Journal of Clinical Monitoring and Computing

, Volume 27, Issue 5, pp 561–565

Respiratory parameters as a surrogate marker for duration of intubation: potential application of automated vital sign collection

Original Research


Prolonged time during endotracheal tube placement has been associated with poor outcomes, including cardiac arrest and death. For this reason, the accurate measurement of the duration of intubation time is an important metric in studies that evaluate interventions to improve airway outcomes. In the current study we correlated the gaps in routinely measured ventilatory parameters with duration of the intubation procedure to determine if these intervals could be used to accurately calculate the intubation time. Fifty-six random airway management encounters were video recorded along with a continuous video feed of the patient monitor. Intubation event times were measured and correlated with “gap” times of end-tidal carbon dioxide, airway pressure, airway flow, tidal volume, and respiratory rate defined as the disappearance of the parameter at the end of mask ventilation to the reappearance after intubation. Scatter plots were generated for intubation times versus each parameter time gap and correlation coefficients were calculated. Of the 56 recordings 50 of were suitable for analysis. The correlation of the gaps in airway pressure and airway flow correlated best with the duration of intubation (R2 = 0.88) and were available on all cases. The gap in measured tidal volume of 39 ± 53 s most closely approximated the actual duration of intubation of 38 ± 28 s, (R2 = 0.85, y = x − 0.87). During intubation, the disappearance gaps in tidal volume, and the airway pressure and flow waveforms highly correlate with the duration of the intubation procedure and may be useful in the evaluation of airway management interventions. However, just as there are limitations to a labor-intensive method of recording airway management timing, there are limitations to using an automated method.


Capnography Intubation Airway management Ventilator parameters Automated anesthesia information systems 

Copyright information

© Springer Science+Business Media New York 2013

Authors and Affiliations

  • Doug Hester
    • 1
  • Stuart McGrane
    • 2
  • Michael S. Higgins
    • 1
  1. 1.Department of AnesthesiologyVanderbilt University School of MedicineNashvilleUSA
  2. 2.Division of Critical Care, Department of AnesthesiologyVanderbilt University School of MedicineNashvilleUSA

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