Affiliation:
1. Yong Loo Lin School of Medicine, National University of Singapore;
2. Faculty of Science, National University of Singapore;
3. Division of Neurosurgery, University Surgical Cluster, National University Hospital, Singapore; and
4. Department of Electrical and Computer Engineering, National University of Singapore, Singapore
Abstract
OBJECTIVE
Intracranial pressure (ICP) monitoring is a widely utilized and essential tool for tracking neurosurgical patients, but there are limitations to the use of a solely ICP-based paradigm for guiding management. It has been suggested that ICP variability (ICPV), in addition to mean ICP, may be a useful predictor of neurological outcomes, as it represents an indirect measure of intact cerebral pressure autoregulation. However, the current literature regarding the applicability of ICPV shows conflicting associations between ICPV and mortality. Thus, the authors aimed to investigate the effect of ICPV on intracranial hypertensive episodes and mortality using the eICU Collaborative Research Database version 2.0.
METHODS
The authors extracted from the eICU database 1,815,676 ICP readings from 868 patients with neurosurgical conditions. ICPV was computed using two methods: the rolling standard deviation (RSD) and the absolute deviation from the rolling mean (DRM). An episode of intracranial hypertension was defined as at least 25 minutes of ICP > 22 mm Hg in any 30-minute window. The effects of mean ICPV on intracranial hypertension and mortality were computed using multivariate logistic regression. A recurrent neural network with long short-term memory was used for time-series predictions of ICP and ICPV to prognosticate future episodes of intracranial hypertension.
RESULTS
A higher mean ICPV was significantly associated with intracranial hypertension using both ICPV definitions (RSD: aOR 2.82, 95% CI 2.07–3.90, p < 0.001; DRM: aOR 3.93, 95% CI 2.77–5.69, p < 0.001). ICPV was significantly associated with mortality in patients with intracranial hypertension (RSD: aOR 1.28, 95% CI 1.04–1.61, p = 0.026, DRM: aOR 1.39, 95% CI 1.10–1.79, p = 0.007). In the machine learning models, both definitions of ICPV achieved similarly good results, with the best F1 score of 0.685 ± 0.026 and an area under the curve of 0.980 ± 0.003 achieved with the DRM definition over 20 minutes.
CONCLUSIONS
ICPV may be useful as an adjunct for the prognostication of intracranial hypertensive episodes and mortality in neurosurgical critical care as part of neuromonitoring. Further research on predicting future intracranial hypertensive episodes with ICPV may help clinicians react expediently to ICP changes in patients.
Publisher
Journal of Neurosurgery Publishing Group (JNSPG)
Subject
Genetics,Animal Science and Zoology
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