Low-Order Mechanistic Models for Volumetric and Temporal Capnography: Development, Validation, and Application
Objective : Develop low-order mechanistic models accounting quantitatively for, and identifiable from, the capnogram - the concentration in exhaled breath, recorded over time (Tcap) or exhaled volume (Vcap). Methods : The airflow model's single "alveolar" compartment has compliance...
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Published in | IEEE transactions on biomedical engineering Vol. 70; no. 9; pp. 1 - 12 |
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Main Authors | , , , , |
Format | Journal Article |
Language | English |
Published |
United States
IEEE
01.09.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
Subjects | |
Online Access | Get full text |
ISSN | 0018-9294 1558-2531 1558-2531 |
DOI | 10.1109/TBME.2023.3262764 |
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Abstract | Objective : Develop low-order mechanistic models accounting quantitatively for, and identifiable from, the capnogram - the concentration in exhaled breath, recorded over time (Tcap) or exhaled volume (Vcap). Methods : The airflow model's single "alveolar" compartment has compliance and inertance, and feeds a resistive unperfused airway comprising a laminar-flow region followed by a turbulent-mixing region. The gas-mixing model tracks mixing-region CO<inline-formula><tex-math notation="LaTeX">_{2}</tex-math></inline-formula> concentration, which is fitted breath-by-breath to the measured capnogram, yielding estimates of model parameters that characterize the capnogram. Results : For the 17 examined records (310 breaths) of airflow, airway pressure and Tcap from ventilated adult patients, the models fit closely (mean rmse 1% of end-tidal cŞoncentration on Vcap; 1.7% on Tcap). The associated parameters (4 for Vcap, 5 for Tcap) for each exhalation, and airflow parameters for the corresponding forced inhalation, are robustly estimated, and consonant with each other and literature values. The models also allow, using Tcap alone , estimation of the entire exhaled airflow waveform to within a scaling. This suggests new Tcap-based tests, analogous to spirometry but with normal breathing, for discriminating chronic obstructive pulmonary disease (COPD) from congestive heart failure (CHF). A version trained on 15 exhalations from each of 24 COPD/24 CHF Tcap records from one hospital, then tested 100 times with 15 random exhalations from each of 27 COPD/31 CHF Tcap records at another, gave mean accuracy 80.6% (stdev 2.1%). Another version, tested on 29 COPD/32 CHF, yielded AUROC 0.84. Conclusion : Our mechanistic models closely fit Tcap and Vcap measurements, and yield subject-specific parameter estimates. Significance : This can inform cardiorespiratory care. |
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AbstractList | Develop low-order mechanistic models accounting quantitatively for, and identifiable from, the capnogram - the CO 2 concentration in exhaled breath, recorded over time (Tcap) or exhaled volume (Vcap).OBJECTIVEDevelop low-order mechanistic models accounting quantitatively for, and identifiable from, the capnogram - the CO 2 concentration in exhaled breath, recorded over time (Tcap) or exhaled volume (Vcap).The airflow model's single "alveolar" compartment has compliance and inertance, and feeds a resistive unperfused airway comprising a laminar-flow region followed by a turbulent-mixing region. The gas-mixing model tracks mixing-region CO 2 concentration, fitted breath-by-breath to the measured capnogram, yielding estimates of model parameters that characterize the capnogram.METHODSThe airflow model's single "alveolar" compartment has compliance and inertance, and feeds a resistive unperfused airway comprising a laminar-flow region followed by a turbulent-mixing region. The gas-mixing model tracks mixing-region CO 2 concentration, fitted breath-by-breath to the measured capnogram, yielding estimates of model parameters that characterize the capnogram.For the 17 examined records (310 breaths) of airflow, airway pressure and Tcap from ventilated adult patients, the models fit closely (mean rmse 1% of end-tidal CO 2 concentration on Vcap; 1.7% on Tcap). The associated parameters (4 for Vcap, 5 for Tcap) for each exhalation, and airflow parameters for the corresponding forced inhalation, are robustly estimated, and consonant with literature values. The models also allow, using Tcap alone, estimation of the entire exhaled airflow waveform to within a scaling. This suggests new Tcap-based tests, analogous to spirometry but with normal breathing, for discriminating chronic obstructive pulmonary disease (COPD) from congestive heart failure (CHF). A version trained on 15 exhalations from each of 24 COPD/24 CHF Tcap records from one hospital, then tested 100 times with 15 random exhalations from each of 27 COPD/31 CHF Tcap records at another, gave mean accuracy 80.6% (stdev 2.1%). Another version, tested on 29 COPD/32 CHF, yielded AUROC 0.84.RESULTSFor the 17 examined records (310 breaths) of airflow, airway pressure and Tcap from ventilated adult patients, the models fit closely (mean rmse 1% of end-tidal CO 2 concentration on Vcap; 1.7% on Tcap). The associated parameters (4 for Vcap, 5 for Tcap) for each exhalation, and airflow parameters for the corresponding forced inhalation, are robustly estimated, and consonant with literature values. The models also allow, using Tcap alone, estimation of the entire exhaled airflow waveform to within a scaling. This suggests new Tcap-based tests, analogous to spirometry but with normal breathing, for discriminating chronic obstructive pulmonary disease (COPD) from congestive heart failure (CHF). A version trained on 15 exhalations from each of 24 COPD/24 CHF Tcap records from one hospital, then tested 100 times with 15 random exhalations from each of 27 COPD/31 CHF Tcap records at another, gave mean accuracy 80.6% (stdev 2.1%). Another version, tested on 29 COPD/32 CHF, yielded AUROC 0.84.Our mechanistic models closely fit Tcap and Vcap measurements, and yield subject-specific parameter estimates.CONCLUSIONOur mechanistic models closely fit Tcap and Vcap measurements, and yield subject-specific parameter estimates.This can inform cardiorespiratory care.SIGNIFICANCEThis can inform cardiorespiratory care. Objective : Develop low-order mechanistic models accounting quantitatively for, and identifiable from, the capnogram — the CO[Formula Omitted] concentration in exhaled breath, recorded over time (Tcap) or exhaled volume (Vcap). Methods : The airflow model's single “alveolar” compartment has compliance and inertance, and feeds a resistive unperfused airway comprising a laminar-flow region followed by a turbulent-mixing region. The gas-mixing model tracks mixing-region CO[Formula Omitted] concentration, fitted breath-by-breath to the measured capnogram, yielding estimates of model parameters that characterize the capnogram. Results : For the 17 examined records (310 breaths) of airflow, airway pressure and Tcap from ventilated adult patients, the models fit closely (mean rmse 1% of end-tidal CO[Formula Omitted] concentration on Vcap; 1.7% on Tcap). The associated parameters (4 for Vcap, 5 for Tcap) for each exhalation, and airflow parameters for the corresponding forced inhalation, are robustly estimated, and consonant with literature values. The models also allow, using Tcap alone , estimation of the entire exhaled airflow waveform to within a scaling. This suggests new Tcap-based tests, analogous to spirometry but with normal breathing, for discriminating chronic obstructive pulmonary disease (COPD) from congestive heart failure (CHF). A version trained on 15 exhalations from each of 24 COPD/24 CHF Tcap records from one hospital, then tested 100 times with 15 random exhalations from each of 27 COPD/31 CHF Tcap records at another, gave mean accuracy 80.6% (stdev 2.1%). Another version, tested on 29 COPD/32 CHF, yielded AUROC 0.84. Conclusion : Our mechanistic models closely fit Tcap and Vcap measurements, and yield subject-specific parameter estimates. Significance : This can inform cardiorespiratory care. Objective: Develop low-order mechanistic models accounting quantitatively for, and identifiable from, the capnogram - the concentration in exhaled breath, recorded over time (Tcap) or exhaled volume (Vcap). The airflow model's single "alveolar" compartment has compliance and inertance, and feeds a resistive unperfused airway comprising a laminar-flow region followed by a turbulent-mixing region. The gas-mixing model tracks mixing-region CO concentration, which is fitted breath-by-breath to the measured capnogram, yielding estimates of model parameters that characterize the capnogram. For the 17 examined records (310 breaths) of airflow, airway pressure and Tcap from ventilated adult patients, the models fit closely (mean rmse 1% of end-tidal cŞoncentration on Vcap; 1.7% on Tcap). The associated parameters (4 for Vcap, 5 for Tcap) for each exhalation, and airflow parameters for the corresponding forced inhalation, are robustly estimated, and consonant with each other and literature values. The models also allow, using Tcap alone, estimation of the entire exhaled airflow waveform to within a scaling. This suggests new Tcap-based tests, analogous to spirometry but with normal breathing, for discriminating chronic obstructive pulmonary disease (COPD) from congestive heart failure (CHF). A version trained on 15 exhalations from each of 24 COPD/24 CHF Tcap records from one hospital, then tested 100 times with 15 random exhalations from each of 27 COPD/31 CHF Tcap records at another, gave mean accuracy 80.6% (stdev 2.1%). Another version, tested on 29 COPD/32 CHF, yielded AUROC 0.84. Our mechanistic models closely fit Tcap and Vcap measurements, and yield subject-specific parameter estimates. This can inform cardiorespiratory care. Objective : Develop low-order mechanistic models accounting quantitatively for, and identifiable from, the capnogram - the concentration in exhaled breath, recorded over time (Tcap) or exhaled volume (Vcap). Methods : The airflow model's single "alveolar" compartment has compliance and inertance, and feeds a resistive unperfused airway comprising a laminar-flow region followed by a turbulent-mixing region. The gas-mixing model tracks mixing-region CO<inline-formula><tex-math notation="LaTeX">_{2}</tex-math></inline-formula> concentration, which is fitted breath-by-breath to the measured capnogram, yielding estimates of model parameters that characterize the capnogram. Results : For the 17 examined records (310 breaths) of airflow, airway pressure and Tcap from ventilated adult patients, the models fit closely (mean rmse 1% of end-tidal cŞoncentration on Vcap; 1.7% on Tcap). The associated parameters (4 for Vcap, 5 for Tcap) for each exhalation, and airflow parameters for the corresponding forced inhalation, are robustly estimated, and consonant with each other and literature values. The models also allow, using Tcap alone , estimation of the entire exhaled airflow waveform to within a scaling. This suggests new Tcap-based tests, analogous to spirometry but with normal breathing, for discriminating chronic obstructive pulmonary disease (COPD) from congestive heart failure (CHF). A version trained on 15 exhalations from each of 24 COPD/24 CHF Tcap records from one hospital, then tested 100 times with 15 random exhalations from each of 27 COPD/31 CHF Tcap records at another, gave mean accuracy 80.6% (stdev 2.1%). Another version, tested on 29 COPD/32 CHF, yielded AUROC 0.84. Conclusion : Our mechanistic models closely fit Tcap and Vcap measurements, and yield subject-specific parameter estimates. Significance : This can inform cardiorespiratory care. |
Author | Heldt, Thomas Krauss, Baruch S. You, Carine X. Murray, Elizabeth K. Verghese, George C. |
Author_xml | – sequence: 1 givenname: Elizabeth K. surname: Murray fullname: Murray, Elizabeth K. organization: Research Laboratory of Electronics and the EECS Department, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA – sequence: 2 givenname: Carine X. surname: You fullname: You, Carine X. organization: Research Laboratory of Electronics and the EECS Department, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA – sequence: 3 givenname: George C. surname: Verghese fullname: Verghese, George C. organization: Research Laboratory of Electronics and the EECS Department, Massachusetts Institute of Technology (MIT), Cambridge, MA, USA – sequence: 4 givenname: Baruch S. surname: Krauss fullname: Krauss, Baruch S. organization: Division of Emergency Medicine, Boston Children's Hospital, USA – sequence: 5 givenname: Thomas surname: Heldt fullname: Heldt, Thomas organization: Institute for Medical Engineering and Science, EECS Department, MIT, USA |
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Snippet | Objective : Develop low-order mechanistic models accounting quantitatively for, and identifiable from, the capnogram - the concentration in exhaled breath,... Objective: Develop low-order mechanistic models accounting quantitatively for, and identifiable from, the capnogram - the concentration in exhaled breath,... Objective : Develop low-order mechanistic models accounting quantitatively for, and identifiable from, the capnogram — the CO[Formula Omitted] concentration in... Develop low-order mechanistic models accounting quantitatively for, and identifiable from, the capnogram - the CO 2 concentration in exhaled breath, recorded... |
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SubjectTerms | Air flow Alveoli Atmospheric modeling Capnography Carbon dioxide Chronic obstructive pulmonary disease Congestive heart failure deadspace Estimates Exhalation Inhalation Laminar flow Lung Lung diseases Mathematical models Numerical models Obstructive lung disease Parameter estimation Physiology Pressure measurement Respiration respiratory model Respiratory tract Spirometry Ventilators Waveforms |
Title | Low-Order Mechanistic Models for Volumetric and Temporal Capnography: Development, Validation, and Application |
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