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Computer application for respiratory data processing in closed circuit anesthesia.

T Oyama, H Ishihara

    International Journal of Clinical Monitoring and Computing
    |January 1, 1984
    PubMed
    Summary
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    A new computerized system monitors respiratory function during closed circuit anesthesia. It tracks oxygen consumption and carbon dioxide production, aiding anesthesiologists in optimizing gas flow and patient metabolic needs.

    Area of Science:

    • Anesthesiology
    • Biomedical Engineering
    • Respiratory Physiology

    Background:

    • Closed circuit anesthesia is increasingly common but presents challenges in monitoring respiratory gas exchange.
    • Continuous patient monitoring is crucial for maintaining anesthesia depth and preventing adverse events like hypoxia or hypercarbia.
    • Accurate assessment of metabolic requirements and gas flow is difficult with current methods.

    Purpose of the Study:

    • To develop and describe a computerized respiratory monitor system for closed circuit anesthesia.
    • To enable breath-by-breath monitoring of key respiratory parameters.
    • To assist anesthesiologists in optimizing gas flow and managing metabolic demands.

    Main Methods:

    • The system integrates a mass spectrometer, hot-wire respiratory flow meter, microcomputer, central display, and recorder.

    Related Experiment Videos

  • Respiratory parameters including O2 consumption, CO2 production, expiratory minute volume, and respiratory rate are measured.
  • The system was utilized in eleven surgical patients undergoing closed circuit anesthesia.

    • Main Results:

    • The computerized system successfully monitored respiratory parameters during closed circuit anesthesia.
    • Carbon dioxide production remained within normal ranges breath-by-breath.
    • Oxygen consumption exhibited significant variability throughout the procedures.

    Conclusions:

    • The developed computerized system effectively monitors respiratory gas exchange during closed circuit anesthesia.
    • It provides anesthesiologists with real-time data to detect optimal gas flow and metabolic requirements.
    • This technology can enhance patient safety and management in closed circuit anesthesia settings.