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Erschienen in: Neurocritical Care 2/2022

30.07.2021 | Original work

Dynamic Intracranial Pressure Waveform Morphology Predicts Ventriculitis

verfasst von: Murad Megjhani, Kalijah Terilli, Lakshman Kalasapudi, Justine Chen, John Carlson, Serenity Miller, Neeraj Badjatia, Peter Hu, Angela Velazquez, David J. Roh, Sachin Agarwal, Jan Claassen, E. S. Connolly Jr., Xiao Hu, Nicholas Morris, Soojin Park

Erschienen in: Neurocritical Care | Ausgabe 2/2022

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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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Metadaten
Titel
Dynamic Intracranial Pressure Waveform Morphology Predicts Ventriculitis
verfasst von
Murad Megjhani
Kalijah Terilli
Lakshman Kalasapudi
Justine Chen
John Carlson
Serenity Miller
Neeraj Badjatia
Peter Hu
Angela Velazquez
David J. Roh
Sachin Agarwal
Jan Claassen
E. S. Connolly Jr.
Xiao Hu
Nicholas Morris
Soojin Park
Publikationsdatum
30.07.2021
Verlag
Springer US
Erschienen in
Neurocritical Care / Ausgabe 2/2022
Print ISSN: 1541-6933
Elektronische ISSN: 1556-0961
DOI
https://doi.org/10.1007/s12028-021-01303-3

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