynchrony is common in critically ill patients receiving mechanical ventilation, and timely recognition is essential for safe ventilatory management. However, factors associated with intensive care professionals' ability to identify these events have not been systematically synthesized.
Objective:
To identify and synthesize factors associated with intensive care professionals' ability to identify patient-ventilator asynchronies through a systematic review and meta-analysis.
Methods:
Two reviewers independently conducted systematic literature searches in PubMed, LILACS, Cochrane Library, ScienceDirect, and EMBASE from database inception to January 2026. Study selection, data extraction, and methodological appraisal were performed independently. Risk of bias was assessed using the Joanna Briggs Institute Critical Appraisal Checklist for Analytical Cross-Sectional Studies. Pooled odds ratios (ORs) with 95% confidence intervals (95% CI) were calculated using random-effects models. Statistical heterogeneity was assessed using the I2 statistic, and leave-one-out sensitivity analyses were performed to evaluate the influence of individual studies. Publication bias was explored using funnel plots. Statistical significance was set at p < 0.05. Certainty of evidence was assessed using the GRADE approach.
Results:
Twelve studies including 4823 healthcare professionals were included, of which seven contributed data to the meta-analysis. Previous training in mechanical ventilation was significantly associated with a higher likelihood of correctly identifying patient-ventilator asynchronies (OR = 3.49; 95% CI: 1.95-6.25; I2 = 83%). Similarly, advanced academic training was also significantly associated with correct identification (OR = 1.83; 95% CI: 1.07-3.16; I2 = 28%). In contrast, specific training in asynchronies or waveform interpretation was not significantly associated (OR = 1.75; 95% CI: 0.67-4.56; I2 = 68%). No significant association was observed according to profession. Overall, most studies were at low risk of bias, although some methodological limitations were identified, and the certainty of the evidence was low.
Conclusion:
Previous training in mechanical ventilation and advanced academic training were associated with improved identification of patient-ventilator asynchronies among intensive care professionals. However, the available evidence remains limited and heterogeneous.
Implications For Clinical Practice:
General training in mechanical ventilation is associated with improved recognition of patient-ventilator asynchrony in clinical practice. Specific training in waveform interpretation alone may be insufficient. Standardized and clinically integrated training approaches may support improved detection of asynchrony in intensive care settings.
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