ReviewBrain : a journal of neurology2025
The normative modelling framework for traumatic brain injury.
Review in Brain : a journal of neurology, 2025. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 2 papers.
What it found
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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.
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.
Who cites it
2 citing papers in PubMed.
- The Framework of Policy Transition in TBI: From GCS to CBI-M.Neurocritical care · 2026Article
- Review
Corrections and comments
PubMed lists nothing against this paper. Absence here is not a guarantee, only a check that was made.
Authors and funding
10 authors.
Funding
Abstract
This review examines the principles, applications and methodological foundations of normative modelling, emphasizing its potential to assist in mitigating longstanding challenges in traumatic brain injury (TBI) research and management. TBI remains a major global health concern, with an incidence exceeding 50-60 million cases worldwide. Progress in research and clinical practice has been hindered by the complex and heterogeneous nature of TBI, arising from diverse aetiologies, injury mechanisms and pathophysiological processes that lead to variable clinical presentations. A significant obstacle, particularly present within neuroimaging, is the continued reliance on classification scales and analytical models that do not account for nuanced differences among patients. For example, the Glasgow Coma Scale and many prevalent models categorize injury severity levels by assuming homogeneity within groups, which inevitably results in heterogeneity and obscures individual variability. Similarly, traditional case-control research designs separate injury and control groups to conduct group difference testing, diluting valuable individual data by focusing on mean comparisons. We advocate for a paradigm shift towards normative modelling-a flexible framework that assesses individual differences by comparing patients to a reference cohort. This approach moves beyond traditional methods that emphasize group differences, addressing the limitations of conventional classification by avoiding the aggregation of TBI patients into heterogeneous categories based on simplistic measures. By capturing the full spectrum of variability, normative modelling has the potential to improve patient selection in clinical trials and foster more personalized treatment strategies. Adopting this innovative approach aims to enhance outcomes for TBI patients by emphasizing individual variability rather than relying on broad group classifications. Normative modelling promises to transform the translation of TBI research into clinical practice, ultimately driving progress towards more effective, tailored interventions.
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Registered trials
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 Socratic graph.