Clinical Decision Support for Traumatic Brain Injury: Identifying a Framework for Practical Model-Based Intracranial Pressure Estimation at Multihour Timescales (Preprint) Article Swipe
J.N. Stroh
,
Tellen D. Bennett
,
Vitaly O. Kheyfets
,
David J. Albers
·
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.2196/preprints.23215
YOU?
·
· 2020
· Open Access
·
· DOI: https://doi.org/10.2196/preprints.23215
BACKGROUND The clinical mitigation of intracranial hypertension due to traumatic brain injury requires timely knowledge of intracranial pressure to avoid secondary injury or death. Noninvasive intracranial pressure (nICP) estimation that operates sufficiently fast at multihour timescales and requires only common patient measurements is a desirable tool for clinical decision support and improving traumatic brain injury patient outcomes. However, existing model-based nICP estimation methods may be too slow or require data that are not easily obtained. OBJECTIVE This work considers short- and real-time nICP estimation at multihour timescales based on arterial blood pressure (ABP) to better inform the ongoing development of practical models with commonly available data. METHODS We assess and analyze the effects of two distinct pathways of model development, either by increasing physiological integration using a simple pressure estimation model, or by increasing physiological fidelity using a more complex model. Comparison of the model approaches is performed using a set of quantitative model validation criteria over hour-scale times applied to model nICP estimates in relation to observed ICP. RESULTS The simple fully coupled estimation scheme based on windowed regression outperforms a more complex nICP model with prescribed intracranial inflow when pulsatile ABP inflow conditions are provided. We also show that the simple estimation data requirements can be reduced to 1-minute averaged ABP summary data under generic waveform representation. CONCLUSIONS Stronger performance of the simple bidirectional model indicates that feedback between the systemic vascular network and nICP estimation scheme is crucial for modeling over long intervals. However, simple model reduction to ABP-only dependence limits its utility in cases involving other brain injuries such as ischemic stroke and subarachnoid hemorrhage. Additional methodologies and considerations needed to overcome these limitations are illustrated and discussed. CLINICALTRIAL
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- Type
- preprint
- Language
- en
- Landing Page
- https://doi.org/10.2196/preprints.23215
- OA Status
- gold
- References
- 54
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- 10
- OpenAlex ID
- https://openalex.org/W4210671793
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https://openalex.org/W4210671793Canonical identifier for this work in OpenAlex
- DOI
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https://doi.org/10.2196/preprints.23215Digital Object Identifier
- Title
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Clinical Decision Support for Traumatic Brain Injury: Identifying a Framework for Practical Model-Based Intracranial Pressure Estimation at Multihour Timescales (Preprint)Work title
- Type
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preprintOpenAlex work type
- Language
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enPrimary language
- Publication year
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2020Year of publication
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2020-08-04Full publication date if available
- Authors
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J.N. Stroh, Tellen D. Bennett, Vitaly O. Kheyfets, David J. AlbersList of authors in order
- Landing page
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https://doi.org/10.2196/preprints.23215Publisher landing page
- Open access
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YesWhether a free full text is available
- OA status
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goldOpen access status per OpenAlex
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https://doi.org/10.2196/preprints.23215Direct OA link when available
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Traumatic brain injury, Intracranial pressure, Computer science, Inflow, Estimation, Representation (politics), Preprint, Gold standard (test), Medicine, Internal medicine, Surgery, Physics, Law, Psychiatry, Political science, Mechanics, World Wide Web, Politics, Economics, ManagementTop concepts (fields/topics) attached by OpenAlex
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0Total citation count in OpenAlex
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54Number of works referenced by this work
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| abstract_inverted_index.methods | 63 |
| abstract_inverted_index.network | 243 |
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| abstract_inverted_index.summary | 220 |
| abstract_inverted_index.support | 50 |
| abstract_inverted_index.utility | 264 |
| abstract_inverted_index.1-minute | 217 |
| abstract_inverted_index.ABP-only | 260 |
| abstract_inverted_index.However, | 58, 255 |
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| abstract_inverted_index.arterial | 92 |
| abstract_inverted_index.averaged | 218 |
| abstract_inverted_index.clinical | 3, 48 |
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| abstract_inverted_index.criteria | 160 |
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| abstract_inverted_index.pressure | 18, 27, 94, 133 |
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| abstract_inverted_index.requires | 13, 38 |
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| abstract_inverted_index.vascular | 242 |
| abstract_inverted_index.waveform | 224 |
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| abstract_inverted_index.involving | 267 |
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| abstract_inverted_index.multihour | 35, 88 |
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| abstract_inverted_index.outcomes. | 57 |
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| abstract_inverted_index.practical | 103 |
| abstract_inverted_index.provided. | 203 |
| abstract_inverted_index.pulsatile | 198 |
| abstract_inverted_index.real-time | 84 |
| abstract_inverted_index.reduction | 258 |
| abstract_inverted_index.secondary | 21 |
| abstract_inverted_index.traumatic | 10, 53 |
| abstract_inverted_index.Additional | 278 |
| abstract_inverted_index.Comparison | 146 |
| abstract_inverted_index.approaches | 150 |
| abstract_inverted_index.conditions | 201 |
| abstract_inverted_index.dependence | 261 |
| abstract_inverted_index.discussed. | 290 |
| abstract_inverted_index.estimation | 29, 62, 86, 134, 181, 210, 246 |
| abstract_inverted_index.hour-scale | 162 |
| abstract_inverted_index.increasing | 127, 138 |
| abstract_inverted_index.intervals. | 254 |
| abstract_inverted_index.mitigation | 4 |
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| abstract_inverted_index.timescales | 36, 89 |
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| abstract_inverted_index.hemorrhage. | 277 |
| abstract_inverted_index.illustrated | 288 |
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| abstract_inverted_index.limitations | 286 |
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| abstract_inverted_index.performance | 230 |
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| abstract_inverted_index.hypertension | 7 |
| abstract_inverted_index.intracranial | 6, 17, 26, 195 |
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| abstract_inverted_index.quantitative | 157 |
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| abstract_inverted_index.physiological | 128, 139 |
| abstract_inverted_index.considerations | 281 |
| abstract_inverted_index.representation. | 225 |
| abstract_inverted_index.<title>METHODS</title> | 111 |
| abstract_inverted_index.<title>RESULTS</title> | 176 |
| abstract_inverted_index.<title>OBJECTIVE</title> | 78 |
| abstract_inverted_index.<title>BACKGROUND</title> | 1 |
| abstract_inverted_index.<title>CONCLUSIONS</title> | 228 |
| abstract_inverted_index.<title>CLINICALTRIAL</title> | 293 |
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| institutions_distinct_count | 4 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/3 |
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| sustainable_development_goals[0].display_name | Good health and well-being |
| citation_normalized_percentile.value | 0.2760133 |
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| citation_normalized_percentile.is_in_top_10_percent | False |