Transitions in intensive care: Investigating critical slowing down post extubation.
Complex biological systems undergo sudden transitions in their state, which are often preceded by a critical slowing down of dynamics. This results in longer recovery times as systems approach transitions, quantified as an increase in measures such as the autocorrelation and variance. In this study,...
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| Format: | Article |
| Language: | English |
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Public Library of Science (PLoS)
2025-01-01
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| Series: | PLoS ONE |
| Online Access: | https://doi.org/10.1371/journal.pone.0317211 |
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| author | Lucinda Khalil Sandip V George Katherine L Brown Samiran Ray Simon Arridge |
| author_facet | Lucinda Khalil Sandip V George Katherine L Brown Samiran Ray Simon Arridge |
| author_sort | Lucinda Khalil |
| collection | DOAJ |
| description | Complex biological systems undergo sudden transitions in their state, which are often preceded by a critical slowing down of dynamics. This results in longer recovery times as systems approach transitions, quantified as an increase in measures such as the autocorrelation and variance. In this study, we analysed paediatric patients in intensive care for whom mechanical ventilation was discontinued through removal of the endotracheal tube (extubation). Some patients failed extubation, and required a re-intubation within 48 hours. We investigated whether critical slowing down could be observed post failed extubations, prior to re-intubation. We tested for significant increases (p <.05) between extubation and re-intubation, in the variance and autocorrelation, over the time series data of heart rate, respiratory rate and mean blood pressure. The autocorrelation of the heart rate showed a significantly higher proportion of increases in the group that failed extubation, compared who those who did not. It also showed a significantly higher magnitude of increase for the failed extubation group in a t-test. Moreover, incorporating these magnitudes significantly improved the fit of a logistic regression model when compared to a model that solely used the mean and standard deviation of the vital signs. While immediate clinical utility is limited, the work marks an important first step towards using dynamical systems theory to understand the dynamics of signals measured at the bedside during intensive care. |
| format | Article |
| id | doaj-art-6d3f7c7d2dd649758580b956f5d489fa |
| institution | Kabale University |
| issn | 1932-6203 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | Public Library of Science (PLoS) |
| record_format | Article |
| series | PLoS ONE |
| spelling | doaj-art-6d3f7c7d2dd649758580b956f5d489fa2025-02-05T05:32:15ZengPublic Library of Science (PLoS)PLoS ONE1932-62032025-01-01201e031721110.1371/journal.pone.0317211Transitions in intensive care: Investigating critical slowing down post extubation.Lucinda KhalilSandip V GeorgeKatherine L BrownSamiran RaySimon ArridgeComplex biological systems undergo sudden transitions in their state, which are often preceded by a critical slowing down of dynamics. This results in longer recovery times as systems approach transitions, quantified as an increase in measures such as the autocorrelation and variance. In this study, we analysed paediatric patients in intensive care for whom mechanical ventilation was discontinued through removal of the endotracheal tube (extubation). Some patients failed extubation, and required a re-intubation within 48 hours. We investigated whether critical slowing down could be observed post failed extubations, prior to re-intubation. We tested for significant increases (p <.05) between extubation and re-intubation, in the variance and autocorrelation, over the time series data of heart rate, respiratory rate and mean blood pressure. The autocorrelation of the heart rate showed a significantly higher proportion of increases in the group that failed extubation, compared who those who did not. It also showed a significantly higher magnitude of increase for the failed extubation group in a t-test. Moreover, incorporating these magnitudes significantly improved the fit of a logistic regression model when compared to a model that solely used the mean and standard deviation of the vital signs. While immediate clinical utility is limited, the work marks an important first step towards using dynamical systems theory to understand the dynamics of signals measured at the bedside during intensive care.https://doi.org/10.1371/journal.pone.0317211 |
| spellingShingle | Lucinda Khalil Sandip V George Katherine L Brown Samiran Ray Simon Arridge Transitions in intensive care: Investigating critical slowing down post extubation. PLoS ONE |
| title | Transitions in intensive care: Investigating critical slowing down post extubation. |
| title_full | Transitions in intensive care: Investigating critical slowing down post extubation. |
| title_fullStr | Transitions in intensive care: Investigating critical slowing down post extubation. |
| title_full_unstemmed | Transitions in intensive care: Investigating critical slowing down post extubation. |
| title_short | Transitions in intensive care: Investigating critical slowing down post extubation. |
| title_sort | transitions in intensive care investigating critical slowing down post extubation |
| url | https://doi.org/10.1371/journal.pone.0317211 |
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