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- Czeiter, Endre, et al.
(författare)
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Brain Injury Biomarkers May Improve the Predictive Power of the IMPACT Outcome Calculator
- 2012
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Ingår i: Journal of Neurotrauma. - : Mary Ann Liebert. - 0897-7151 .- 1557-9042. ; 29:9, s. 1770-1778
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Tidskriftsartikel (refereegranskat)abstract
- Outcome prediction following severe traumatic brain injury (sTBI) is a widely investigated field of research. A major breakthrough is represented by the IMPACT prognostic calculator based on admission data of more than 8500 patients. A growing body of scientific evidence has shown that clinically meaningful biomarkers, including glial fibrillary acidic protein (GFAP), ubiquitin C-terminal hydrolase-L1 (UCH-L1), and alpha II-spectrin breakdown product (SBDP145), could also contribute to outcome prediction. The present study was initiated to assess whether the addition of biomarkers to the IMPACT prognostic calculator could improve its predictive power. Forty-five sTBI patients (GCS score <= 8) from four different sites were investigated. We utilized the core model of the IMPACT calculator (age, GCS motor score, and reaction of pupils), and measured the level of GFAP, UCH-L1, and SBDP145 in serum and cerebrospinal fluid (CSF). The forecast and actual 6-month outcomes were compared by logistic regression analysis. The results of the core model itself, as well as serum values of GFAP and CSF levels of SBDP145, showed a significant correlation with the 6-month mortality using a univariate analysis. In the core model, the Nagelkerke R-2 value was 0.214. With multivariate analysis we were able to increase this predictive power with one additional biomarker (GFAP in CSF) to R-2 = 0.476, while the application of three biomarker levels (GFAP in CSF, GFAP in serum, and SBDP145 in CSF) increased the Nagelkerke R-2 to 0.700. Our preliminary results underline the importance of biomarkers in outcome prediction, and encourage further investigation to expand the predictive power of contemporary outcome calculators and prognostic models in TBI.
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| 3. |
- Mondello, Stefania, et al.
(författare)
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Glial Neuronal Ratio : A Novel Index for Differentiating Injury Type in Patients with Severe Traumatic Brain Injury
- 2012
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Ingår i: Journal of Neurotrauma. - : Mary Ann Liebert. - 0897-7151 .- 1557-9042. ; 29:6, s. 1096-1104
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Tidskriftsartikel (refereegranskat)abstract
- Neurobiochemical marker levels in blood after traumatic brain injury (TBI) may reflect structural changes detected by neuroimaging. This study evaluates whether correlations between neuronal (ubiquitin carboxyterminal hydrolase-L1 [UCH-L1]) and glial (glial fibrillary acidic protein [GFAP]) biomarkers may be used as an indicator for differing intracranial pathologies after brain trauma. In 59 patients with severe TBI (Glasgow Coma Scale [GCS] score <= 8) serum samples were obtained at the time of hospital admission and analyzed for UCH-L1 and GFAP. Glial neuronal ratio (GNR) was evaluated as the ratio between GFAP and UCH-L1 concentrations. A logistic regression analysis was used to identify variables associated with type of injury. GNR had a median of 0.85 and was positively correlated with age (R = 0.45, p = 0.003). Twenty-nine patients presented with diffuse injury and 30 with focal mass lesions as assessed by CT scan at admission and classified according to the Marshall Classification. GNR was significantly higher in the focal mass lesion group compared with the diffuse injury group (1.77 versus 0.48, respectively; p = 0.003). Receiver operating characteristic curve analysis showed that GNR discriminated between types of injury (area under the curve [AUC] = 0.72; p = 0.003). GNR was more accurate earlier (<= 12 h after injury) than later (AUC = 0.80; p = 0.002). Increased GNR was independently associated with type of injury, but not age, gender, GCS score, or mechanism of injury. GNR was significantly higher in patients who died, but was not an independent predictor of death. The data from the present study indicate that GNR provides valuable information about different injury pathways, which may be of diagnostic significance. In addition, GNR may help to identify different pathophysiological mechanisms following different types of brain trauma, with implications for therapeutic interventions.
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| 4. |
- Nieves, P., et al.
(författare)
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Database of novel magnetic materials for high-performance permanent magnet development
- 2019
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Ingår i: Computational materials science. - : Elsevier. - 0927-0256 .- 1879-0801. ; 168, s. 188-202
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Tidskriftsartikel (refereegranskat)abstract
- This paper describes the open Novamag database that has been developed for the design of novel Rare-Earth free/lean permanent magnets. Its main features as software technologies, friendly graphical user interface, advanced search mode, plotting tool and available data are explained in detail. Following the philosophy and standards of Materials Genome Initiative, it contains significant results of novel magnetic phases with high magnetocrystalline anisotropy obtained by three computational high-throughput screening approaches based on a crystal structure prediction method using an Adaptive Genetic Algorithm, tetragonally distortion of cubic phases and tuning known phases by doping. Additionally, it also includes theoretical and experimental data about fundamental magnetic material properties such as magnetic moments, magnetocrystalline anisotropy energy, exchange parameters, Curie temperature, domain wall width, exchange stiffness, coercivity and maximum energy product, that can be used in the study and design of new promising high-performance Rare-Earth free/lean permanent magnets. The results therein contained might provide some insights into the ongoing debate about the theoretical performance limits beyond Rare-Earth based magnets. Finally, some general strategies are discussed to design possible experimental routes for exploring most promising theoretical novel materials found in the database.
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