Evidence map›Paper›PMID 41082603›Full record

Observational studyCritical care explorations2025

Physiological Signal Entropy in Pediatric Traumatic Brain Injury: Looking Beyond the Obvious: A STARSHIP Study.

Stefan Yu Bögli, Claudia Ann Smith, Peter Hutchinson, Shruti Agrawal, Peter Smielewski, Studying Trends of Autoregulation in Severe Head Injury in Paediatrics (STARSHIP) study team

Abstract readMulticenter StudyObservational Study
In one paragraph

Observational study in Critical care explorations, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 1 paper.

0numbers the graph read from it
0cells of the map it votes in
1citing 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

1 citing paper in PubMed.

  1. Article
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

6 authors.

Stefan Yu BögliBrain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.ORCID 0000-0001-5386-0811
Claudia Ann SmithBrain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.
Peter HutchinsonDivision of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.
Shruti AgrawalDepartment of Paediatrics, Cambridge University, Cambridge, United Kingdom.
Peter SmielewskiBrain Physics Laboratory, Division of Neurosurgery, Department of Clinical Neurosciences, University of Cambridge, Cambridge, United Kingdom.
Studying Trends of Autoregulation in Severe Head Injury in Paediatrics (STARSHIP) study team

Funding

Action Medical Research for Children’s Charity GN2609Patrick & Margaret Flanagan Skye Cambridge Trust Scholarship NA
6 · The paper itself

Abstract

objectivesMultimodality monitoring based prognostication in pediatric traumatic brain injury (TBI) relies heavily on the evaluation of instantaneous and easily interpretable monitoring values. Entropy quantifies the level of disorder within a system reflecting overall activity of sensitive closed-loop feedback homeostatic mechanisms. Multiscale entropy (MSE) assesses entropy across different time scales to examine various physiologic systems and processes that operate across different time scales. The current understanding of MSE suggests that low entropy reflects increased rigidity of the various homeostatic control systems, reflecting underperformance of mechanisms such as cerebral autoregulation. This hypothesis-generating retrospective study explores the value of MSE for prognostication after pediatric TBI.

designRetrospective analysis of data from an observational multicenter database.

settingTen PICUs across the United Kingdom. PATIENTS: One hundred thirty-five children with severe pediatric TBI receiving invasive neuromonitoring between 2018 and 2022.

interventionsNone. MEASUREMENTS AND MAIN

resultsMSE was calculated based on 10-second time trends of different biosignals (incl. blood pressure, heart rate, intracranial pressure [ICP]). MSE metrics were assessed using univariable and multivariable (logistic regression with backward stepwise elimination and sliding dichotomy) methods. Last, correlation coefficients between MSE and clinical or monitoring metrics were assessed. Decreased MSE of physiologic biosignals were associated with worse outcomes and remained associated with outcomes when added to multivariable analyses. Within multivariable logistic regression analyses (covariates: Injury Severity Score [ISS], Rotterdam score, ICP, pressure reactivity index [PRx]), the resulting odds ratios (ORs) were: MSE arterial blood pressure (abp: OR, 0.83; p = 0.014), MSE cerebral perfusion pressure (cpp: OR, 0.86; p = 0.024), and MSE icp (OR, 0.87; p = 0.029). MSE displayed weak associations with clinical parameters reflecting higher TBI severity (i.e., ISS, Abbreviated Injury Scale, Glasgow Coma Scale, etc.) but moderate correlations with PRx (correlation coefficients: MSE abp, -0.47; MSE cpp, -0.55) and ICP (MSE abp, -0.3).

conclusionsBiosignal complexity is a promising tool for improving individualized prognostication after pediatric TBI. Our results further underpin the association between MSE and the function of physiologic autoregulatory mechanisms.

Indexed as

Brain Injuries, TraumaticEntropyAdolescentBlood PressureChildChild, PreschoolFemaleHeart RateHomeostasisHumansInfantIntensive Care Units, PediatricIntracranial PressureMaleMonitoring, PhysiologicPrognosisentropymultimodality neuromonitoringneurocritical careprognosticationtraumatic brain injury

Identifiers

PMID41082603
PMCPMC12520216

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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.