Computer-assisted capnogram analysis |
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Authors: | Huib R. van Genderingen Ir Nikolaus Gravenstein MD Jan J. van der Aa Ir Joachim S. Gravenstein MD |
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Affiliation: | (1) Department of Anesthesiology, University of Florida College of Medicine, Gainesville, FL.;(2) Present address: Margrietlaan 72, 6713 PN Ede, The Netherlands;(3) Department of Anesthesiology, J. Hillis Miller Health Center, Box J-254, 32610-0254 Gainesville, FL |
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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.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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Keywords: | Algorithm Carbon dioxide: measurement Complications: accidents Equipment: circuits computers ventilators Measurement techniques: computer algorithms infrared capnography waveform analysis Monitoring: ventilation |
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