Abstract
Characteristic abnormal carbon dioxide waveforms from patients with mechanically ventilated lungs are observed when, for example, valves are incompetent, the airway is obstructed, the breathing circuit becomes disconnected, or a patient overrides mechanical ventilation with spontaneous breaths. Automated observation of the carbon dioxide waveform provides a uniform, concise, and consistent interpretation of the capnogram. This article describes a computer algorithm for analyzing and classifying capnograms as normal or as belonging to one of the categories above. The algorithm also generates a diagnostic message when the capnogram deviates from a learned norm for at least three consecutive waveforms (and thus reduces the influence of artifacts). Clinical experience shows reliable waveform recognition by the algorithm.
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Supported in part by a grant from Datascope Corporation.
The authors thank David A. Paulus, MD, and Jeffrey M. Feldman, MD, for their assistance and advice.
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van Genderingen, H.R., Gravenstein, N., van der Aa, J.J. et al. Computer-assisted capnogram analysis. J Clin Monitor Comput 3, 194–200 (1987). https://doi.org/10.1007/BF01695944
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DOI: https://doi.org/10.1007/BF01695944