TY - JOUR
T1 - Non-invasive assessment of respiratory muscle activity during pressure support ventilation
T2 - accuracy of end-inspiration occlusion and least square fitting methods
AU - Natalini, Giuseppe
AU - Buizza, Barbara
AU - Granato, Anna
AU - Aniballi, Eros
AU - Pisani, Luigi
AU - Ciabatti, Gianni
AU - Lippolis, Valeria
AU - Rosano, Antonio
AU - Latronico, Nicola
AU - Grasso, Salvatore
AU - Antonelli, Massimo
AU - Bernardini, Achille
N1 - Publisher Copyright:
© 2020, Springer Nature B.V.
Copyright:
Copyright 2020 Elsevier B.V., All rights reserved.
PY - 2020
Y1 - 2020
N2 - Pressure support ventilation (PSV) should be titrated considering the pressure developed by the respiratory muscles (Pmusc) to prevent under- and over-assistance. The esophageal pressure (Pes) is the clinical gold standard for Pmusc assessment, but its use is limited by alleged invasiveness and complexity. The least square fitting method and the end-inspiratory occlusion method have been proposed as non-invasive alternatives for Pmusc assessment. The aims of this study were: (1) to compare the accuracy of Pmusc estimation using the end-inspiration occlusion (Pmusc,index) and the least square fitting (Pmusc,lsf) against the reference method based on Pes; (2) to test the accuracy of Pmusc,lsf and of Pmusc,index to detect overassistance, defined as Pmusc ≤ 1 cmH2O. We studied 18 patients at three different PSV levels. At each PSV level, Pmusc, Pmusc,lsf, Pmusc,index were calculated on the same breaths. Differences among Pmusc, Pmusc,lsf, Pmusc,index were analyzed with linear mixed effects models. Bias and agreement were assessed by Bland–Altman analysis for repeated measures. The ability of Pmusc,lsf and Pmusc,index to detect overassistance was assessed by the area under the receiver operating characteristics curve. Positive and negative predictive values were calculated using cutoff values that maximized the sum of sensitivity and specificity. At each PSV level, Pmusc,lsf was not different from Pmusc (p = 0.96), whereas Pmusc,index was significantly lower than Pmusc. The bias between Pmusc and Pmusc,lsf was zero, whereas Pmusc,index systematically underestimated Pmusc of 6 cmH2O. The limits of agreement between Pmusc and Pmusc,lsf and between Pmusc and Pmusc,index were ± 12 cmH2O across bias. Both Pmusc,lsf ≤ 4 cmH2O and Pmusc,index ≤ 1 cmH2O had excellent negative predictive value [0.98 (95% CI 0.94–1) and 0.96 (95% CI 0.91–0.99), respectively)] to identify over-assistance. The inspiratory effort during PSV could not be accurately estimated by the least square fitting or end-inspiratory occlusion method because the limits of agreement were far above the signal size. These non-invasive approaches, however, could be used to screen patients at risk for absent or minimal respiratory muscles activation to prevent the ventilator-induced diaphragmatic dysfunction.
AB - Pressure support ventilation (PSV) should be titrated considering the pressure developed by the respiratory muscles (Pmusc) to prevent under- and over-assistance. The esophageal pressure (Pes) is the clinical gold standard for Pmusc assessment, but its use is limited by alleged invasiveness and complexity. The least square fitting method and the end-inspiratory occlusion method have been proposed as non-invasive alternatives for Pmusc assessment. The aims of this study were: (1) to compare the accuracy of Pmusc estimation using the end-inspiration occlusion (Pmusc,index) and the least square fitting (Pmusc,lsf) against the reference method based on Pes; (2) to test the accuracy of Pmusc,lsf and of Pmusc,index to detect overassistance, defined as Pmusc ≤ 1 cmH2O. We studied 18 patients at three different PSV levels. At each PSV level, Pmusc, Pmusc,lsf, Pmusc,index were calculated on the same breaths. Differences among Pmusc, Pmusc,lsf, Pmusc,index were analyzed with linear mixed effects models. Bias and agreement were assessed by Bland–Altman analysis for repeated measures. The ability of Pmusc,lsf and Pmusc,index to detect overassistance was assessed by the area under the receiver operating characteristics curve. Positive and negative predictive values were calculated using cutoff values that maximized the sum of sensitivity and specificity. At each PSV level, Pmusc,lsf was not different from Pmusc (p = 0.96), whereas Pmusc,index was significantly lower than Pmusc. The bias between Pmusc and Pmusc,lsf was zero, whereas Pmusc,index systematically underestimated Pmusc of 6 cmH2O. The limits of agreement between Pmusc and Pmusc,lsf and between Pmusc and Pmusc,index were ± 12 cmH2O across bias. Both Pmusc,lsf ≤ 4 cmH2O and Pmusc,index ≤ 1 cmH2O had excellent negative predictive value [0.98 (95% CI 0.94–1) and 0.96 (95% CI 0.91–0.99), respectively)] to identify over-assistance. The inspiratory effort during PSV could not be accurately estimated by the least square fitting or end-inspiratory occlusion method because the limits of agreement were far above the signal size. These non-invasive approaches, however, could be used to screen patients at risk for absent or minimal respiratory muscles activation to prevent the ventilator-induced diaphragmatic dysfunction.
KW - End-inspiratory occlusion
KW - Esophageal pressure
KW - Inspiratory effort
KW - Least square fitting
KW - Mechanical ventilation
KW - Respiratory muscles
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U2 - 10.1007/s10877-020-00552-5
DO - 10.1007/s10877-020-00552-5
M3 - Article
AN - SCOPUS:85087421869
JO - Journal of Clinical Monitoring and Computing
JF - Journal of Clinical Monitoring and Computing
SN - 1387-1307
ER -