Why the study?
Does flow and airway pressure analysis accurately detect ineffective efforts during mechanical ventilation compared to esophageal pressure measurement in patients with neuromuscular diseases?
Does flow and airway pressure analysis accurately detect ineffective efforts during mechanical ventilation compared to esophageal pressure measurement in patients with neuromuscular diseases?
Using flow and pressure signals is a simple, rapid, and highly sensitive method for detecting ineffective efforts during mechanical ventilation in neuromuscular patients.
May aid bedside IE detection in NMD ventilation; leaves open need for prospective validation before clinical use.
Ineffective efforts (IEs) are among the most common types of patient-ventilator asynchrony. The objective of this study is to validate IE detection during expiration using pressure and flow signals, with respiratory effort detection by esophageal pressure (Pes) measurement as the reference, in patients with neuromuscular diseases (NMDs). We included 10 patients diagnosed with chronic respiratory failure related to NMD. Twenty-eight 5-minute recordings of daytime ventilation were studied for IE detection. Standard formulas were used to calculate sensitivity, specificity, positive predictive value (PPV), and negative predictive value (NPV) of IE detection using pressure and flow signals compared to Pes measurement. Mean sensitivity and specificity of flow and pressure signal-based IE detection versus Pes measurement were 97.5% ± 5.3% and 91.4% ± 13.7%, respectively. NPV was 98.1% ± 8.2% and PPV was 67.6% ± 33.8%. Spearman's rank correlation coefficient indicated a moderately significant correlation between frequencies of IEs and controlled cycles ( ρ = 0.50 and p = 0.01). Among respiratory cycles, 311 (11.2%) were false-positive IEs overall. Separating false-positive IEs according to their mechanisms, we observed premature cycling in 1.2% of cycles, delayed ventilator triggering in 0.1%, cardiac contraction in 9.2%, and upper airway instability during expiration in 0.3%. Using flow and pressure signals to detect IEs is a simple and rapid method that produces adequate data to support clinical decisions.
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Ciorba et al. (2018) studied this question.
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