Literature DB >> 33161840

Outcome Prediction after Moderate and Severe Traumatic Brain Injury: External Validation of Two Established Prognostic Models in 1742 European Patients.

Simone A Dijkland1, Isabel R A Retel Helmrich1, Daan Nieboer1, Mathieu van der Jagt2, Diederik W J Dippel3, David K Menon4, Nino Stocchetti5,6, Andrew I R Maas7, Hester F Lingsma1, Ewout W Steyerberg1,8.   

Abstract

The International Mission on Prognosis and Analysis of Clinical Trials in Traumatic Brain Injury (IMPACT) and Corticoid Randomisation After Significant Head injury (CRASH) prognostic models predict functional outcome after moderate and severe traumatic brain injury (TBI). We aimed to assess their performance in a contemporary cohort of patients across Europe. The Collaborative European NeuroTrauma Effectiveness Research in Traumatic Brain Injury (CENTER-TBI) core study is a prospective, observational cohort study in patients presenting with TBI and an indication for brain computed tomography. The CENTER-TBI core cohort consists of 4509 TBI patients available for analyses from 59 centers in 18 countries across Europe and Israel. The IMPACT validation cohort included 1173 patients with GCS ≤12, age ≥14, and 6-month Glasgow Outcome Scale-Extended (GOSE) available. The CRASH validation cohort contained 1742 patients with GCS ≤14, age ≥16, and 14-day mortality or 6-month GOSE available. Performance of the three IMPACT and two CRASH model variants was assessed with discrimination (area under the receiver operating characteristic curve; AUC) and calibration (comparison of observed vs. predicted outcome rates). For IMPACT, model discrimination was good, with AUCs ranging between 0.77 and 0.85 in 1173 patients and between 0.80 and 0.88 in the broader CRASH selection (n = 1742). For CRASH, AUCs ranged between 0.82 and 0.88 in 1742 patients and between 0.66 and 0.80 in the stricter IMPACT selection (n = 1173). Calibration of the IMPACT and CRASH models was generally moderate, with calibration-in-the-large and calibration slopes ranging between -2.02 and 0.61 and between 0.48 and 1.39, respectively. The IMPACT and CRASH models adequately identify patients at high risk for mortality or unfavorable outcome, which supports their use in research settings and for benchmarking in the context of quality-of-care assessment.

Entities:  

Keywords:  clinical prediction model; external validation; outcome; prognosis; traumatic brain injury

Mesh:

Year:  2020        PMID: 33161840     DOI: 10.1089/neu.2020.7300

Source DB:  PubMed          Journal:  J Neurotrauma        ISSN: 0897-7151            Impact factor:   5.269


  9 in total

Review 1.  Prognostic Models in Severe Traumatic Brain Injury: A Systematic Review and Meta-analysis.

Authors:  Rita de Cássia Almeida Vieira; Juliana Cristina Pereira Silveira; Wellingson Silva Paiva; Daniel Vieira de Oliveira; Camila Pedroso Estevam de Souza; Eduesley Santana-Santos; Regina Marcia Cardoso de Sousa
Journal:  Neurocrit Care       Date:  2022-08-09       Impact factor: 3.532

Review 2.  Management of moderate to severe traumatic brain injury: an update for the intensivist.

Authors:  Geert Meyfroidt; Pierre Bouzat; Michael P Casaer; Randall Chesnut; Sophie Rym Hamada; Raimund Helbok; Peter Hutchinson; Andrew I R Maas; Geoffrey Manley; David K Menon; Virginia F J Newcombe; Mauro Oddo; Chiara Robba; Lori Shutter; Martin Smith; Ewout W Steyerberg; Nino Stocchetti; Fabio Silvio Taccone; Lindsay Wilson; Elisa R Zanier; Giuseppe Citerio
Journal:  Intensive Care Med       Date:  2022-05-20       Impact factor: 41.787

3.  Serum metabolome associated with severity of acute traumatic brain injury.

Authors:  Ilias Thomas; Alex M Dickens; Jussi P Posti; Endre Czeiter; Daniel Duberg; Tim Sinioja; Matilda Kråkström; Isabel R A Retel Helmrich; Kevin K W Wang; Andrew I R Maas; Ewout W Steyerberg; David K Menon; Olli Tenovuo; Tuulia Hyötyläinen; András Büki; Matej Orešič
Journal:  Nat Commun       Date:  2022-05-10       Impact factor: 17.694

4.  Unmasking Covert Language Processing in the Intensive Care Unit with Electroencephalography.

Authors:  Brian L Edlow; Lionel Naccache
Journal:  Ann Neurol       Date:  2021-02-16       Impact factor: 10.422

5.  Continuous Determination of the Optimal Bispectral Index Value Based on Cerebrovascular Reactivity in Moderate/Severe Traumatic Brain Injury: A Retrospective Observational Cohort Study of a Novel Individualized Sedation Target.

Authors:  Logan Froese; Alwyn Gomez; Amanjyot Singh Sainbhi; Carleen Batson; Kevin Stein; Arsalan Alizadeh; Asher A Mendelson; Frederick A Zeiler
Journal:  Crit Care Explor       Date:  2022-03-04

6.  Impact of Age and Biological Sex on Cerebrovascular Reactivity in Adult Moderate/Severe Traumatic Brain Injury: An Exploratory Analysis.

Authors:  Carleen Batson; Logan Froese; Alwyn Gomez; Amanjyot Singh Sainbhi; Kevin Y Stein; Arsalan Alizadeh; Frederick A Zeiler
Journal:  Neurotrauma Rep       Date:  2021-11-09

Review 7.  A Precision Medicine Agenda in Traumatic Brain Injury.

Authors:  Jovany Cruz Navarro; Lucido L Ponce Mejia; Claudia Robertson
Journal:  Front Pharmacol       Date:  2022-03-16       Impact factor: 5.810

8.  Does poor methodological quality of prediction modeling studies translate to poor model performance? An illustration in traumatic brain injury.

Authors:  Isabel R A Retel Helmrich; Ana Mikolić; David M Kent; Hester F Lingsma; Laure Wynants; Ewout W Steyerberg; David van Klaveren
Journal:  Diagn Progn Res       Date:  2022-05-05

9.  Selection of CT variables and prognostic models for outcome prediction in patients with traumatic brain injury.

Authors:  Djino Khaki; Virpi Hietanen; Alba Corell; Helena Odenstedt Hergès; Johan Ljungqvist
Journal:  Scand J Trauma Resusc Emerg Med       Date:  2021-07-17       Impact factor: 2.953

  9 in total

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