Abstract
BACKGROUND: The Australian Traumatic Brain Injury Initiative (AUS-TBI) aims to co-design a data resource to predict outcomes for people with moderate-severe TBI across Australia. Fundamental to this resource is the data dictionary; an ontology of data items. Here, we report the systematic review and consensus process for inclusion of biological markers in the data dictionary.
METHODS: Standardised database searches were implemented from inception through April 2022. English-language studies evaluating association between a fluid, tissue or imaging marker and any clinical outcome in at least ten patients with moderate-severe TBI were included. Records were screened using a prioritisation algorithm and saturation threshold in Research Screener. Full-length records were then screened in Covidence. A predefined algorithm was used to assign a judgement of predictive value to each observed association, and high-value predictors were discussed in a consensus process.
FINDINGS: Searches retrieved 106,593 records. 1,417 full-length records were screened, resulting in 546 included records. 239 individual markers were extracted, evaluated against 101 distinct outcomes. 44 markers were judged to be high-value predictors of 15 outcomes. Fluid markers retained following the consensus process included neuron specific enolase, ubiquitin C-terminal Hydrolase L1 and glial fibrillary acidic protein. Imaging markers included CT scores (e.g., Marshall), pathological observations (e.g., haemorrhage, midline shift), and MRI (e.g., diffuse axonal injury). The clinical context and time of sampling of potential predictive indicators are important considerations for utility.
CONCLUSIONS: This systematic review and consensus process has identified fluid and imaging biomarkers with high predictive value of clinical and long-term outcomes following moderate-severe TBI.
| Original language | English |
|---|---|
| Pages (from-to) | 2116-2137 |
| Number of pages | 22 |
| Journal | Journal of Neurotrauma |
| Volume | 42 |
| Issue number | 21-22 |
| Early online date | 19 Dec 2023 |
| DOIs | |
| Publication status | Published - Nov 2025 |
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