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| Name | Class |
|---|---|
| UMC Utrecht | OTHER |
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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.
Background The healthcare, societal and economic impact from paediatric traumatic brain injury (pTBI) is one of the greatest unmet needs with estimates suggesting upto 2/3rd of survivors developing life-long neurological deficits. Due to ethical and logistical challenges related to paediatric research, there is limited age-appropriate evidence for children which perpetuates the funding gaps further confounding the lack of evidence. However, extrapolation of adult TBI research evidence to children is inaccurate and inappropriate given the differences in mechanisms and patterns of injury, pathophysiological responses and neurological recovery from it, in the context of developmental trajectory; hence, robust evidence is required to improve outcomes from pTBI as well as facilitate research collaborations.
The prognostic models used for adult TBI research (IMPACT, CRASH)5,6 and imaging criteria (Marshall and Rotterdam scores), 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; however, no such models exist for pTBI with most pTBI 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 the age variable. In the adult models, the younger age is expected to be associated with better outcome; for CRASH, the model is likely weighed heavily towards non-age variables as the younger patients are expected to do better with patients between 18-40 lumped as <40 years and for IMPACT, slightly better which accounts for 14 years and above.
However, the balance between neuroplasticity and neurodevelopmental trajectory in paediatric age group 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.
Rationale & Theoretical Framework A validated predictive model for pTBI would be the first step towards collaborative research and identifying age-appropriate benchmarks for pTBI research studies as well as to complement an individual child's clinical assessment, treatment decisions, informing families and resource allocation. Given that the amount of data required to create pTBI predictive model is difficult to collect and the reasonable validity of adult prognostic models in pTBI, albeit in small single-centre studies, 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.
Research Question/Aims and Objectives:
To create and validate a paediatric specific prognostic model for outcomes following moderate to severe TBI for use in both resource-limited and resource-rich environments. The study hypothesis is that the performance of the current adult TBI prognostic models in predicting outcomes following pTBI can be improved by introducing age-appropriate modifications to the existing models.
Study Design/ Methods:
The study will use combined retrospective pTBI datasets (moderate to severe TBI in children < 18 years).
Sample & Statistical Methods:
There is no defined sample size for the study. Investigators aim to collect datasets which contain the variables defining injury severity from children with moderate to severe TBI upto the age of 18 years. There are no exclusion criteria for the study. All the datasets will either be from a prospective study (ethics approved with valid consent) and/or datasets created for audit/institutional purposes with appropriate approvals from local/national research committees and contain anonymised non-identifiable information.
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| Label | Type | Description | Intervention Names |
|---|---|---|---|
| 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 |
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| Measure | Description | Time Frame |
|---|---|---|
| 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 |
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Inclusion Criteria:
Exclusion Criteria:
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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.
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| Facility | Status | City | State | ZIP | Country | Contacts |
|---|---|---|---|---|---|---|
| Hospital | Cambridge | Cambridgeshire | CB2 2QQ | United Kingdom |
| PubMed Identifier | Type | Citation | Retractions |
|---|---|---|---|
| 25981519 | Background | 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. | |
| 32460675 | 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. |
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As per the data share agreement with existing datasets, the combined dataset will only be used for the prediction modelling. However, the individual dataset controllers maybe willing to consider valid scientific requests as per their arrangements
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| Type | Includes Protocol | Includes SAP | Includes ICF | Document Label | Document Date | Document Uploaded Date | Document File Name |
|---|---|---|---|---|---|---|---|
| Prot | Yes | No | No | Study Protocol | Mar 21, 2025 | Apr 12, 2026 | Prot_000.pdf |
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| ID | Term |
|---|---|
| D000070642 | Brain Injuries, Traumatic |
| ID | Term |
|---|---|
| D001930 | Brain Injuries |
| D001927 | Brain Diseases |
| D002493 | Central Nervous System Diseases |
| D009422 | Nervous System Diseases |
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| 27564785 | 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. |
| 38489823 | 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. |
| 16331165 | 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. |
| 39138720 | 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. |
| 31055004 | 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. |
| 36694026 | 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. |
| 27018009 | 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. |
| D006259 |
| Craniocerebral Trauma |
| D020196 | Trauma, Nervous System |
| D014947 | Wounds and Injuries |