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 CO
$_{2}$
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
$_{2}$
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
$_{2}$
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.
Conclusion
: Our mechanistic models closely fit Tcap and Vcap measurements, and yield subject-specific parameter estimates.
Significance
: This can inform cardiorespiratory care.