4.6 Article

Prognostic value of global deep white matter DTI metrics for 1-year outcome prediction in ICU traumatic brain injury patients: an MRI-COMA and CENTER-TBI combined study

期刊

INTENSIVE CARE MEDICINE
卷 48, 期 2, 页码 201-212

出版社

SPRINGER
DOI: 10.1007/s00134-021-06583-z

关键词

Traumatic brain injury; Outcome; Prognosis; Diffusion tensor imaging; Deep white matter

资金

  1. French Ministry of Health, Paris, France (Programme Hospitalier de Recherche Clinique 2005) [051061]
  2. French National Agency for Research (ANR) [ANR-10-IAIHU-06]
  3. Regione Lombardia [2010-RF-2010-2319503]
  4. European Union [602150]
  5. Hannelore Kohl Stiftung (Germany)
  6. OneMind (USA)
  7. Integra LifeSciences Corporation (USA)
  8. Italian Ministry of health

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This study aimed to design a new classification score based on magnetic resonance diffusion metrics measured in the deep white matter between day 7 and day 35 after TBI to predict 1-year clinical outcome. The score achieved a high accuracy in predicting both favorable and unfavorable outcomes, providing objective information for ICU decision-making.
Purpose A reliable tool for outcome prognostication in severe traumatic brain injury (TBI) would improve intensive care unit (ICU) decision-making process by providing objective information to caregivers and family. This study aimed at designing a new classification score based on magnetic resonance (MR) diffusion metrics measured in the deep white matter between day 7 and day 35 after TBI to predict 1-year clinical outcome. Methods Two multicenter cohorts (29 centers) were used. MRI-COMA cohort (NCT00577954) was split into MRI-COMA-Train (50 patients enrolled between 2006 and mid-2014) and MRI-COMA-Test (140 patients followed up in clinical routine from 2014) sub-cohorts. These latter patients were pooled with 56 ICU patients (enrolled from 2014 to 2020) from CENTER-TBI cohort (NCT02210221). Patients were dichotomised depending on their 1-year Glasgow outcome scale extended (GOSE) score: GOSE 1-3, unfavorable outcome (UFO); GOSE 4-8, favorable outcome (FO). A support vector classifier incorporating fractional anisotropy and mean diffusivity measured in deep white matter, and age at the time of injury was developed to predict whether the patients would be either UFO or FO. Results The model achieved an area under the ROC curve of 0.93 on MRI-COMA-Train training dataset, and 49% sensitivity for 96.8% specificity in predicting UFO and 58.5% sensitivity for 97.1% specificity in predicting FO on the pooled MRI-COMA-Test and CENTER-TBI validation datasets. Conclusion The model successfully identified, with a specificity compatible with a personalized decision-making process in ICU, one in two patients who had an unfavorable outcome at 1 year after the injury, and two-thirds of the patients who experienced a favorable outcome.

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