Evidence map›Paper›PMID 42215827›Full record

ArticleNeurocritical care2026

Toward Causal Relationships of Intracranial Pressure, Cerebrovascular Reactivity, Interventions, and Outcome in Severe Traumatic Brain Injury: A CENTER-TBI High-Resolution Substudy.

Cecilia A I Åkerlund, Anders Holst, Erta Beqiri, Peter Smielewski, Ari Ercole, David Nelson, CENTER-TBI High-Resolution Substudy participants

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Article in Neurocritical care, 2026. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Not yet cited in PubMed.

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1 · What the graph read from it

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2 · The registry

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3 · Its place in the literature

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4 · The record

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5 · Who and what money

Authors and funding

7 authors.

Cecilia A I ÅkerlundDepartment of Physiology and Pharmacology, Section of Anaesthesia and Intensive Care, Department of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden. cecilia.akerlund@ki.se.ORCID http://orcid.org/0000-0003-4918-1482
Anders HolstSchool of Electrical Engineering and Computer Science, KTH Royal Institute of Technology, Stockholm, Sweden.
Erta BeqiriBrain Physics Lab, Department of Clinical Neuroscience, University of Cambridge, Cambridge, UK.
Peter SmielewskiBrain Physics Lab, Department of Clinical Neuroscience, University of Cambridge, Cambridge, UK.
Ari ErcoleDivision of Anaesthesia, Department of Medicine, University of Cambridge, Cambridge, UK.
David NelsonDepartment of Physiology and Pharmacology, Section of Anaesthesia and Intensive Care, Department of Physiology and Pharmacology, Karolinska Institute, Stockholm, Sweden.
CENTER-TBI High-Resolution Substudy participants

Funding

FP7 Health 602150Region Stockholm Clinical postdoctoral appointment
6 · The paper itself

Abstract

backgroundMost available evidence for treatment and outcome prediction in traumatic brain injuries (TBI) is derived from observational studies. Such association studies provide limited evidence for the causality of relationships. While randomized controlled trials are appropriately regarded as the gold standard for causal inference, there are many domains where such experimental approaches are not feasible. During the last decades however, mathematical methods have been developed to infer causal relationships from observational data. This study aims to investigate causal relations of systemic and cerebral physiological parameters, intracranial pressure (ICP)-lowering interventions, and outcome in patients with severe TBI.

methodsPatients with severe TBI enrolled in the prospective observational Collaborative European Neurotrauma Effectiveness Research in TBI (CENTER-TBI) High-Resolution Substudy group were included (n = 201). We applied a causal inference algorithm to determine causal relations between the first week post-injury mean of values of ICP, cerebrovascular reactivity (PRx), cerebral perfusion pressure (CPP), heart rate, oxygen saturation, arterial partial pressure of carbon dioxide, ICP-lowering therapies [represented by the therapy intensity level (TIL) score], and 6-month outcome represented by Glasgow Outcome Scale-Extended (GOSE).

resultsThe median age was 51.5 years [interquartile range (IQR) 31 to 64], 158 were men (77.5%), and median GOSE at 6 months was 3 (IQR 3 to 5). PRx and TIL score were the only features identified as directly related to outcome in this analysis (r = - 0.19, p = 0.003; r = - 0.20, p = 0.002, respectively). Significant correlations between ICP and CPP (r = - 0.62, p < 0.0001); ICP and PRx (r = 0.31, p < 0.001); PRx and heart rate (r = 0.17, p = 0.007); and PaCO

conclusionsThe results suggest that cerebrovascular autoregulation status (PRx) and ICP-lowering therapies may be more directly associated with outcomes than ICP itself and that these factors should be considered in ICP monitoring and management strategies.

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Brain injuriesCritical careIntracranial pressureTraumatic

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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.