Cargando…
Non-invasive assessment of respiratory muscle activity during pressure support ventilation: accuracy of end-inspiration occlusion and least square fitting methods
Pressure support ventilation (PSV) should be titrated considering the pressure developed by the respiratory muscles (P(musc)) to prevent under- and over-assistance. The esophageal pressure (P(es)) is the clinical gold standard for P(musc) assessment, but its use is limited by alleged invasiveness an...
Autores principales: | , , , , , , , , , , , |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Springer Netherlands
2020
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330529/ https://www.ncbi.nlm.nih.gov/pubmed/32617847 http://dx.doi.org/10.1007/s10877-020-00552-5 |
_version_ | 1783553133986709504 |
---|---|
author | Natalini, Giuseppe Buizza, Barbara Granato, Anna Aniballi, Eros Pisani, Luigi Ciabatti, Gianni Lippolis, Valeria Rosano, Antonio Latronico, Nicola Grasso, Salvatore Antonelli, Massimo Bernardini, Achille |
author_facet | Natalini, Giuseppe Buizza, Barbara Granato, Anna Aniballi, Eros Pisani, Luigi Ciabatti, Gianni Lippolis, Valeria Rosano, Antonio Latronico, Nicola Grasso, Salvatore Antonelli, Massimo Bernardini, Achille |
author_sort | Natalini, Giuseppe |
collection | PubMed |
description | Pressure support ventilation (PSV) should be titrated considering the pressure developed by the respiratory muscles (P(musc)) to prevent under- and over-assistance. The esophageal pressure (P(es)) is the clinical gold standard for P(musc) 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 P(musc) assessment. The aims of this study were: (1) to compare the accuracy of P(musc) estimation using the end-inspiration occlusion (P(musc,index)) and the least square fitting (P(musc,lsf)) against the reference method based on P(es); (2) to test the accuracy of P(musc,lsf) and of P(musc,index) to detect overassistance, defined as P(musc) ≤ 1 cmH(2)O. We studied 18 patients at three different PSV levels. At each PSV level, P(musc), P(musc,lsf), P(musc,index) were calculated on the same breaths. Differences among P(musc), P(musc,lsf), P(musc,index) were analyzed with linear mixed effects models. Bias and agreement were assessed by Bland–Altman analysis for repeated measures. The ability of P(musc,lsf) and P(musc,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, P(musc,lsf) was not different from P(musc) (p = 0.96), whereas P(musc,index) was significantly lower than P(musc). The bias between P(musc) and P(musc,lsf) was zero, whereas P(musc,index) systematically underestimated P(musc) of 6 cmH(2)O. The limits of agreement between P(musc) and P(musc,lsf) and between P(musc) and P(musc,index) were ± 12 cmH(2)O across bias. Both P(musc,lsf) ≤ 4 cmH(2)O and P(musc,index) ≤ 1 cmH(2)O 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. |
format | Online Article Text |
id | pubmed-7330529 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2020 |
publisher | Springer Netherlands |
record_format | MEDLINE/PubMed |
spelling | pubmed-73305292020-07-02 Non-invasive assessment of respiratory muscle activity during pressure support ventilation: accuracy of end-inspiration occlusion and least square fitting methods Natalini, Giuseppe Buizza, Barbara Granato, Anna Aniballi, Eros Pisani, Luigi Ciabatti, Gianni Lippolis, Valeria Rosano, Antonio Latronico, Nicola Grasso, Salvatore Antonelli, Massimo Bernardini, Achille J Clin Monit Comput Original Research Pressure support ventilation (PSV) should be titrated considering the pressure developed by the respiratory muscles (P(musc)) to prevent under- and over-assistance. The esophageal pressure (P(es)) is the clinical gold standard for P(musc) 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 P(musc) assessment. The aims of this study were: (1) to compare the accuracy of P(musc) estimation using the end-inspiration occlusion (P(musc,index)) and the least square fitting (P(musc,lsf)) against the reference method based on P(es); (2) to test the accuracy of P(musc,lsf) and of P(musc,index) to detect overassistance, defined as P(musc) ≤ 1 cmH(2)O. We studied 18 patients at three different PSV levels. At each PSV level, P(musc), P(musc,lsf), P(musc,index) were calculated on the same breaths. Differences among P(musc), P(musc,lsf), P(musc,index) were analyzed with linear mixed effects models. Bias and agreement were assessed by Bland–Altman analysis for repeated measures. The ability of P(musc,lsf) and P(musc,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, P(musc,lsf) was not different from P(musc) (p = 0.96), whereas P(musc,index) was significantly lower than P(musc). The bias between P(musc) and P(musc,lsf) was zero, whereas P(musc,index) systematically underestimated P(musc) of 6 cmH(2)O. The limits of agreement between P(musc) and P(musc,lsf) and between P(musc) and P(musc,index) were ± 12 cmH(2)O across bias. Both P(musc,lsf) ≤ 4 cmH(2)O and P(musc,index) ≤ 1 cmH(2)O 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. Springer Netherlands 2020-07-02 2021 /pmc/articles/PMC7330529/ /pubmed/32617847 http://dx.doi.org/10.1007/s10877-020-00552-5 Text en © Springer Nature B.V. 2020 This article is made available via the PMC Open Access Subset for unrestricted research re-use and secondary analysis in any form or by any means with acknowledgement of the original source. These permissions are granted for the duration of the World Health Organization (WHO) declaration of COVID-19 as a global pandemic. |
spellingShingle | Original Research Natalini, Giuseppe Buizza, Barbara Granato, Anna Aniballi, Eros Pisani, Luigi Ciabatti, Gianni Lippolis, Valeria Rosano, Antonio Latronico, Nicola Grasso, Salvatore Antonelli, Massimo Bernardini, Achille Non-invasive assessment of respiratory muscle activity during pressure support ventilation: accuracy of end-inspiration occlusion and least square fitting methods |
title | Non-invasive assessment of respiratory muscle activity during pressure support ventilation: accuracy of end-inspiration occlusion and least square fitting methods |
title_full | Non-invasive assessment of respiratory muscle activity during pressure support ventilation: accuracy of end-inspiration occlusion and least square fitting methods |
title_fullStr | Non-invasive assessment of respiratory muscle activity during pressure support ventilation: accuracy of end-inspiration occlusion and least square fitting methods |
title_full_unstemmed | Non-invasive assessment of respiratory muscle activity during pressure support ventilation: accuracy of end-inspiration occlusion and least square fitting methods |
title_short | Non-invasive assessment of respiratory muscle activity during pressure support ventilation: accuracy of end-inspiration occlusion and least square fitting methods |
title_sort | non-invasive assessment of respiratory muscle activity during pressure support ventilation: accuracy of end-inspiration occlusion and least square fitting methods |
topic | Original Research |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC7330529/ https://www.ncbi.nlm.nih.gov/pubmed/32617847 http://dx.doi.org/10.1007/s10877-020-00552-5 |
work_keys_str_mv | AT natalinigiuseppe noninvasiveassessmentofrespiratorymuscleactivityduringpressuresupportventilationaccuracyofendinspirationocclusionandleastsquarefittingmethods AT buizzabarbara noninvasiveassessmentofrespiratorymuscleactivityduringpressuresupportventilationaccuracyofendinspirationocclusionandleastsquarefittingmethods AT granatoanna noninvasiveassessmentofrespiratorymuscleactivityduringpressuresupportventilationaccuracyofendinspirationocclusionandleastsquarefittingmethods AT aniballieros noninvasiveassessmentofrespiratorymuscleactivityduringpressuresupportventilationaccuracyofendinspirationocclusionandleastsquarefittingmethods AT pisaniluigi noninvasiveassessmentofrespiratorymuscleactivityduringpressuresupportventilationaccuracyofendinspirationocclusionandleastsquarefittingmethods AT ciabattigianni noninvasiveassessmentofrespiratorymuscleactivityduringpressuresupportventilationaccuracyofendinspirationocclusionandleastsquarefittingmethods AT lippolisvaleria noninvasiveassessmentofrespiratorymuscleactivityduringpressuresupportventilationaccuracyofendinspirationocclusionandleastsquarefittingmethods AT rosanoantonio noninvasiveassessmentofrespiratorymuscleactivityduringpressuresupportventilationaccuracyofendinspirationocclusionandleastsquarefittingmethods AT latroniconicola noninvasiveassessmentofrespiratorymuscleactivityduringpressuresupportventilationaccuracyofendinspirationocclusionandleastsquarefittingmethods AT grassosalvatore noninvasiveassessmentofrespiratorymuscleactivityduringpressuresupportventilationaccuracyofendinspirationocclusionandleastsquarefittingmethods AT antonellimassimo noninvasiveassessmentofrespiratorymuscleactivityduringpressuresupportventilationaccuracyofendinspirationocclusionandleastsquarefittingmethods AT bernardiniachille noninvasiveassessmentofrespiratorymuscleactivityduringpressuresupportventilationaccuracyofendinspirationocclusionandleastsquarefittingmethods |