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Erschienen in: Journal of Clinical Monitoring and Computing 4/2021

02.07.2020 | Original Research

Non-invasive assessment of respiratory muscle activity during pressure support ventilation: accuracy of end-inspiration occlusion and least square fitting methods

verfasst von: Giuseppe Natalini, Barbara Buizza, Anna Granato, Eros Aniballi, Luigi Pisani, Gianni Ciabatti, Valeria Lippolis, Antonio Rosano, Nicola Latronico, Salvatore Grasso, Massimo Antonelli, Achille Bernardini

Erschienen in: Journal of Clinical Monitoring and Computing | Ausgabe 4/2021

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Abstract

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.
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Metadaten
Titel
Non-invasive assessment of respiratory muscle activity during pressure support ventilation: accuracy of end-inspiration occlusion and least square fitting methods
verfasst von
Giuseppe Natalini
Barbara Buizza
Anna Granato
Eros Aniballi
Luigi Pisani
Gianni Ciabatti
Valeria Lippolis
Antonio Rosano
Nicola Latronico
Salvatore Grasso
Massimo Antonelli
Achille Bernardini
Publikationsdatum
02.07.2020
Verlag
Springer Netherlands
Erschienen in
Journal of Clinical Monitoring and Computing / Ausgabe 4/2021
Print ISSN: 1387-1307
Elektronische ISSN: 1573-2614
DOI
https://doi.org/10.1007/s10877-020-00552-5

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