Assessment of White Matter Injury and Outcome in Severe Brain Trauma
| Autor: | Rajiv Gupta, Sébastien Faivre, Louis Puybasset, Thomas Tourdias, Audrey Vanhaudenhuyse, Frédéric Dailler, Françoise Masson, Danielle Ibarrola, Alexandre Krainik, Luaba Tshibanda, Jean François Le Bas, Nicolas Bruder, Gustavo Soto-Ares, Habib Benali, Emmanuelle Schmitt, Jean François Payen, Nicolas Menjot de Champfleur, Eléonore Tollard, Edith André, Vincent Perlbarg, Benoit Veber, Vincent Cottenceau, Nadine Girard, Gérard Audibert, Steven Laureys, Damien Galanaud, Robert Stevens, Paola Sanchez, Julien Dinkel |
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| Rok vydání: | 2012 |
| Předmět: |
medicine.medical_specialty
Receiver operating characteristic medicine.diagnostic_test business.industry Traumatic brain injury Glasgow Outcome Scale Poison control Magnetic resonance imaging medicine.disease 030218 nuclear medicine & medical imaging Surgery White matter 03 medical and health sciences 0302 clinical medicine Anesthesiology and Pain Medicine medicine.anatomical_structure Cohort medicine Radiology business 030217 neurology & neurosurgery Diffusion MRI |
| Zdroj: | Anesthesiology. 117:1300-1310 |
| ISSN: | 0003-3022 |
| DOI: | 10.1097/aln.0b013e3182755558 |
| Popis: | Background Existing methods to predict recovery after severe traumatic brain injury lack accuracy. The aim of this study is to determine the prognostic value of quantitative diffusion tensor imaging (DTI). Methods In a multicenter study, the authors prospectively enrolled 105 patients who remained comatose at least 7 days after traumatic brain injury. Patients underwent brain magnetic resonance imaging, including DTI in 20 preselected white matter tracts. Patients were evaluated at 1 yr with a modified Glasgow Outcome Scale. A composite DTI score was constructed for outcome prognostication on this training database and then validated on an independent database (n=38). DTI score was compared with the International Mission for Prognosis and Analysis of Clinical Trials Score. Results Using the DTI score for prediction of unfavorable outcome on the training database, the area under the receiver operating characteristic curve was 0.84 (95% CI: 0.75-0.91). The DTI score had a sensitivity of 64% and a specificity of 95% for the prediction of unfavorable outcome. On the validation-independent database, the area under the receiver operating characteristic curve was 0.80 (95% CI: 0.54-0.94). On the training database, reclassification methods showed significant improvement of classification accuracy (P < 0.05) compared with the International Mission for Prognosis and Analysis of Clinical Trials score. Similar results were observed on the validation database. Conclusions White matter assessment with quantitative DTI increases the accuracy of long-term outcome prediction compared with the available clinical/radiographic prognostic score. |
| Databáze: | OpenAIRE |
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