| 1. |
- Dickens, Alex Mountfort, et al.
(författare)
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Serum Metabolites Associated with Computed TomographyFindings after Traumatic Brain Injury
- 2018
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Ingår i: Journal of Neurotrauma. - : Mary Ann Liebert. - 0897-7151 .- 1557-9042. ; 35:22, s. 2673-2683
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Tidskriftsartikel (refereegranskat)abstract
- There is a need to rapidly detect patients with traumatic brain injury (TBI) who require head computed tomography (CT). Given the energy crisis in the brain following TBI, we hypothesized that serum metabolomics would be a useful tool for developing a set of biomarkers to determine the need for CT and to distinguish between different types of injuries observed. Logistic regression models using metabolite data from the discovery cohort (n=144, Turku, Finland) were used to distinguish between patients with traumatic intracranial findings and negative findings on head CT. The resultant models were then tested in the validation cohort (n=66, Cambridge, UK). The levels of glial fibrillary acidic protein and ubiquitin C-terminal hydrolase-L1 were also quantified in the serum from the same patients. Despite there being significant differences in the protein biomarkers in patients with TBI, the model that determined the need for a CT scan validated poorly (AUC=0.64: Cambridge patients). However, using a combination of six metabolites (two amino acids, three sugar derivatives and one ketoacid) it was possible to discriminate patients with intracranial abnormalities on CT and patients with a normal CT (AUC=0.77 in Turku patients and AUC=0.73 in Cambridge patients). Furthermore, a combination of three metabolites could distinguish between diffuse brain injuries and mass lesions (AUC=0.87 in Turku patients and AUC=0.68 in Cambridge patients). This study identifies a set of validated serum polar metabolites, which associate with the need for a CT scan. Additionally, serum metabolites can also predict the nature of the brain injury. These metabolite markers may prevent unnecessary CT scans, thus reducing the cost of diagnostics and radiation load.
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| 2. |
- Oresic, Matej, 1967-, et al.
(författare)
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Human Serum Metabolites Associate With Severity and Patient Outcomes in Traumatic Brain Injury
- 2016
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Ingår i: EBioMedicine. - : Elsevier. - 2352-3964. ; 12, s. 118-126
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Tidskriftsartikel (refereegranskat)abstract
- Traumatic brain injury (TBI) is a major cause of death and disability worldwide, especially in children and young adults. TBI is an example of a medical condition where there are still major lacks in diagnostics and outcome prediction. Here we apply comprehensive metabolic profiling of serum samples from TBI patients and controls in two independent cohorts. The discovery study included 144 TBI patients, with the samples taken at the time of hospitalization. The patients were diagnosed as severe (sTBI; n=22), moderate (moTBI; n=14) or mild TBI (mTBI; n=108) according to Glasgow Coma Scale. The control group (n=28) comprised of acute orthopedic non-brain injuries. The validation study included sTBI (n=23), moTBI (n=7), mTBI (n=37) patients and controls (n=27). We show that two medium-chain fatty acids (decanoic and octanoic acids) and sugar derivatives including 2,3-bisphosphoglyceric acid are strongly associated with severity of TBI, and most of them are also detected at high concentrations in brain microdialysates of TBI patients. Based on metabolite concentrations from TBI patients at the time of hospitalization, an algorithm was developed that accurately predicted the patient outcomes (AUC=0.84 in validation cohort). Addition of the metabolites to the established clinical model (CRASH), comprising clinical and computed tomography data, significantly improved prediction of patient outcomes. The identified 'TBI metabotype' in serum, that may be indicative of disrupted blood-brain barrier, of protective physiological response and altered metabolism due to head trauma, offers a new venue for the development of diagnostic and prognostic markers of broad spectrum of TBIs. (C) 2016 Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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| 3. |
- Posti, Jussi P., et al.
(författare)
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SERUM METABOLITES ASSOCIATE WITH HEAD COMPUTED TOMOGRAPHY FINDINGS FOLLOWING TRAUMATIC BRAIN INJURY
- 2018
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Ingår i: Journal of Neurotrauma. - : Mary Ann Liebert. - 0897-7151 .- 1557-9042. ; 35:16, s. A67-A67
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Tidskriftsartikel (övrigt vetenskapligt/konstnärligt)abstract
- There is a need to rapidly detect patients with traumatic brain injury (TBI) who require head computed tomography (CT). Given the energy crisis in the brain following TBI, we hypothesized that serum metabolomics would be a useful tool for developing a set of bio-markers to determine the need for CT and to distinguish between different types of injuries observed. Logistic regression models using metabolite data from the discovery cohort (n=144, Turku, Finland) were used to distinguish between patients with traumatic intracranial findings and negative findings on head CT. The resultant models were then tested in the validation cohort (n=66, Cambridge, UK). The levels of glial fibrillary acidic protein and ubiquitin C-terminalhydrolase-L1 were also quantified in the serum from the same patients. Despite there being significant differences in the protein bio-markers in patients with TBI, the model that determined the need for a CT scan validated poorly (AUC=0.64: Cambridge patients). However, using a combination of six metabolites (two amino acids, thre esugar derivatives and one ketoacid) it was possible to discriminate patients with intracranial abnormalities on CT and patients with a normal CT (AUC=0.77 in Turku patients and AUC=0.73 in Cambridge patients). Furthermore, a combination of three metabolites could distinguish between diffuse brain injuries and mass lesions (AUC=0.87 in Turku patients and AUC=0.68 in Cambridge pa-tients). This study identifies a set of validated serum polar metabolites, which associate with the need for a CT scan. Additionally, serum metabolites can also predict the nature of the brain injury. These metabolite markers may prevent unnecessary CT scans, thus reducing the cost of diagnostics and radiation load.
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