An Enhanced Automatic Algorithm for Estimation of Respiratory Variations in Arterial Pulse Pressure During Regions of Abrupt Hemodynamic Changes

We describe an improved automatic algorithm to estimate the pulse-pressure-variation (PPV) index from arterial blood pressure (ABP) signals. This enhanced algorithm enables for PPV estimation during periods of abrupt hemodynamic changes. Numerous studies have shown PPV to be one of most specific and...

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Published in:	IEEE transactions on biomedical engineering Vol. 56; no. 10; pp. 2537 - 2545
Main Authors:	Aboy, Mateo, Crespo, Cristina, Austin, Daniel
Format:	Journal Article
Language:	English
Published:	United States IEEE 01.10.2009 The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subjects:	Algorithms Animals Arterial blood pressure Blood pressure Blood Pressure - physiology Cardiac Output - physiology Change detection algorithms Delay Detection algorithms Envelope detectors Fluid dynamics Fluid flow Fluid responsiveness Fluids hemodynamic monitoring Hemodynamics Hemodynamics - physiology Injuries Kernel Liver Liver - injuries Mathematical analysis Models, Cardiovascular Monitoring, Physiologic - methods pulse contour analysis pulse contour cardiac output (PICCO) pulse-pressure-variation (PPV) index (PPV) Reproducibility of Results Respiratory Rate - physiology Shock, Hemorrhagic - physiopathology Signal Processing, Computer-Assisted stroke-volume-variation index (SSV) Swine Ventilation
ISSN:	0018-9294, 1558-2531, 1558-2531
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Abstract	We describe an improved automatic algorithm to estimate the pulse-pressure-variation (PPV) index from arterial blood pressure (ABP) signals. This enhanced algorithm enables for PPV estimation during periods of abrupt hemodynamic changes. Numerous studies have shown PPV to be one of most specific and sensitive predictors of fluid responsiveness in mechanically ventilated patients. The algorithm uses a beat detection algorithm to perform beat segmentation, kernel smoothers for envelope detection, and a suboptimal Kalman filter for PPV estimation and artifact removal. In this paper, we provide a detailed description of the algorithm and assess its performance on over 40 h of ABP signals obtained from 18 mechanically ventilated crossbred Yorkshire swine. The subjects underwent grade V liver injury after splenectomy, while receiving mechanical ventilation, and general anesthesia with isoflurane. All subjects in the database underwent a period of abrupt hemodynamic change after an induced grade V liver injury involving severe blood loss resulting in hemorrhagic shock, followed by fluid resuscitation with either 0.9% normal saline or lactated ringers solutions. Trained experts manually calculated PPV at five time instances during the period of abrupt hemodynamic changes. We report validation results comparing the proposed algorithm against a commercial system (pulse contour cardiac output, PICCO) with continuous PPV monitoring capabilities. Both systems were assessed during periods of abrupt hemodynamic changes against the ldquogold-standardrdquo PPV, calculated and manually annotated by experts. Our results indicate that the proposed algorithm performs considerably better than the PICCO system during regions of abrupt hemodynamic changes.
AbstractList	We describe an improved automatic algorithm to estimate the pulse-pressure-variation (PPV) index from arterial blood pressure (ABP) signals. This enhanced algorithm enables for PPV estimation during periods of abrupt hemodynamic changes. Numerous studies have shown PPV to be one of most specific and sensitive predictors of fluid responsiveness in mechanically ventilated patients. The algorithm uses a beat detection algorithm to perform beat segmentation, kernel smoothers for envelope detection, and a suboptimal Kalman filter for PPV estimation and artifact removal. In this paper, we provide a detailed description of the algorithm and assess its performance on over 40 h of ABP signals obtained from 18 mechanically ventilated crossbred Yorkshire swine. The subjects underwent grade V liver injury after splenectomy, while receiving mechanical ventilation, and general anesthesia with isoflurane. All subjects in the database underwent a period of abrupt hemodynamic change after an induced grade V liver injury involving severe blood loss resulting in hemorrhagic shock, followed by fluid resuscitation with either 0.9% normal saline or lactated ringers solutions. Trained experts manually calculated PPV at five time instances during the period of abrupt hemodynamic changes. We report validation results comparing the proposed algorithm against a commercial system (pulse contour cardiac output, PICCO) with continuous PPV monitoring capabilities. Both systems were assessed during periods of abrupt hemodynamic changes against the "gold-standard" PPV, calculated and manually annotated by experts. Our results indicate that the proposed algorithm performs considerably better than the PICCO system during regions of abrupt hemodynamic changes. We describe an improved automatic algorithm to estimate the pulse-pressure-variation (PPV) index from arterial blood pressure (ABP) signals. This enhanced algorithm enables for PPV estimation during periods of abrupt hemodynamic changes. Numerous studies have shown PPV to be one of most specific and sensitive predictors of fluid responsiveness in mechanically ventilated patients. The algorithm uses a beat detection algorithm to perform beat segmentation, kernel smoothers for envelope detection, and a suboptimal Kalman filter for PPV estimation and artifact removal. In this paper, we provide a detailed description of the algorithm and assess its performance on over 40 h of ABP signals obtained from 18 mechanically ventilated crossbred Yorkshire swine. The subjects underwent grade V liver injury after splenectomy, while receiving mechanical ventilation, and general anesthesia with isoflurane. All subjects in the database underwent a period of abrupt hemodynamic change after an induced grade V liver injury involving severe blood loss resulting in hemorrhagic shock, followed by fluid resuscitation with either 0.9% normal saline or lactated ringers solutions. Trained experts manually calculated PPV at five time instances during the period of abrupt hemodynamic changes. We report validation results comparing the proposed algorithm against a commercial system (pulse contour cardiac output, PICCO) with continuous PPV monitoring capabilities. Both systems were assessed during periods of abrupt hemodynamic changes against the ldquogold-standardrdquo PPV, calculated and manually annotated by experts. Our results indicate that the proposed algorithm performs considerably better than the PICCO system during regions of abrupt hemodynamic changes. We describe an improved automatic algorithm to estimate the pulse-pressure-variation (PPV) index from arterial blood pressure (ABP) signals. This enhanced algorithm enables for PPV estimation during periods of abrupt hemodynamic changes. Numerous studies have shown PPV to be one of most specific and sensitive predictors of fluid responsiveness in mechanically ventilated patients. The algorithm uses a beat detection algorithm to perform beat segmentation, kernel smoothers for envelope detection, and a suboptimal Kalman filter for PPV estimation and artifact removal. In this paper, we provide a detailed description of the algorithm and assess its performance on over 40 h of ABP signals obtained from 18 mechanically ventilated crossbred Yorkshire swine. The subjects underwent grade V liver injury after splenectomy, while receiving mechanical ventilation, and general anesthesia with isoflurane. All subjects in the database underwent a period of abrupt hemodynamic change after an induced grade V liver injury involving severe blood loss resulting in hemorrhagic shock, followed by fluid resuscitation with either 0.9% normal saline or lactated ringers solutions. Trained experts manually calculated PPV at five time instances during the period of abrupt hemodynamic changes. We report validation results comparing the proposed algorithm against a commercial system (pulse contour cardiac output, PICCO) with continuous PPV monitoring capabilities. Both systems were assessed during periods of abrupt hemodynamic changes against the "gold-standard" PPV, calculated and manually annotated by experts. Our results indicate that the proposed algorithm performs considerably better than the PICCO system during regions of abrupt hemodynamic changes.We describe an improved automatic algorithm to estimate the pulse-pressure-variation (PPV) index from arterial blood pressure (ABP) signals. This enhanced algorithm enables for PPV estimation during periods of abrupt hemodynamic changes. Numerous studies have shown PPV to be one of most specific and sensitive predictors of fluid responsiveness in mechanically ventilated patients. The algorithm uses a beat detection algorithm to perform beat segmentation, kernel smoothers for envelope detection, and a suboptimal Kalman filter for PPV estimation and artifact removal. In this paper, we provide a detailed description of the algorithm and assess its performance on over 40 h of ABP signals obtained from 18 mechanically ventilated crossbred Yorkshire swine. The subjects underwent grade V liver injury after splenectomy, while receiving mechanical ventilation, and general anesthesia with isoflurane. All subjects in the database underwent a period of abrupt hemodynamic change after an induced grade V liver injury involving severe blood loss resulting in hemorrhagic shock, followed by fluid resuscitation with either 0.9% normal saline or lactated ringers solutions. Trained experts manually calculated PPV at five time instances during the period of abrupt hemodynamic changes. We report validation results comparing the proposed algorithm against a commercial system (pulse contour cardiac output, PICCO) with continuous PPV monitoring capabilities. Both systems were assessed during periods of abrupt hemodynamic changes against the "gold-standard" PPV, calculated and manually annotated by experts. Our results indicate that the proposed algorithm performs considerably better than the PICCO system during regions of abrupt hemodynamic changes. All subjects in the database underwent a period of abrupt hemodynamic change after an induced grade V liver injury involving severe blood loss resulting in hemorrhagic shock, followed by fluid resuscitation with either 0.9% normal saline or lactated ringers solutions.
Author	Aboy, Mateo Crespo, Cristina Austin, Daniel
Author_xml	– sequence: 1 givenname: Mateo surname: Aboy fullname: Aboy, Mateo email: mateoaboy@ieee.org organization: Electr. Eng. Dept., Oregon Inst. of Technol. (OIT), Portland, OR, USA – sequence: 2 givenname: Cristina surname: Crespo fullname: Crespo, Cristina organization: Electr. Eng. Dept., Oregon Inst. of Technol. (OIT), Portland, OR, USA – sequence: 3 givenname: Daniel surname: Austin fullname: Austin, Daniel organization: Electr. Eng. Dept., Oregon Inst. of Technol. (OIT), Portland, OR, USA
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SubjectTerms	Algorithms Animals Arterial blood pressure Blood pressure Blood Pressure - physiology Cardiac Output - physiology Change detection algorithms Delay Detection algorithms Envelope detectors Fluid dynamics Fluid flow Fluid responsiveness Fluids hemodynamic monitoring Hemodynamics Hemodynamics - physiology Injuries Kernel Liver Liver - injuries Mathematical analysis Models, Cardiovascular Monitoring, Physiologic - methods pulse contour analysis pulse contour cardiac output (PICCO) pulse-pressure-variation (PPV) index (PPV) Reproducibility of Results Respiratory Rate - physiology Shock, Hemorrhagic - physiopathology Signal Processing, Computer-Assisted stroke-volume-variation index (SSV) Swine Ventilation
Title	An Enhanced Automatic Algorithm for Estimation of Respiratory Variations in Arterial Pulse Pressure During Regions of Abrupt Hemodynamic Changes
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