Evidence map›Paper›PMID 40243158›Full record

ArticlePhysiological reports2025

Untangling discrepancies between cerebrovascular autoregulation correlation coefficients: An exploration of filters, coherence and power.

Stefan Yu Bögli, Ihsane Olakorede, Erta Beqiri, Giada Cucciolini, Virginia Motroni, Claudia Ann Smith, Marina Sandra Cherchi, Ronan O'Leary, Peter Smielewski

Abstract read
PubMed Full text at PMC Publisher
In one paragraph

Article in Physiological reports, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 7 papers.

0numbers the graph read from it
0cells of the map it votes in
7citing papers in PubMed
–field-weighted citation impact
1 · What the graph read from it

What it found

Each row is one number read from the abstract, on the scale the paper reported it, with its interval. Left of the dashed line favours the treatment, right favours the comparator. Under each row is the sentence it came from. New to these charts? A ten-minute tutorial.

The abstract states no effect estimate the extractor could read, or names no intervention and outcome on the map, so this paper lights no cell and moves no belief. It is still indexed, cited and linked below.

2 · The registry

The trial behind it

Trials whose registry record cites this paper, or whose number appears in the abstract. A trial that started after this paper was published is citing it as background, not reporting it.

Neither the registry nor the abstract names a trial number. If this is a trial report, that itself is worth knowing.

3 · Its place in the literature

Who cites it

7 citing papers in PubMed.

  1. Article
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4 · The record

Corrections and comments

PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.

5 · Who and what money

Authors and funding

9 authors.

Stefan Yu BögliBrain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.ORCID 0000-0001-5386-0811
Ihsane OlakoredeBrain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Erta BeqiriBrain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Giada CuccioliniBrain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Virginia MotroniBrain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Claudia Ann SmithBrain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Marina Sandra CherchiBrain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.
Ronan O'LearyNeurosciences and Trauma Critical Care Unit, Addenbrooke's Hospital, Cambridge University Hospitals, Cambridge, UK.
Peter SmielewskiBrain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, UK.

Funding

Cambridge Trust CIS ScholarshipCantabrian Health Service PESI/1/22Medical Research Council and Gates Cambridge Scholarship MR N013433-1Patrick and Margaret Flanagan Skye Cambridge Trust ScholarshipSwiss National Science Foundation 210839/225270
6 · The paper itself

Abstract

Cerebrovascular autoregulation (CAR) maintains stable cerebral perfusion by adjusting arteriole diameters in response to slow pressure fluctuations. Various CAR correlation coefficients-PRx (based on intracranial pressure-ICP), Mx (based on transcranial doppler-TCD), and COx/THx (based on near-infrared spectroscopy-NIRS)-are used interchangeably despite fundamental differences. 566 hours of ICP, NIRS, and TCD data from 38 traumatic brain injury (TBI) patients were assessed. The intercorrelation between CAR correlation coefficients was compared in relation to: (1) The impact of different filtering methods (to minimize noise); (2) The impact of slow wave power (i.e., magnitude of incoming trigger); (3) The impact of coherence (i.e., to what extent can the power of slow waves explain the change in power within the cerebral biosignal). Only coherence stratification consistently increased the metric intercorrelation to PRx (high vs. low) when evaluating Mx (0.43 vs. 0.08, p < 0.01) and THx (0.36 vs. 0.05, p < 0.01). Additionally, high coherence and ABP power were associated with fewer correlation coefficients around 0. Coherence increases the intercorrelation between the different CAR metrics. These sections might be regarded as more reliable, since they are derived from different biosignals that are all affected by CAR through different mechanisms.

Indexed as

Brain Injuries, TraumaticCerebrovascular CirculationHomeostasisAdultFemaleHumansIntracranial PressureMaleMiddle AgedSpectroscopy, Near-InfraredUltrasonography, Doppler, TranscranialYoung Adultcerebrovascular autoregulationintensive caremultimodality monitoringtraumatic brain injury

Identifiers

PMID40243158
PMCPMC12004267

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Registered trials

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Read under generation 80e0d062 · epoch 390. Bibliography from PubMed, PubMed Central and OpenAlex; grants from NIH RePORTER; trial links from ClinicalTrials.gov; estimates, votes and beliefs from the OpenQuestion graph.