Related Experiment Video
Updated: Aug 19, 2026

Evaluation of Capnography Sampling Line Compatibility and Accuracy when Used with a Portable Capnography Monitor
Published on: September 29, 2020
Evaluation of capnography using a genetic algorithm to predict PaCO2
Milo Engoren1, Michael Plewa, David O'Hara
1Department of Anesthesiology, St. Vincent Mercy Medical Center, 2213 Cherry St, Toledo, OH 43608, USA. engoren@pol.net
Introduction:
Noninvasive estimates of Paco(2) are usually done by measuring exhaled carbon dioxide at end-expiration (Petco(2)). While commonly used in studies involving healthy patients, it is less useful in sicker patients. Conditions that affect the terminal dead space and hence the accuracy of Petco(2) as a surrogate for Paco(2) may also affect other components of the capnogram. A genetic algorithm is a computer technique for discovering relationships between variables. The purpose of this study was to use a genetic algorithm to improve the precision of Paco(2) prediction in comparison to Petco(2).
Methods:
Inspiratory and expiratory volumes were measured and analyzed by the computerized capnogram. Data were recorded for 2 min. Within 5 min of recording the capnograms, arterial blood gases were obtained. After excluding artifact and incomplete capnograms, five of the remaining breaths from each patient were selected. A genetic algorithm, constructed in postfix notation, consisted of 1,000 chromosomes with genes randomly selected from the 11 capnographic data fields and mathematical operators. The algorithm was constructed on 400 breaths from 83 randomly selected patients (construction group) and tested on 160 breaths from the remaining 32 patients (test group).
Results:
For the construction group, the bias and precision between Petco(2) and Paco(2) were 4.3 +/- 4.9 mm Hg (mean +/- SD). For the 160 breaths in the test group, Petco(2) predicted Paco(2) with bias and precision of 2.9 +/- 4.2 mm Hg. The best chromosome found by the genetic algorithm was (10 x 5 + 5 x 5 x 5)/(10 x 10) x Petco(2) - (5 x 5 x 10 + 5 x 5)/(10 x 10) x int time + 2 x 2 x 2 x 2 + (2 x 2)/10, which reduces to 0.65 x Petco(2) - 2.75 x int time + 16.4. This produced a bias and precision of 0.9 +/- 4.1 mm Hg in the construction group and 0 +/- 3.7 mm Hg in the test group (p < 0.01).
Conclusions:
In this study of nonintubated emergency department patients, a genetic algorithm produced an improvement in bias and precision of Paco(2) prediction.
More Related Videos
Related Concept Videos
Assessment of Diffusion and Perfusion
The Role of Diffusion in Respiration
Diffusion is the process by which molecules move from an area of higher concentration to an area of lower concentration. In the respiratory system, this principle...
Diagnosing Acidosis and Alkalosis
First, the pH level is assessed to determine whether the blood pH is normal (7.35–7.45), low (acidosis), or high (alkalosis).
Next, the PCO2 and HCO3− values are examined to...
Chemical Factors Affecting Respiration Centers
CO2 has a potent influence on respiration and is strictly regulated. Under...
Acute Respiratory Failure-III

