Mechanical Power Density Predicts Prolonged Ventilation Following Double Lung Transplantation
Prolonged mechanical ventilation (PMV) after lung transplantation poses several risks, including higher tracheostomy rates and increased in-hospital mortality. Mechanical power (MP) of artificial ventilation unifies the ventilatory variables that determine gas exchange and may be related to allograf...
Autores principales: | , , , , , , , |
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Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Frontiers Media S.A.
2023
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Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10548550/ https://www.ncbi.nlm.nih.gov/pubmed/37799668 http://dx.doi.org/10.3389/ti.2023.11506 |
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author | Ghiani, Alessandro Kneidinger, Nikolaus Neurohr, Claus Frank, Sandra Hinske, Ludwig Christian Schneider, Christian Michel, Sebastian Irlbeck, Michael |
author_facet | Ghiani, Alessandro Kneidinger, Nikolaus Neurohr, Claus Frank, Sandra Hinske, Ludwig Christian Schneider, Christian Michel, Sebastian Irlbeck, Michael |
author_sort | Ghiani, Alessandro |
collection | PubMed |
description | Prolonged mechanical ventilation (PMV) after lung transplantation poses several risks, including higher tracheostomy rates and increased in-hospital mortality. Mechanical power (MP) of artificial ventilation unifies the ventilatory variables that determine gas exchange and may be related to allograft function following transplant, affecting ventilator weaning. We retrospectively analyzed consecutive double lung transplant recipients at a national transplant center, ventilated through endotracheal tubes upon ICU admission, excluding those receiving extracorporeal support. MP and derived indexes assessed up to 36 h after transplant were correlated with invasive ventilation duration using Spearman’s coefficient, and we conducted receiver operating characteristic (ROC) curve analysis to evaluate the accuracy in predicting PMV (>72 h), expressed as area under the ROC curve (AUROC). PMV occurred in 82 (35%) out of 237 cases. MP was significantly correlated with invasive ventilation duration (Spearman’s ρ = 0.252 [95% CI 0.129–0.369], p < 0.01), with power density (MP normalized to lung-thorax compliance) demonstrating the strongest correlation (ρ = 0.452 [0.345–0.548], p < 0.01) and enhancing PMV prediction (AUROC 0.78 [95% CI 0.72–0.83], p < 0.01) compared to MP (AUROC 0.66 [0.60–0.72], p < 0.01). Mechanical power density may help identify patients at risk for PMV after double lung transplantation. |
format | Online Article Text |
id | pubmed-10548550 |
institution | National Center for Biotechnology Information |
language | English |
publishDate | 2023 |
publisher | Frontiers Media S.A. |
record_format | MEDLINE/PubMed |
spelling | pubmed-105485502023-10-05 Mechanical Power Density Predicts Prolonged Ventilation Following Double Lung Transplantation Ghiani, Alessandro Kneidinger, Nikolaus Neurohr, Claus Frank, Sandra Hinske, Ludwig Christian Schneider, Christian Michel, Sebastian Irlbeck, Michael Transpl Int Health Archive Prolonged mechanical ventilation (PMV) after lung transplantation poses several risks, including higher tracheostomy rates and increased in-hospital mortality. Mechanical power (MP) of artificial ventilation unifies the ventilatory variables that determine gas exchange and may be related to allograft function following transplant, affecting ventilator weaning. We retrospectively analyzed consecutive double lung transplant recipients at a national transplant center, ventilated through endotracheal tubes upon ICU admission, excluding those receiving extracorporeal support. MP and derived indexes assessed up to 36 h after transplant were correlated with invasive ventilation duration using Spearman’s coefficient, and we conducted receiver operating characteristic (ROC) curve analysis to evaluate the accuracy in predicting PMV (>72 h), expressed as area under the ROC curve (AUROC). PMV occurred in 82 (35%) out of 237 cases. MP was significantly correlated with invasive ventilation duration (Spearman’s ρ = 0.252 [95% CI 0.129–0.369], p < 0.01), with power density (MP normalized to lung-thorax compliance) demonstrating the strongest correlation (ρ = 0.452 [0.345–0.548], p < 0.01) and enhancing PMV prediction (AUROC 0.78 [95% CI 0.72–0.83], p < 0.01) compared to MP (AUROC 0.66 [0.60–0.72], p < 0.01). Mechanical power density may help identify patients at risk for PMV after double lung transplantation. Frontiers Media S.A. 2023-09-20 /pmc/articles/PMC10548550/ /pubmed/37799668 http://dx.doi.org/10.3389/ti.2023.11506 Text en Copyright © 2023 Ghiani, Kneidinger, Neurohr, Frank, Hinske, Schneider, Michel and Irlbeck. https://creativecommons.org/licenses/by/4.0/This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) and the copyright owner(s) are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms. |
spellingShingle | Health Archive Ghiani, Alessandro Kneidinger, Nikolaus Neurohr, Claus Frank, Sandra Hinske, Ludwig Christian Schneider, Christian Michel, Sebastian Irlbeck, Michael Mechanical Power Density Predicts Prolonged Ventilation Following Double Lung Transplantation |
title | Mechanical Power Density Predicts Prolonged Ventilation Following Double Lung Transplantation |
title_full | Mechanical Power Density Predicts Prolonged Ventilation Following Double Lung Transplantation |
title_fullStr | Mechanical Power Density Predicts Prolonged Ventilation Following Double Lung Transplantation |
title_full_unstemmed | Mechanical Power Density Predicts Prolonged Ventilation Following Double Lung Transplantation |
title_short | Mechanical Power Density Predicts Prolonged Ventilation Following Double Lung Transplantation |
title_sort | mechanical power density predicts prolonged ventilation following double lung transplantation |
topic | Health Archive |
url | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10548550/ https://www.ncbi.nlm.nih.gov/pubmed/37799668 http://dx.doi.org/10.3389/ti.2023.11506 |
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