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Comparing the novel microstream and the traditional mainstream method of end-tidal CO2 monitoring with respect to PaCO2 as gold standard in intubated critically ill children.

Muhterem DuyuAnıl Dogan BektasZeynep KarakayaMeral BaharAybüke GunalpYasemin Mocan CaglarMeryem Nihal YerselOzlem Bozkurt
Published in: Scientific reports (2020)
The objective of this study was to evaluate a novel microstream method by comparison with PaCO2 and the more standard mainstream capnometer in intubated pediatric patients. We hypothesized that the novel microstream method would superior compared to the traditional mainstream method in predicting PaCO2. This was a prospective single-center comparative study. The study was carried out on 174 subjects with a total of 1338 values for each method. Data were collected prospectively from mainstream and microstream capnometer simultaneously and compared with PaCO2 results. Although both mainstream PetCO2 (mainPetCO2) and microstream PetCO2 (microPetCO2) were moderately correlated (r = 0.63 and r = 0.68, respectively) with PaCO2 values, mainPetCO2 was in better agreement with PaCO2 in all subjects (bias ± precision values of 3.8 ± 8.9 and 7.3 ± 8.2 mmHg, respectively). In those with severe pulmonary disease, the mainPetCO2 and microPetCO2 methods were highly correlated with PaCO2 (r = 0.80 and r = 0.81, respectively); however, the biases of both methods increased (14.8 ± 9.1 mmHg and 16.2 ± 9.0 mmHg, respectively). In cases with increased physiologic dead space ventilation, the agreement levels of mainPetCO2 and microPetCO2 methods became distorted (bias ± precision values of 20.9 ± 11.2 and 25.0 ± 11.8 mm Hg, respectively) even though mainPetCO2 and microPetCO2 were highly correlated (r = 0.78 and r = 0.78, respectively). It was found that the novel microstream capnometer method for PetCO2 measurements provided no superiority to the traditional mainstream method. Both capnometer methods may be useful in predicting the trend of PaCO2 due to significant correlations with the gold standard measurement in cases with severe pulmonary disease or increased physiological dead space -despite reduced accuracy.
Keyphrases
  • pulmonary hypertension
  • early onset
  • machine learning
  • intensive care unit
  • silver nanoparticles
  • carbon dioxide
  • respiratory failure