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 inIEEE transactions on biomedical engineering Vol. 70; no. 9; pp. 1 - 12
Main Authors Murray, Elizabeth K., You, Carine X., Verghese, George C., Krauss, Baruch S., Heldt, Thomas
Format Journal Article
LanguageEnglish
Published United States IEEE 01.09.2023
The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
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Online AccessGet full text
ISSN0018-9294
1558-2531
1558-2531
DOI10.1109/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.
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.
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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
URI https://ieeexplore.ieee.org/document/10086622
https://www.ncbi.nlm.nih.gov/pubmed/37030832
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