Automated evaluation of typical patient–ventilator asynchronies based on lung hysteretic responses
Abstract Background Patient–ventilator asynchrony is common during mechanical ventilation (MV) in intensive care unit (ICU), leading to worse MV care outcome. Identification of asynchrony is critical for optimizing MV settings to reduce or eliminate asynchrony, whilst current clinical visual inspect...
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| Format: | Article |
| Language: | English |
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BMC
2023-10-01
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| Series: | BioMedical Engineering OnLine |
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| Online Access: | https://doi.org/10.1186/s12938-023-01165-0 |
| _version_ | 1797557657648758784 |
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| author | Yuhong Chen Kun Zhang Cong Zhou J. Geoffrey Chase Zhenjie Hu |
| author_facet | Yuhong Chen Kun Zhang Cong Zhou J. Geoffrey Chase Zhenjie Hu |
| author_sort | Yuhong Chen |
| collection | DOAJ |
| description | Abstract Background Patient–ventilator asynchrony is common during mechanical ventilation (MV) in intensive care unit (ICU), leading to worse MV care outcome. Identification of asynchrony is critical for optimizing MV settings to reduce or eliminate asynchrony, whilst current clinical visual inspection of all typical types of asynchronous breaths is difficult and inefficient. Patient asynchronies create a unique pattern of distortions in hysteresis respiratory behaviours presented in pressure–volume (PV) loop. Methods Identification method based on hysteretic lung mechanics and hysteresis loop analysis is proposed to delineate the resulted changes of lung mechanics in PV loop during asynchronous breathing, offering detection of both its incidence and 7 major types. Performance is tested against clinical patient data with comparison to visual inspection conducted by clinical doctors. Results The identification sensitivity and specificity of 11 patients with 500 breaths for each patient are above 89.5% and 96.8% for all 7 types, respectively. The average sensitivity and specificity across all cases are 94.6% and 99.3%, indicating a very good accuracy. The comparison of statistical analysis between identification and human inspection yields the essential same clinical judgement on patient asynchrony status for each patient, potentially leading to the same clinical decision for setting adjustment. Conclusions The overall results validate the accuracy and robustness of the identification method for a bedside monitoring, as well as its ability to provide a quantified metric for clinical decision of ventilator setting. Hence, the method shows its potential to assist a more consistent and objective assessment of asynchrony without undermining the efficacy of the current clinical practice. |
| first_indexed | 2024-03-10T17:20:54Z |
| format | Article |
| id | doaj.art-e5421244b2ff4a48832bb3b4812cabb9 |
| institution | Directory Open Access Journal |
| issn | 1475-925X |
| language | English |
| last_indexed | 2024-03-10T17:20:54Z |
| publishDate | 2023-10-01 |
| publisher | BMC |
| record_format | Article |
| series | BioMedical Engineering OnLine |
| spelling | doaj.art-e5421244b2ff4a48832bb3b4812cabb92023-11-20T10:22:31ZengBMCBioMedical Engineering OnLine1475-925X2023-10-0122112110.1186/s12938-023-01165-0Automated evaluation of typical patient–ventilator asynchronies based on lung hysteretic responsesYuhong Chen0Kun Zhang1Cong Zhou2J. Geoffrey Chase3Zhenjie Hu4Intensive Care Unit, The Fourth Hospital of Hebei Medical UniversityIntensive Care Unit, The Fourth Hospital of Hebei Medical UniversityDepartment of Mechanical Engineering & Centre for Bio-Engineering, University of CanterburyDepartment of Mechanical Engineering & Centre for Bio-Engineering, University of CanterburyIntensive Care Unit, The Fourth Hospital of Hebei Medical UniversityAbstract Background Patient–ventilator asynchrony is common during mechanical ventilation (MV) in intensive care unit (ICU), leading to worse MV care outcome. Identification of asynchrony is critical for optimizing MV settings to reduce or eliminate asynchrony, whilst current clinical visual inspection of all typical types of asynchronous breaths is difficult and inefficient. Patient asynchronies create a unique pattern of distortions in hysteresis respiratory behaviours presented in pressure–volume (PV) loop. Methods Identification method based on hysteretic lung mechanics and hysteresis loop analysis is proposed to delineate the resulted changes of lung mechanics in PV loop during asynchronous breathing, offering detection of both its incidence and 7 major types. Performance is tested against clinical patient data with comparison to visual inspection conducted by clinical doctors. Results The identification sensitivity and specificity of 11 patients with 500 breaths for each patient are above 89.5% and 96.8% for all 7 types, respectively. The average sensitivity and specificity across all cases are 94.6% and 99.3%, indicating a very good accuracy. The comparison of statistical analysis between identification and human inspection yields the essential same clinical judgement on patient asynchrony status for each patient, potentially leading to the same clinical decision for setting adjustment. Conclusions The overall results validate the accuracy and robustness of the identification method for a bedside monitoring, as well as its ability to provide a quantified metric for clinical decision of ventilator setting. Hence, the method shows its potential to assist a more consistent and objective assessment of asynchrony without undermining the efficacy of the current clinical practice.https://doi.org/10.1186/s12938-023-01165-0Patient–ventilator asynchronyMechanical ventilationPV loopHysteretic lung mechanicsHysteresis loop analysisIntensive care unit |
| spellingShingle | Yuhong Chen Kun Zhang Cong Zhou J. Geoffrey Chase Zhenjie Hu Automated evaluation of typical patient–ventilator asynchronies based on lung hysteretic responses BioMedical Engineering OnLine Patient–ventilator asynchrony Mechanical ventilation PV loop Hysteretic lung mechanics Hysteresis loop analysis Intensive care unit |
| title | Automated evaluation of typical patient–ventilator asynchronies based on lung hysteretic responses |
| title_full | Automated evaluation of typical patient–ventilator asynchronies based on lung hysteretic responses |
| title_fullStr | Automated evaluation of typical patient–ventilator asynchronies based on lung hysteretic responses |
| title_full_unstemmed | Automated evaluation of typical patient–ventilator asynchronies based on lung hysteretic responses |
| title_short | Automated evaluation of typical patient–ventilator asynchronies based on lung hysteretic responses |
| title_sort | automated evaluation of typical patient ventilator asynchronies based on lung hysteretic responses |
| topic | Patient–ventilator asynchrony Mechanical ventilation PV loop Hysteretic lung mechanics Hysteresis loop analysis Intensive care unit |
| url | https://doi.org/10.1186/s12938-023-01165-0 |
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