Prognostic Model for Predicting Outcome After Moderate to Severe Paediatric Traumatic Brain Injury

NCT07538440 | Active Not Recruiting

• 1 other identifier: A097348
• Study Type: observational
• Target: 2,000
• Locations: 1 country
• Sites: 1

Brief Summary

Due to ethical and logistical challenges related to paediatric research, there is limited age-appropriate evidence for managing paediatric traumatic brain injury (pTBI). The prognostic models used for adult TBI research (IMPACT, CRASH), have been derived and validated from analysis of large international datasets which have undergone further validation in multiple prospective studies; the wide use of these prognostic models across neurotrauma research highlights the relative simplicity and the variables used for prediction making them applicable to both low and high resource set-ups. This has facilitated international collaborative research in adult TBI. At present, no such models exist for pTBI with most paediatric research continuing to use adult prognostic models. Though the variables used for these models show association with outcome in pTBI as well, there are multiple issues with this approach with the key difficulty being that younger age is expected to be associated with better outcome in these models; however, the balance between neuroplasticity and neurodevelopmental trajectory in children is difficult to predict with evidence suggesting worse neuro-developmental outcomes after TBI in younger children. Hence the adult models can either over- or under-predict neurological outcomes in pTBI and have never been validated in pTBI datasets. Given that the amount of data required to create pTBI predictive model is difficult to collect and reasonable validity of adult prognostic models in pTBI, investigators propose to create paediatric modification to the adult models and identify a robust pTBI predictive model for improved classification of injury severity to predict disease trajectory and outcome as well as stratification of patients for interventional research and benchmarking in pTBI to help with appropriate resource allocation for neuro-interventions towards improved outcomes. This will help identify age-appropriate benchmarks for pTBI research studies as well as complement an individual child's clinical assessment, treatment decisions, informing families and resource allocation.

Conditions

Traumatic Brain Injury (TBI)

Keywords

Paediatric; Prediction modelling; Outcome

Outcome Measures

Primary Outcomes (1)

• Glasgow Outcome Score.

  The scale ranges from 1 to 5 with increasing scores suggesting improving outcome (1-death, 5-normal). The score will be dichotomised to favourable (4-5) and unfavourable (1-3).

  6 months

Study Arms (4)

ADAPT

International Paediatric severe traumatic brain injury prospective study- 1000 patients

STARSHIP

Prospective multicentre researchdatabase of Paediatric moderate to severe TBI of 135 patients

CENTER-TBI

Prospective research database of traumatic brain injury, 227 patients \<18 years of age.

Cambridge

Database of Paediatric TBI admissions to CUH, 350 patients

Eligibility Criteria

• Age: Up to 18 Years
• Sex: all
• Healthy Volunteers: No
• Age Groups: Child (0-17), Adult (18-64)
• Sampling Method: Non-Probability Sample

Study Population

The existing datasets of paediatric patients with moderate to severe TBI will be combined and prediction model will be developed using the baseline injury severity variables with training and validation groups.

You may qualify if:

• Patients admitted to hospital with moderate to severe TBI

You may not qualify if:

• None

Sponsors & Collaborators

• Cambridge University Hospitals NHS Foundation Trust: lead
• UMC Utrecht: collaborator

Study Sites (1)

Hospital

Cambridge, Cambridgeshire, CB2 2QQ, United Kingdom

Location

Related Publications (9)

• Steyerberg EW, Harrell FE Jr. Prediction models need appropriate internal, internal-external, and external validation. J Clin Epidemiol. 2016 Jan;69:245-7. doi: 10.1016/j.jclinepi.2015.04.005. Epub 2015 Apr 18. No abstract available.

  PMID: 25981519 BACKGROUND

• Huth SF, Slater A, Waak M, Barlow K, Raman S. Predicting Neurological Recovery after Traumatic Brain Injury in Children: A Systematic Review of Prognostic Models. J Neurotrauma. 2020 Oct 15;37(20):2141-2149. doi: 10.1089/neu.2020.7158. Epub 2020 Jul 20.

  PMID: 32460675 BACKGROUND

• Young AM, Guilfoyle MR, Fernandes H, Garnett MR, Agrawal S, Hutchinson PJ. The application of adult traumatic brain injury models in a pediatric cohort. J Neurosurg Pediatr. 2016 Nov;18(5):558-564. doi: 10.3171/2016.5.PEDS15427. Epub 2016 Aug 26.

  PMID: 27564785 BACKGROUND

• Yue JK, Lee YM, Sun X, van Essen TA, Elguindy MM, Belton PJ, Pisica D, Mikolic A, Deng H, Kanter JH, McCrea MA, Bodien YG, Satris GG, Wong JC, Ambati VS, Grandhi R, Puccio AM, Mukherjee P, Valadka AB, Tarapore PE, Huang MC, DiGiorgio AM, Markowitz AJ, Yuh EL, Okonkwo DO, Steyerberg EW, Lingsma HF, Menon DK, Maas AIR, Jain S, Manley GT; The TRACK-TBI Investigators. Performance of the IMPACT and CRASH prognostic models for traumatic brain injury in a contemporary multicenter cohort: a TRACK-TBI study. J Neurosurg. 2024 Mar 15;141(2):417-429. doi: 10.3171/2023.11.JNS231425. Print 2024 Aug 1.

  PMID: 38489823 BACKGROUND

• Maas AI, Hukkelhoven CW, Marshall LF, Steyerberg EW. Prediction of outcome in traumatic brain injury with computed tomographic characteristics: a comparison between the computed tomographic classification and combinations of computed tomographic predictors. Neurosurgery. 2005 Dec;57(6):1173-82; discussion 1173-82. doi: 10.1227/01.neu.0000186013.63046.6b.

  PMID: 16331165 BACKGROUND

• Martin FP, Goronflot T, Moyer JD, Huet O, Asehnoune K, Cinotti R, Gourraud PA, Roquilly A. Predictive Models of Long-Term Outcome in Patients with Moderate to Severe Traumatic Brain Injury are Biased Toward Mortality Prediction. Neurocrit Care. 2025 Apr;42(2):573-586. doi: 10.1007/s12028-024-02082-3. Epub 2024 Aug 13.

  PMID: 39138720 BACKGROUND

• Sta Maria NS, Sargolzaei S, Prins ML, Dennis EL, Asarnow RF, Hovda DA, Harris NG, Giza CC. Bridging the gap: Mechanisms of plasticity and repair after pediatric TBI. Exp Neurol. 2019 Aug;318:78-91. doi: 10.1016/j.expneurol.2019.04.016. Epub 2019 May 2.

  PMID: 31055004 BACKGROUND

• Speer EM, Lee LK, Bourgeois FT, Gitterman D, Hay WW Jr, Davis JM, Javier JR. The state and future of pediatric research-an introductory overview : The state and future of pediatric research series. Pediatr Res. 2023 Jan 24:1-5. doi: 10.1038/s41390-022-02439-4. Online ahead of print.

  PMID: 36694026 BACKGROUND

• Dewan MC, Mummareddy N, Wellons JC 3rd, Bonfield CM. Epidemiology of Global Pediatric Traumatic Brain Injury: Qualitative Review. World Neurosurg. 2016 Jul;91:497-509.e1. doi: 10.1016/j.wneu.2016.03.045. Epub 2016 Mar 25.

  PMID: 27018009 BACKGROUND

MeSH Terms

Conditions

Brain Injuries, Traumatic

Condition Hierarchy (Ancestors)

Brain Injuries; Brain Diseases; Central Nervous System Diseases; Nervous System Diseases; Craniocerebral Trauma; Trauma, Nervous System; Wounds and Injuries

Study Design

• Study Type: observational
• Observational Model: OTHER
• Time Perspective: OTHER
• Target Duration: 6 Months
• Sponsor Type: OTHER
• Responsible Party: PRINCIPAL INVESTIGATOR
• PI Title: PICU Consultant

Study Record Dates

• First Submitted: April 12, 2026
• First Posted: April 20, 2026
• Study Start: July 1, 2025
• Primary Completion (Estimated): July 1, 2026
• Study Completion (Estimated): December 1, 2026
• Last Updated: April 22, 2026

Record last verified: 2026-04

Data Sharing

• IPD Sharing: Will not share

Locations

GB (1)