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Dynamic Intracranial Pressure Waveform Morphology Predicts Ventriculitis

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Abstract

Background

Intracranial pressure waveform morphology reflects compliance, which can be decreased by ventriculitis. We investigated whether morphologic analysis of intracranial pressure dynamics predicts the onset of ventriculitis.

Methods

Ventriculitis was defined as culture or Gram stain positive cerebrospinal fluid, warranting treatment. We developed a pipeline to automatically isolate segments of intracranial pressure waveforms from extraventricular catheters, extract dominant pulses, and obtain morphologically similar groupings. We used a previously validated clinician-supervised active learning paradigm to identify metaclusters of triphasic, single-peak, or artifactual peaks. Metacluster distributions were concatenated with temperature and routine blood laboratory values to create feature vectors. A L2-regularized logistic regression classifier was trained to distinguish patients with ventriculitis from matched controls, and the discriminative performance using area under receiver operating characteristic curve with bootstrapping cross-validation was reported.

Results

Fifty-eight patients were included for analysis. Twenty-seven patients with ventriculitis from two centers were identified. Thirty-one patients with catheters but without ventriculitis were selected as matched controls based on age, sex, and primary diagnosis. There were 1590 h of segmented data, including 396,130 dominant pulses in patients with ventriculitis and 557,435 pulses in patients without ventriculitis. There were significant differences in metacluster distribution comparing before culture-positivity versus during culture-positivity (p < 0.001) and after culture-positivity (p < 0.001). The classifier demonstrated good discrimination with median area under receiver operating characteristic 0.70 (interquartile range 0.55–0.80). There were 1.5 true alerts (ventriculitis detected) for every false alert.

Conclusions

Intracranial pressure waveform morphology analysis can classify ventriculitis without cerebrospinal fluid sampling.

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Funding

This study was funded by the National Institutes of Health (Grant Number: R21NS113055 [SP]) and American Heart Association (Grant Number 20POST35210653 [MM]).

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Authors and Affiliations

  1. Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons, 177 Fort Washington Ave, 8 Milstein – 300 Center, New York, NY, USA

    Murad Megjhani, Kalijah Terilli, Justine Chen, John Carlson, Angela Velazquez, David J. Roh, Sachin Agarwal, Jan Claassen & Soojin Park

  2. Program for Hospital and Intensive Care Informatics, Department of Neurology, Columbia University Vagelos College of Physicians and Surgeons, New York, NY, USA

    Murad Megjhani, Kalijah Terilli, John Carlson & Soojin Park

  3. Department of Neurology, Program in Trauma, University of Maryland School of Medicine, Baltimore, MD, USA

    Lakshman Kalasapudi, Neeraj Badjatia & Nicholas Morris

  4. New York Presbyterian Hospital, Columbia University Irving Medical Center, New York, NY, USA

    Justine Chen, David J. Roh, Sachin Agarwal, Jan Claassen, E. S. Connolly Jr. & Soojin Park

  5. Department of Anesthesia, Program in Trauma, University of Maryland School of Medicine, Baltimore, MD, USA

    Serenity Miller & Peter Hu

  6. Department of Neurosurgery, Columbia University, New York, NY, USA

    E. S. Connolly Jr.

  7. School of Nursing, Duke University, Durham, NC, USA

    Xiao Hu

  8. Departments of Electrical and Computer Engineering, Biostatistics and Bioinformatics, Surgery, Neurology, Duke University, Durham, NC, USA

    Xiao Hu

Authors
  1. Murad Megjhani
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  2. Kalijah Terilli
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  3. Lakshman Kalasapudi
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  4. Justine Chen
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  5. John Carlson
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  7. Neeraj Badjatia
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  8. Peter Hu
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  9. Angela Velazquez
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  10. David J. Roh
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  11. Sachin Agarwal
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  12. Jan Claassen
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  13. E. S. Connolly Jr.
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  14. Xiao Hu
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  15. Nicholas Morris
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  16. Soojin Park
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Contributions

Data collection (KT, LK, JC, JC, SM, NB, PH, DJR, SA, JC, ESC, and NM), Analysis (MM, SP, and KT), Writing (MM, SP, and KT), Editing (All). All authors have read and approved the final manuscript.

Corresponding author

Correspondence to Soojin Park.

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Conflict of interest

NM reports funding from Accelerated Translational Incubator Pilot Grant through the University of Maryland Baltimore Institute of Clinical and Translational Research unrelated to this study.

Ethical Approval/Informed Consent

The study was approved by the institutional review boards at the respective centers.

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Megjhani, M., Terilli, K., Kalasapudi, L. et al. Dynamic Intracranial Pressure Waveform Morphology Predicts Ventriculitis. Neurocrit Care 36, 404–411 (2022). https://doi.org/10.1007/s12028-021-01303-3

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  • DOI: https://doi.org/10.1007/s12028-021-01303-3

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