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Intracranial Pressure and Neuromonitoring XVII pp 243–248Cite as

Comparison of Two Algorithms Analysing the Intracranial Pressure Curve in Terms of the Accuracy of Their Start-Point Detection and Resistance to Artefacts

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Part of the book series: Acta Neurochirurgica Supplement ((NEUROCHIRURGICA,volume 131))

Abstract

Objectives: For further insight into the possibly predictive quality of the intracranial pressure (ICP) waveform morphology a definite and reliable identification of its components is a prerequisite but presents the problem of artefacts in physiological signals.

Methods: ICP and electrocardiogram (ECG) data were recorded to depict not only their numerical value but also their respective waveforms and were analysed by two algorithms, which were then compared for their artefact resistance.

The algorithms in question identify the start point of every ICP wave, one (AR[SA]) by scale analysis, the other (AR[ECG]) by analysing the ICP wave linked to the ECG.

Results: Start-point identification accuracy in rhythmic patients showed sensitivity of 95.14% for AR[SA] and 99.99% for AR[ECG], with a positive predictive value (ppv) of 98.30% for AR[SA] and 99.76% for AR[ECG].

In arrhythmic patients sensitivity was 98.05% for AR[SA] and 99.73% for AR[ECG], with a ppv of 100% for AR[SA] and 99.78% for AR[ECG].

Conclusions: AR[ECG] has proven to be more resistant to artefacts than AR[SA], even in cases such as cardiac arrhythmia. It facilitates reliable, three-dimensional visualisation of long-term changes in ICP-wave morphology and is thus suited for analysis in cases of more complex or irregular vital parameters.

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Change history

  • 29 October 2021

    The original version of Chapter 46 was revised.

Abbreviations

ABP:

Arterial blood pressure

BP:

Blood pressure

CBF:

Cerebral blood flow

CPP:

Cerebral perfusion pressure

ECG:

Electrocardiogram

GCS:

Glasgow coma scale

GOS:

Glasgow outcome scale

ICH:

Intracranial haemorrhage

ICP:

Intracranial pressure

ICU:

Intensive care unit

MAP:

Mean arterial blood pressure

PEEP:

Positive end-expiratory pressure

SAH:

Subarachnoid haemorrhage

TBI:

Traumatic brain injury

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Acknowledgments

We received research grants from Software AG Stiftung and would like to thank them for their generous funding of this work.

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Authors and Affiliations

  1. Gemeinschaftskrankenhaus Herdecke (Community Hospital Herdecke), Herdecke, Germany

    Anna-Li Schönenberg-Tu, Benjamin Pätzold, Adam Lichota, Ghaith Al Assali, Friedrich Edelhäuser, Martin Marsch & Wolfram Scharbrodt

  2. Institute of Integrative Medicine, University of Witten, Herdecke, Germany

    Christa Raak, Friedrich Edelhäuser & Dirk Cysarz

  3. University of Witten, Herdecke, Germany

    Friedrich Edelhäuser

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  1. Anna-Li Schönenberg-Tu
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  9. Wolfram Scharbrodt
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Corresponding author

Correspondence to Anna-Li Schönenberg-Tu .

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Editors and Affiliations

  1. Department of Neurosurgery, University Hospitals Leuven, Leuven, Belgium

    Bart Depreitere

  2. Department of Intensive Care Medicine, University Hospitals Leuven, Leuven, Belgium

    Geert Meyfroidt

  3. Department of Intensive Care Medicine, University Hospitals Leuven, Leuven, Belgium

    Fabian Güiza

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The authors are employed by their institutions as stated above independently of this research. There are no conflicts of interest.

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Schönenberg-Tu, AL. et al. (2021). Comparison of Two Algorithms Analysing the Intracranial Pressure Curve in Terms of the Accuracy of Their Start-Point Detection and Resistance to Artefacts. In: Depreitere, B., Meyfroidt, G., Güiza, F. (eds) Intracranial Pressure and Neuromonitoring XVII. Acta Neurochirurgica Supplement, vol 131. Springer, Cham. https://doi.org/10.1007/978-3-030-59436-7_46

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  • DOI: https://doi.org/10.1007/978-3-030-59436-7_46

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  • Publisher Name: Springer, Cham

  • Print ISBN: 978-3-030-59435-0

  • Online ISBN: 978-3-030-59436-7

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