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Record W2993261428 · doi:10.1007/s12028-019-00885-3

Relationship Between Measures of Cerebrovascular Reactivity and Intracranial Lesion Progression in Acute TBI Patients: an Exploratory Analysis

2019· article· en· W2993261428 on OpenAlexaff
François Mathieu, Frederick A. Zeiler, Daniel Whitehouse, Tilak Das, Ari Ercole, Peter Smielewski, Peter J. Hutchinson, Marek Czosnyka, Virginia Newcombe, David Menon

Bibliographic record

VenueNeurocritical Care · 2019
Typearticle
Languageen
FieldMedicine
TopicTraumatic Brain Injury and Neurovascular Disturbances
Canadian institutionsUniversity of ManitobaUniversity of Toronto
FundersNational Institute of Neurological Disorders and StrokeCambridge TrustCambridge Commonwealth TrustNational Institute of Biomedical Imaging and BioengineeringNIHR Cambridge Biomedical Research CentreAcademy of Medical SciencesNational Institutes of HealthUniversity of CambridgeDepartment of Health and Social CareCambridge University HospitalsNational Institute for Health and Care Research
KeywordsMedicineTraumatic brain injuryIntracranial pressureCerebral perfusion pressureLesionNeurologyPopulationCohortCardiologyInternal medicineRadiologyAnesthesiaCerebral blood flowPathology

Abstract

fetched live from OpenAlex

BACKGROUND: Failure of cerebral autoregulation and progression of intracranial lesion have both been shown to contribute to poor outcome in patients with acute traumatic brain injury (TBI), but the interplay between the two phenomena has not been investigated. Preliminary evidence leads us to hypothesize that brain tissue adjacent to primary injury foci may be more vulnerable to large fluctuations in blood flow in the absence of intact autoregulatory mechanisms. The goal of this study was therefore to assess the influence of cerebrovascular reactivity measures on radiological lesion expansion in a cohort of patients with acute TBI. METHODS: We conducted a retrospective cohort analysis on 50 TBI patients who had undergone high-frequency multimodal intracranial monitoring and for which at least two brain computed tomography (CT) scans had been performed in the acute phase of injury. We first performed univariate analyses on the full cohort to identify non-neurophysiological factors (i.e., initial lesion volume, timing of scan, coagulopathy) associated with traumatic lesion growth in this population. In a subset analysis of 23 patients who had intracranial recording data covering the period between the initial and repeat CT scan, we then correlated changes in serial volumetric lesion measurements with cerebrovascular reactivity metrics derived from the pressure reactivity index (PRx), pulse amplitude index (PAx), and RAC (correlation coefficient between the pulse amplitude of intracranial pressure and cerebral perfusion pressure). Using multivariate methods, these results were subsequently adjusted for the non-neurophysiological confounders identified in the univariate analyses. RESULTS: We observed significant positive linear associations between the degree of cerebrovascular reactivity impairment and progression of pericontusional edema. The strongest correlations were observed between edema progression and the following indices of cerebrovascular reactivity between sequential scans: % time PRx > 0.25 (r = 0.69, p = 0.002) and % time PAx > 0.25 (r = 0.64, p = 0.006). These associations remained significant after adjusting for initial lesion volume and mean cerebral perfusion pressure. In contrast, progression of the hemorrhagic core and extra-axial hemorrhage volume did not appear to be strongly influenced by autoregulatory status. CONCLUSIONS: Our preliminary findings suggest a possible link between autoregulatory failure and traumatic edema progression, which warrants re-evaluation in larger-scale prospective studies.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.514

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.046
GPT teacher head0.317
Teacher spread0.272 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations26
Published2019
Admission routes1
Has abstractyes

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